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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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Suggested Citation:"Appendix C - STREAM Applied to Driver Information Systems." National Academies of Sciences, Engineering, and Medicine. 2013. Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance. Washington, DC: The National Academies Press. doi: 10.17226/22448.
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71 Population growth and urbanization have increased traffic con- gestion around the world. An increasing number of US high- ways and roads experience overwhelming traffic congestion, even though most Interstate physical and safety conditions have been improved. According to a report by the Texas Transporta- tion Institute (TTI), based on congestion trends for 439 selected areas from 1982 to 2007, traffic congestion is costing Americans $87.2 billion (in constant 2007 dollars) in wasted time and fuel annually. Many metropolitan areas in the world including but not limited to London, Paris, Stockholm, Tokyo, and Beijing are experiencing serious traffic congestion that causes significant economic losses. (Liu, Triantis and Sarangi, 2010). Frame Congestion is common among some of the most economi- cally and culturally vibrant cities in the world. However, con- cern is growing about the economic and environmental costs associated with congestion. Cities cannot afford to let conges- tion continue unmanaged because it can become a serious competitive disadvantage, hindering their capacity to con- tinue developing and attracting new talent and new capital (de Palma and Lindsey, 2011). The construction of new road infrastructure, an approach traditionally used to mitigate congestion, has also become a less viable solution because of social, environmental, geo- graphic, and financial barriers. As a result, transportation agen- cies are exploring new ideas and methods to manage traffic. These include policies for expanding the capacity of existing roads through new control methods (e.g., ramp metering, lane control), policies for increasing the cost of private mobility (e.g., congestion pricing), and policies for providing motorists with the information they need to travel the road infrastruc- ture more efficiently (e.g., adaptive signal systems, in-vehicle road guidance) (Emmerink and Nijkamp, 1999). Of these emerging possibilities, development of driver infor- mation systems may be one of the most challenging and prom- ising for transportation agencies. This novel approach could help motorists use the road infrastructure more efficiently and, as a result, reduce congestion (Kitamura et al., 1999). However, this approach also requires that transportation agencies recon- sider their traditional role in providing traffic information to motorists as well as the synergies needed with other relevant parties, such as automakers, telecommunications companies, and transportation companies. Thus, transportation agen- cies are seeking ways to best contribute to this setting, to add real value to existing driver information systems, and to better identify and incorporate emerging technologies aligned with their goals and functions. The options for this area of agency function can be framed in terms allowing for the STREAM approach to be applied. In terms of mobility, the research team considers that congestion problems are mitigated in a transportation system when motor- ists reduce their average travel times and increase their average travel speed, and, when there is an expansion of the transpor- tation network’s capacity. In terms of safety, the research team believes that the system improves once it has been possible to reduce the propensity of accidents in a transportation network, the severity of accidents, and the vehicles affected by average car collisions. Finally, in terms of sustainability, the research team considers that a transportation system improves under this dimension when motorists reduce their GHG emissions during travel. Major inputs to the STREAM analysis of driver information systems are as follows: • Functions: Provision of traffic and safety information services directly to motorists; • Goals: Reduce congestion in order to contribute to three main agency goals: mobility, safety and sustainability; • Objectives (Metrics): Agency’s objectives: – Mobility: 77 Average Travel Time (hr/trip), 77 Average Speed of Vehicles (mi/hr), 77 Road Capacity (Max Vehicle/hr/lane); 77 Demand (Vehicle/hr); A p p e n d i x C STREAM Applied to Driver Information Systems

72 – Safety: 77 Highway accidents propensity (collisions/yr/mi), 77 Severity of accidents (fatalities/collision/mi), 77 Average vehicles affected per collision (vehicles/ collision/mi); – Sustainability: 77 Average GHG emission (GHG/trip/vehicle type) The Growing Challenges of Private Mobility Transportation problems arising from the use of automo- biles are among the most pressing issues in urban areas. World- wide, many metropolitan areas (e.g., New York, Chicago, Los Angeles, London, Milan, Paris, Bangkok, Jakarta, and Tokyo) suffer seriously from the social and environmental problems resulting from congestion. Broadly speaking, three main types of externalities arise from congestion: (1) negative economic effects caused by the restrictions that congestion imposes on the economic activity of a region, (2) social problems related to the limited mobility of individuals and (3) negative con- sequences for the natural environment and the health of the population (Emmerink and Nijkamp, 1999). In most cases, these negative externalities do not outweigh the economic opportunity and comfort offered by these metropolitan areas. In fact, many cities suffering from congestion are also among the most vibrant economic and cultural centers in the world. Nevertheless, experience also shows that cities cannot afford to leave these problems untreated for long because conges- tion problems can significantly reduce the quality of life of their residents and the cities’ capacity to attract new people and new capital. Addressing congestion is of notable strategic importance for metropolitan areas and a primary concern for travelers, transportation agencies, and transportation companies. Various agencies have estimated the monetary costs of these externalities. For example, the European UNITE project esti- mated the costs of traffic congestion in the United Kingdom to be $23.7 billion/year or 1.5% of GDP (Nash et al., 2003). For France and Germany the estimates were 1.3% and 0.9% of GDP, respectively. In the United States, the TTI estimates that in 2007 congestion caused an estimated 4.2 billion hours of travel delay and 2.8 billion gallons of extra fuel consump- tion with a total cost of $87 billion, amounting to 0.6% of GDP (Schrank and Lomax, 2009). In fact, the average annual cost per traveler in urban areas averaged $757 (de Palma and Lindsey, 2011). Even more alarming than the magnitude of these costs is the fact that the congestion costs seem to grow at a rate faster than GDP (Emmerink and Nijkamp, 1999). Transportation agencies can use several tools to improve traffic flows and reduce congestion. The traditional approach has been to increase the capacity of the transportation net- work by building new roads. However, this approach has become more difficult and costly during recent times for various reasons. First, the costs of expanding the existing road infrastructure may be too high if all aspects are taken into account; for example, the social and environmental costs of expanding road infrastructure. This has made it more dif- ficult for new infrastructure projects to secure resources and public support for their construction. In urban areas with a high population density it can be physically impossible to enlarge the current road infrastructure. As a result, expansion of freeways or the construction of new roads is often consid- ered to be infeasible and highly disruptive. Experience has also shown that most short-term benefits in reducing congestion from building more roads have a limited effect in urban areas because of latent transportation demand. Often, new infra- structure becomes as congested as the old just a few years after being built (Emmerink and Nijkamp, 1999). The complications and limitations of this traditional approach have encouraged transportation agencies to explore new ideas that can increase the efficiency of the transporta- tion networks they manage. In this regard, a set of new policy ideas has been developed which can help agencies in this mat- ter. These have evolved from a traditional command and con- trol planning paradigm used by transportation agencies into a more dynamic and interactive concept of transportation infrastructure that seeks to exploit and integrate the capabi- lities of the road infrastructure, vehicles, and motorists. These new ideas and concepts invite transportation agencies to reconsider their role in managing transportation networks and also suggest new capabilities of transportation agencies to mitigate the adverse effects of massive private mobility in metropolitan areas. New congestion policies can be clustered into three main categories: 1. Policies focusing on expanding the effective capacity of existing road infrastructure. These include ramp meter- ing, the introduction of reversible and pooling lanes, and other more progressive ideas like new automobiles that can use highway space more efficiently by driving faster and closer to each other; 2. Policies that seek to reduce the demand for private mobil- ity by making it less attractive. This includes congestion pricing to decrease the attractiveness of automobiles as well as other measures (e.g., subsidizing public transpor- tation) that can encourage motorists to adopt other modes of transportation; 3. Approaches that aim at providing motorists with infor- mation to use the road infrastructure more efficiently. This consists of using driver information systems to assist motorists in planning travel routes more efficiently and to adapt quickly and more effectively to the changing condi- tions of traffic in highways (Bovy and Van Der Zijpp, 1999).

73 Driver information systems have the potential for reduc- ing congestion, smoothing traffic flows, and increasing the efficiency of transportation infrastructure. Providing motor- ists with better and more information about traffic condi- tions may decrease travel times because motorists can use this information to make better decisions about whether, when, and where to travel. Offering motorists more information may also reduce driving stress and anxiety, increase safety, and diminish environmental pollution (Shladover, 1993). How- ever, driver information systems pose serious challenges for transportation agencies. The net benefits of driver informa- tion systems are far from clear or easy to determine. The pro- vision of travel information to motorists may have adverse effects that could offset its benefits (i.e., information satu- ration, congestion transfer from one place to another, and incentives to drive more) (Kitamura et al., 1999). Multi-actor Context of Driver Information Systems The possibility of using driver information systems encour- ages transportation agencies to reconsider their role in provid- ing traffic information to motorists and to explore new ways by which they can better manage traffic flows. Traditionally, transportation agencies have not been very active in devel- oping driver information systems. In the past, most of these functions were carried out by private parties and traditionally the scope of using driver information systems for traffic man- agement was quite narrow. The new possibilities in which driver information systems can be integrated with transportation infrastructure can change substantially how transportation agencies perform these func- tions and help them reach important milestones in improv- ing mobility and enhancing safety and sustainability in the transportation networks they manage. The development and implementation of driver informa- tion systems requires the efforts and resources of several parties. Transportation agencies need to consider this carefully when analyzing how they can enhance development of these systems. In this context, the role of private information providers, as well as the role of automakers is essential. For example, the dissemination of traffic information in mobile devices (e.g., PDAs, mobile devices) is being done using the infrastructure of major telecommunication companies in the country in col- laboration with companies that offer dedicated applications to process and transform traffic data into information that can be used by motorists. Many of these systems are already commer- cial and available to motorists today. In addition, automakers are at the forefront of the development of technologies that can integrate vehicles with the road infrastructure and with radio and wireless networks; developments in this area can also change significantly the way motorists receive information (Kitamura et al., 1999). It is clear that in this particular context, transportation agencies do not have all the resources needed to advance the development of driver information systems. On the contrary, if they choose to get involved in developing these systems, they will be expected to work along private parties in creating synergies that can enable driver information systems in wider geographical areas. Institutional Efforts to Improve Traffic Conditions Several projects in developed countries have been imple- mented to study how it might be possible to reduce conges- tion using new innovative approaches. The European Union is running several programs in this field, among them: Dedicated Road Infrastructure for Vehicle Safety in Europe (DRIVE) and Intelligent Vehicle Highways Systems (IVHS). The same is occurring in the United States with the Intelligent Transportation Systems (ITS) program and in Japan with the Comprehensive Automobile Control System (CACS) and Vehicle Road and Traffic Intelligence Society (VERTIS) pro- grams. (Gordon et al., 2008) These large institutional efforts are a clear indication of the relevance for transportation agencies of using driver infor- mation systems for mitigating congestion problems. The STREAM analysis that follows illustrates the method itself and is intended to help transportation agencies gain a strate- gic perspective on their roles in furthering their goals through enhanced traffic information systems. Identify Several technologies could change transportation agencies’ ability to provide traffic and safety information services to motorists. The characteristics of these technologies vary pri- marily according to three features: 1. The moment at which motorists receive the information: – Pre-trip; – En route; 2. The type of communication enabled: – One-way communication; – Two-way communication (vehicle-to-vehicle, vehicle- to-infrastructure); 3. The type of transmitted information: – Descriptive information; and – Predictive information. In addition to these features, technologies also vary in terms of maturity. In this respect, the integration of information technologies with vehicles and the road infrastructure is the main force driving new technological developments in driver

74 information systems. Some of the concepts using IT technolo- gies in driver information systems are already commercial applications; other are experimental concepts or state-of-the- art concepts (Watling, 1999). The great differences in relative maturities of potential applications and the rapidity of change create a climate of uncertainty that make these decisions fraught for transportation agencies. The research team found that new developments in infor- mation technologies have increased the versatility of the tech- nology bundles used in driver information systems. This is important for transportation agencies because these novel technology applications can serve multiple goals in terms of mobility, sustainability, and safety. Portfolio of Technologies An ample array of technologies can be used to provide motorists with traffic information. Table C-1 lists some of the relevant technology bundles used in driver information services and notes whether there is evidence of use in each case. In the following sections, the research team describes in more detail these technologies, paying special attention to those aspects that may affect transportation agencies’ functions while discussing the different features of these technologies. Table C-1 shows various technology applications that can be used to help driver information systems meet multiple goals. Traditionally, driver information systems have been designed to serve a single purpose. For example, traditional road signs were designed to increase road safety. They inform motor- ists about speed limits and possible threats in the road to help agencies achieve safety goals. However, new technology bun- dles, such as dynamic message signs can help transportation agencies meeting several goals at once. For instance, in addition to providing safety information to motorists, dynamic message signs can also inform motorists about the traffic conditions in the transportation network and advise them to take alternative routes to avoid congestion which helps transportation agencies to meet their mobility goals. Discussion of how the technology bundles listed in Table C-1 and mapped in Figure C-1 can improve or change the way transportation agencies provide traffic and safety informa- tion services to motorists are discussed in this section. The different features of these technology applications guide this discussion. The Timing of Information Motorists can receive safety and traffic information before or during the journey. In each case, various technology appli- cations can be used to improve the quality and usefulness of the information they receive. This is expected to enable motorists to make better decisions when planning their jour- neys or when adapting to unexpected events and adverse conditions in the road. This is important for transporta- tion agencies because this information helps motorists avoid congestion by planning their journeys ahead or reducing the risks of driving by avoiding dangerous conditions in the road (e.g., unsafe weather conditions). In addition, having a more adaptive type of driver is also of interest for transportation agencies: if motorists can be given information that can help them react in more efficient and safe ways to the changing conditions of the road, this can increase the efficiency of the overall transportation network. Television broadcast traffic pages and kiosks are technol- ogy bundles that enable motorists to access traffic information before they start their journeys. In the case of television broad- cast traffic pages, motorists receive reports describing traffic conditions in main roads, possible traffic incidents (e.g., block- ages or crashes), and the weather conditions. Motorists use this information to choose a particular route to their destina- tion or by delaying their departure time. In general terms, the information provided by television broadcast traffic pages is highly qualitative and selective because drivers do not receive information in the form of metrics, but rather in the form of images and opinions of reporters. Also, drivers are given traffic information describing only a set of the roads in the transportation network, thus missing a more comprehensive description of the whole transportation network. As a result, drivers cannot tailor the information they receive to meet their specific needs (i.e., the specific roads they frequently use or alternative routes). Kiosks are different because, depend- ing on level of sophistication, they can provide drivers with both descriptive and predictive information about their jour- neys. Actual formats vary, but the most sophisticated kiosks allow users to estimate their travel times and choose optimal routes. The number of motorists in a transportation system who benefit from kiosks depends on the number of existing kiosks and their locations. Motorists can also receive traffic and safety information during their travel. Perhaps, in this area, the most relevant technology bundle used by transportation agencies is the 511 telephone information systems. The capabilities of this type of system also vary greatly. Such 511 systems range from sim- ple telephone line systems in which drivers dial in to receive traffic information and advice during their travel, to more complex systems which combine telephone lines and inter- net traffic pages for traffic and safety information services. The most sophisticated 511 systems allow motorists to access detailed information of the state of the transportation net- work before they start their journey. The types of informa- tion they can access include incident and weather reports, traffic levels in different routes, estimated travel times, and access to video cameras in highways. In addition, these systems

75 (continued on next page) Table C-1. Available technologies for driver information systems. fo epyTesU fo ecnedivE ygolonhceT Communication Type of Information Pre-trip Television broadcast traffic pages Nationwide, Private Media One-way Descriptive Internet traffic pages Nationwide: Private (Google Maps) and Public (http://www.511ny.org/mapview.aspx), http://www.itsbenefits.its.dot.gov/ITS/be necost.nsf/ID/4B306AA1F6C2347C852 56A6100607098?OpenDocument&Quer y=BApp One-way Descriptive/Predictive Kiosks Los Angeles Smart Traveller Project, http://www.itsbenefits.its.dot.gov/its/ben ecost.nsf/BenefitTerminators/TI+Kiosks One-way Descriptive En route Telephone information systems (e.g., 511) Nationwide, Federal Communications Commission (FCC), www.fhwa.dot.gov/trafficinfo/511.htm One-way Descriptive/Predictive Highway Advisory Radio Several Cities, FCC, (e.g., Sacramento, Los Angeles, New York, Baltimore) One-way Descriptive Traffic Message Radio Channel Several Cities (e.g., Total Traffic Network, http://totaltraffic.com/, The HD Digital Radio Alliance, http://www.hdradioalliance.com/) One-way Descriptive Adaptive Signal Control Technology Several States: California, New York, Florida, Texas, Oregon http://www.fhwa.dot.gov/everydaycount s/technology/adsc/casestudies.cfm Two-way (V2I) Descriptive Dynamic Message Signs Several States, including New York, California and Washington, http://ops.fhwa.dot.gov/travelinfo/dms/in dex.htm One-way/ Two- way (V2I) Descriptive Portable Dynamic Message Signs (e.g., Automated Work Zone Information System) Grand Canyon National Park, California, North Carolina, Los Angeles, Detroit, http://www.itsbenefits.its.dot.gov/its/ben ecost.nsf/BenefitTerminators/ROM+Port able+DMS One-way Predictive Collision avoidance (V2V) Experimental, US, Germany, Netherlands, http://www.itsbenefits.its.dot.gov/its/ben ecost.nsf/BenefitTerminators/CAS Two-way (V2V) Predictive Cooperative Adaptive Cruise Control (V2V) Southern California, http://www.itsbenefits.its.dot.gov/ITS/be necost.nsf/ID/D614703F777341988525 78B80066CFCA?OpenDocument&Quer y=BApp Two-way (V2V) Predictive In-vehicle navigation systems with GPS Predictive/evitpircseD yaw-enO ediwnoitaN Lane departure warning systems Alaska, http://ntl.bts.gov/lib/jpodocs/repts_te/14 370_files/14370.pdf Two-way (V2I) Predictive Intelligent Speed Control Los Angeles, California, http://www.itsbenefits.its.dot.gov/ITS/be necost.nsf/ID/AA5443936A6D3A2C852 577840049 Two-way (V2I) Predictive Virtual Traffic Guidance System Europe, project: AKTIV-VM, http://www.aktiv- online.org/english/aktiv-vm.html Two-way (V2I) Predictive 0709?OpenDocument&Query=BApp

76 Sustainability Safety Mobility Television broadcast traffic pages Internet traffic pages Kiosks Telephone information systems Highway Advisory Radio Traffic Message Radio Channel Adaptive Signal Control Technology Dynamic Message Signs Portable Dynamic Message Signs • Collision avoidance (V2V) • Cooperative Adaptive Cruise Control (V2V) In-vehicle navigation systems with GPS • Lane departure Warning Systems Intelligent Speed Control • In-vehicle vision enhancement (V2I) Automatic Vehicle Location Systems Figure C-1. Functional mapping of driver information system. Table C-1. (Continued). In-vehicle vision enhancement (V2I) Experimental, Europe, COOPERS, http://publications.lib.chalmers.se/recor ds/fulltext/137657.pdf http://www.coopers-ip.eu/ Experimental, Erie County, New York, http://www.itsbenefits.its.dot.gov/ITS/be necost.nsf/ID/7A0A47F40911538E8525 6CB40057579D?OpenDocument&Quer y=BApp Two-way (V2I) Predictive AVL Systems (Communication with Dispatch) Experimental, Rochester, Pennsylvania; King County, Washington; Portland, Oregon; Columbus, Ohio, http://www.itsbenefits.its.dot.gov/ITS/be necost.nsf/ID/64D2E4A615027E288525 7632004A5E0E?OpenDocument&Quer y=BApp Two-way (V2I) Predictive fo epyTesU fo ecnedivE ygolonhceT Communication Type of Information

77 provide motorists with traffic and safety reports, as well as route selection advice while driving by calling the 511 num- ber. The versatility of 511 systems permits motorists to tailor this vast information to meet their specific needs and develop personal heuristics that can help them in optimizing their use of the transportation network (e.g., choosing less congested routes, better scheduling their journey). Nevertheless, these systems are complex because they need to integrate differ- ent technology and information systems and because they require substantive investments in the necessary technologies for collecting and processing the information in the roads (Gordon et al., 2008). Type of Communication Whether driver information systems are intended to enable one-way or two-way communications is crucial for under- standing the potential role of transportation agencies in the deployment of driver information systems. Traditionally, transportation agencies have been involved in one-way communication. Transportation agencies collect and process the data they want to transmit to motorists and make it available through one or more of their communication chan- nels (i.e., road signs, internet traffic pages, telephone systems, highway advisory radio). Agencies expect motorists to access the information and use it to assist them in their travel deci- sions. Under this approach, transportation agencies are usually heavily involved in collecting, processing, and disseminating traffic and safety data. Private parties are more involved in the dissemination process as in the case of private internet traf- fic pages and the commercialization of mobile applications for driver assistance (Geisler, 2012). Recent technology developments have enabled two-way communications between the road infrastructure, vehicles, and motorists. These new systems permit different parties to communicate with each other for collecting and transmitting traffic and safety information. This is most evident in coop- erative adaptive cruise control systems, which use vehicle- to-vehicle communication technologies, and in the case of in-vehicle vision enhancement systems which use vehicle-to- infrastructure technologies. Cooperative adaptive cruise con- trol systems allow vehicles to share information about road conditions, such as collisions, speed limits, and recommended distance between vehicles. In this case, vehicles communi- cate with each other using a wireless network or hot spots in the road. These information nodes collect and monitor data being transmitted by sensors in cars (floating car data); this information is then processed and transmitted to motorists using specialized driver assistance software in vehicles (Delot and Ilarri, 2012). In-vehicle vision enhancement systems fol- low a similar logic, but, in this case, floating car data is not exchanged directly with vehicles. Rather, it is first transmitted to traffic management centers for processing and then sent to vehicles using road hot spots or other alternative wireless net- works in highways. In this way, traffic management centers can send information to motorists about current or expected traffic road conditions. Both systems are technically complex because they need to process and analyze huge amounts of data in real time (Delot and Ilarri, 2012). The role of transportation agencies in the deployment and management of one-way and two-way communication systems varies. In the first case, transportation agencies take part in several of the processes needed for this type of driver information system and in the construction and operation of the IT architecture needed for collecting, processing, and transmitting traffic and safety information to motorists. In the second case, the role of transportation agencies changes significantly. For example, in cooperative adaptive cruise con- trol systems, transportation agencies do not need to invest in expanding the capabilities of their traffic management centers because in-vehicle software systems can be used for this pur- pose. Moreover, in schemes in which vehicles can exchange information without the support of road hot spots or other third-party networks, transportation agencies would not need to invest in deploying some components of the IT architecture needed for two-way communication systems (Geisler, 2012). This can change substantially the engagement of transporta- tion agencies in the deployment of modern driver information systems. Depending on the actual system architecture, their role could change from developer and administrator of driver information system to regulator of driver information systems and coordinator of the main stakeholders involved in their deployment (i.e., automakers, telecommunication companies, and traffic information companies). Thus if transportation agencies want to get actively involved in the wide deploy- ment and adoption of modern driver information systems, they will need to consider new ways in which they can create synergies with these other actors. Type of Transmitted Information The type of information transmitted to motorists by dif- ferent types of driver information systems is also a key fea- ture that can affect both transportation agencies’ assessment of their own functions and their realization of their own mobility, safety, and sustainability goals. Driver information systems can provide information that is descriptive or predictive (or both). The first group includes technology bundles that provide drivers with a static descrip- tion of the traffic and safety conditions of the transportation network. Examples include internet traffic pages, highway advi- sory radio, and dynamic road signs. At their simplest, such sys- tems provide drivers with road descriptions such as the location of congested roads, average delays due to accidents or repair

78 work, expected weather conditions, current speed limits, and so forth. Motorists receive and process this information on their own and decide how best to use it. Predictive information content integrates the current, empirical data with historical databases and proprietary algo- rithms to yield additional information. Motorists receive infor- mation that assesses how their travel plans and their journeys will be affected by the changing traffic conditions (Toledo and Beinhaker, 2006). In-vehicle navigation systems with GPS are a widespread application that informs motorists about the expected travel time of their journeys and also allows them to choose routes that can be faster or less busy at peak hours. Moreover, in-vehicle navigation systems can help drivers adjust their routes in real time and navigate in unfamiliar regions. Collision avoidance systems are another example of predictive information, but such systems are not yet widely used. Collision avoidance systems consist of vehicle sensors and processing software that inform drivers about risks that can lie ahead in the road. This can help them take preventive maneuvers to avoid a collision of their own and reduce the risks of their journeys (Toledo and Beinhaker, 2006). Maturity of Technologies Driver information systems are among those transporta- tion technologies that have changed significantly owing to new technological trends in information, communications, and sensor technologies. Those systems that provide pre-trip and descriptive information and enable one-way communication are the most mature technology applications. In contrast, tech- nologies that enable two-way communications and provide en route and predictive information are among the technologies that are either still pilot concepts or state-of-the-art applica- tions. This is especially true for vehicle-to-vehicle and vehicle- to-infrastructure technologies. Moreover, the development of new driver information systems is an area that registers one of the highest levels of innovative activity in the transportation sector, thus increasing at an ever greater pace the ideas and con- cepts under development. Therefore, the list of technologies discussed in this chapter should not be viewed as exhaustive (Fan, Khattak and Shay, 2007). The main large firms and OEMs participating in the research and development of novel driver information sys- tems include Siemens, Honda, Toyota, Bosch, Mitsubishi, and Nissan. Worldwide, the main countries engaging in the research and development of driver information systems are the United States, Germany, and Japan. Patent analysis shows that there is no dominant firm or country in the sec- tor which is also an indication that there is strong compe- tition in this technological field. In addition, there is not yet a dominant technology application, which means that developing different technology platforms for novel driver information systems is still in a phase of experimentation (Wu and Lee, 2007). Characterize The technologies described in the Identify step will be char- acterized in this section. The research team will first provide a quantitative and qualitative description of these technologies focusing on a set of specific characteristics that are the most relevant for transportation agencies. These are as follows: • Technology’s effect on transportation agencies’ goals (i.e., mobility, safety, and sustainability); • Transportation Agency’s Role in Adoption Process; • Technology Adoption Barriers; and • Technology Costs. The research team first discusses the comparative factors used. The research team then discusses the individual driver information system considered in the STREAM analysis. The research team concludes the Characterize step with a sum- mary table of the qualitative and quantitative descriptions of these technologies. Overview of Characterizing Factors Metrics For each technology application discussed in this section, the research team will use a qualitative scale to assess its poten- tial influence on three agency goals: mobility, safety, and sus- tainability. In this case study, the research team has primarily focused on both systems and outcomes at the level of the met- ropolitan region, rather than on a statewide basis. For the pur- poses of this illustration of the STREAM method, the research team provides a qualitative scale for each in which the research team aggregates several types of indicators into one measure. Full implementation of STREAM for such a complex subject would involve drawing on a range of quantitative and qualita- tive information sources as well as overall characterizations provided by experts familiar with different aspects of driver information system technologies. Mobility • Low impact. The technology has the potential of slightly (0–5%) reducing motorists’ average travel time, of increas- ing motorists’ average traveling speed, and of increasing the efficiency of the transportation network. The technology provides motorists with pre-trip or en route descriptive traffic information for assisting them in planning their trips or for finding alternative routes when they are in traffic; • Medium impact. The technology has the potential of further reducing motorists’ average travel time (5–15%), of increas-

79 ing motorists’ average traveling speed, and of increasing the capacity of the transportation network. The technol- ogy provides motorists with pre-trip and en route descrip- tive traffic information for assisting them in planning their trips and in adapting to changing road conditions, which expands motorists’ options to use traffic information dur- ing their trips; • High impact. The technology has the potential of signif- icantly reducing motorists’ average travel time (>15%), of increasing motorists’ average traveling speed, and of increasing the capacity of the transportation network. The technology provides motorists with pre-trip and en route descriptive and predictive traffic information for assisting them in planning their trips and adapting in real time to changing conditions (i.e., real-time optimal route selection). Safety • Low impact. The technology has the potential of slightly reducing (0–5%) the propensity for highway accidents, the severity of accidents, and the average number of vehicles per collision. The technology transmits descriptive pre-trip or en route safety information to motorists; this informa- tion is used for avoiding possible road threats and known vehicle collisions in the transportation network. • Medium impact. The technology has the potential of further reducing (5–10%) the propensity for highway accidents, the severity of accidents, and the average number of vehicles per collision. The technology transmits descriptive pre-trip and en route safety information to motorists; this information is used to avoid and safely respond to possible road threats and known vehicle collisions in the transportation network. • High impact. The technology has the potential of signi f- icantly reducing (>15%) propensity for highway accidents, the severity of accidents, and the average number of vehicles per collision. The technology transmits descriptive and pre- dictive pre-trip and en route safety information to motor- ists; this information is used to avoid and safely respond to possible road threats and known and/or unexpected vehicle collisions in the transportation network. Sustainability • Low impact. The technology allows motorists to reduce the time that they spend in congested roads, but does not necessarily reduce their vehicle driven miles. This may result in a slight reduction in GHG emissions per motorist. • Medium impact. The technology allows motorists to reduce their average vehicle driven miles and to increase their average travel speed. This results in a reduction in GHG emissions per motorist. • High impact. The technology allows motorists to reduce their average driven miles and to increase their average travel speed considerably. This results in a significant reduction in GHG emissions per motorist. Transportation Agencies’ Role The role that transportation agencies play in the deploy- ment of driver information systems is largely defined by the processes in which agencies are significantly involved. As a result, for any given technology application, trans portation agencies can play one or more of the following roles: • Data Collection. Transportation agencies are significantly involved in construction and operation of the IT architecture and infrastructure needed for collecting traffic and safety information of the transportation networks they operate. • Data Management and Processing. Transportation agen- cies are significantly involved in managing traffic and safety data and in processing this data into information that can be made available to motorists who use the transportation networks they operate. • Data Dissemination. Transportation agencies are signifi- cantly involved in disseminating traffic and safety informa- tion among motorists who use the transportation networks they operate. Technology Barriers Transportation agencies wanting to implement the tech- nologies described in this chapter may face one or more of the following barriers to successful implementation in the transportation networks they operate: • Technology – Unfamiliarity with core or applied technology – Uncertainty concerning actual performance – Additional implementation requirements (training, stan- dards, etc.) • Agency Process or Institutions – Need for new or conflict with existing regulations and standards – Non-fungibility of funding for required expenditures – Extended or problematic approval processes • External to Agency – Inertia of existing processes and methods – Insufficient political or public acceptance – Lacking precedence of necessary vendor or support base Estimation of Costs The US DOT has developed a costs database of different emerging technologies in the transportation sector. This includes new driver information systems. This database con- tains the costs concepts of different technology deployments. The costs to be incurred in each project are separated accord- ing to different component subsystems; each subsystem con- tains the costs of individual technology units or technology

80 bundles needed for the deployment of new transportation technologies: Roadside Telecommunications (RS-TC), Roadside Detection (RS-D), Roadside Control (RS-C), Roadside Information (RS-I), Roadside Rail Crossing (R-RC), Parking Management (PM), Toll Plaza (TP), Remote Location (RM), Emergency Response Center (ER), Emergency Vehicle On-Board (EV), Information Service Provider (ISP), Transportation Management Center (TM), Transit Management Center (TR), Toll Administration (TA), Transit Vehicle On-Board (TV), Commercial Vehicle Electronic Credentialing (EC)/Administration, Commercial Vehicle Safety Information Exchange (SIE), Commercial Vehicle Electronic Screening (ES) (Preclearance), Commercial Vehicle On-Board (CV), Fleet Management Center (FM), Vehicle On- Board (VS) and Personal Devices (PD) (U.S.Department.of. Transportation, 2012). For each technology application, the interested analyst can select the cost concepts under each of the subsystems employed in the deployment of a particular technology. For example, the implementation of dynamic message signs includes cost concepts for subsystems under Roadside Detec- tion (RS-D), Transportation Management Center (TM), and Roadside Telecommunications (RS-TC). Although this data- base can be a very useful guide for estimating the costs of each technology application, a detailed cost estimation for each technology was out of the scope of this case study, so the cost estimation has been simplified by assuming that, for each tech nology option, the transportation agency would already have the needed equipment for collecting traffic infor- mation and transmitting this information through its infor- mation network (Roadside Telecommunications (RS-TC)) (Gordon et al., 2008). Thus, the research team will only focus on the expenses needed to upgrade such a system and in the equipment needed to disseminate traffic information to motorists. In all cases the research team assessed what the research team estimated the costs would be for deploying a system within a metropolitan region. Characterization of Technologies Internet Traffic Pages Impacts. Internet traffic pages provide both descrip- tive and predictive traffic information to drivers. The most advanced systems provide motorists with optimal routes, traf- fic conditions, and travel times. This is a popular system among motorists because it is easily accessible and low cost. Modeling results indicate that individual travelers who use internet traf- fic pages prior to traveling would receive annual benefits of a 5.4 percent reduction in delay, a 0.5 percent reduction in crash rate, and a 1.8 percent reduction in fuel consumption (Carter et al., 2000). Based on this information, the research team esti- mates that internet traffic pages provide a medium mobility impact and low safety and sustainability impacts on transpor- tation agencies’ goals. Barriers. Internet traffic pages are already mature and in recent years there has been a constant increase in the number of internet traffic pages supported by transportation agencies or by private vendors (Gordon et al., 2008). Nevertheless, the successful implementation of internet traffic pages requires highly complex integration with other technologies (e.g., video cameras, metering devices) and other information sys- tems. This may require additional training of transportation agencies’ staff or developing new protocols or standards. In addition, motorists are often not familiar with the all the pos- sible applications of internet traffic pages. Costs & Agencies’ Role. The cost estimations presented in this chapter assume that transportation agencies have already deployed the IT infrastructure needed in roadways for the implementation of the driver information systems mentioned in this chapter. Therefore, in the following sec- tions the research team will not consider costs incurred in Roadside Telecommunications (RS-TC), Roadside Control (RS-C), and Roadside Information (RS-I). Further work would require relaxing this assumption for estimating more accurately the costs of each driver information system. In this case, the role of transportation agencies wanting to support the deployment of internet traffic pages may engage them in processes of data collection, data management and processing, and data dissemination. Table C-2 shows an esti- mate of which share of the technology implementation costs would need to be incurred by both motorists and the trans- portation agency and which share would need to be incurred only by the transportation agency. Kiosks Impacts. Traveler information kiosks provide descriptive and predictive information to drivers before they start their journeys. Depending on the level of sophistication of these systems, kiosks inform drivers about the current traffic and safety road conditions. Motorists can only access this infor- mation in person and not remotely, reducing the potential number of motorists that can use these systems. Experience shows that users of kiosks are satisfied with the information services provided by these systems (Giuliano, 1995). Neverthe- less, the research team estimates that, given the limited number of motorists that can use these systems, kiosks are expected to have a low mobility, safety, and sustainability impact in the transportation networks in which these are deployed. Several pilot programs have deployed kiosks to assist motorists in the United States in 11 metropolitan areas; however, in recent years the rate of growth of kiosk projects has stagnated (Gordon et al., 2008).

81 Barriers. The main limitations faced by traffic informa- tion kiosks include unfamiliarity with the technology among motorists as well as the lack of necessary vendor or support base. It is also not at all straightforward to demonstrate the effect of this technology in the transportation network. It seems that while there is sufficient public support for kiosks, the performance of the technology in terms of enhancing mobility is uncertain (Gordon et al., 2008). Costs & Agencies’ Role. Support for deploying kiosks may engage agencies in processes of data collection, data man- agement and processing, and data dissemination. Table C-3 shows an estimate of which share of the technology imple- mentation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. Telephone Information Systems Impacts. The sophistication and capabilities of tele- phone information systems vary widely. 511 telephone sys- tems range from systems that only provide pre-trip and en route traffic and safety information through telephone lines to those that integrate telephone, video, and internet capa- bilities into 511 driver information systems. The difference in overall impact between the most and least sophisticated 511 systems can be quite significant. Thus, based on the qualita- tive scale previously defined, the research team estimates that traditional telephone information services have a medium mobility impact and low safety and sustainability impacts. In contrast, the research team considers that advanced 511 telephone information services have high mobility impact and medium safety and sustainability impacts. 511 telephone information systems are becoming more popular. In 2008 these were used by 64 transportation agencies in the United States (Gordon et al., 2008). Barriers. 511 telephone systems are already well estab- lished. However, the more recent integration of this system with other technologies, other information architectures, and other communication channels (i.e., the internet) has considerably increased the complexity of this technology, demanding further training within transportation agencies. In addition, the increasing popularity of other driver infor- mation systems has increased the competition between 511 systems and other dominant technologies. Costs & Agencies’ Role. As shown in Figure C-2, the costs of 511 systems vary according to size and level of sophis- tication. For example, statewide systems’ costs range from $1M to $5.2M, while metropolitan 511 systems range from $1.5M to $2.3M. Given that the focus of the case study is on metropolitan areas, the research team estimates that tradi- tional 511 telephone information systems’ costs range from $1.5M to $1.8M, while integrated 511 telephone informa- tion systems’ costs range from $1.8M to $2.3M (U.S.DOT, 2012). In this case, transportation agencies would need to be engaged in data collection, data managing and processing, and data dissemination. Highway Advisory Radio Impacts. Highway advisory radio uses low-power per- manent or portable radio stations to broadcast descriptive en route traffic and safety information to motorists. The infor- mation enables motorists to adjust their trips according to Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) ISP ISP Hardware 18.3 27.09 ISP Software 287.15 574.30 Map Database Software 10.45 29.27 Systems Integration 88.09 107.67 Transportation Management Center (TM) Hardware for Traffic Information Dissemination 2.09 2.79 Software for Traffic Information Dissemination 18.80 22.97 Integration for Traffic Information Dissemination 89.15 108.96 Total Cost 514.03 873.05 of which, Agencies’ Cost 514.03 873.05 Source: U.S.DOT, 201272 Table C-2. Cost estimates for deploying internet traffic pages. 72 The U.S. DOT Costs Database contains estimates of ITS costs that can be used for preliminary project cost estimates. The cost concepts presented in this table are the costs associated with an individual ITS element or subsystem for a particular ITS deployment. These cost estimates consider capital costs and annual operations and maintenance costs, adjusted to the year 2009 using indexes maintained by the Bureau of Labor Statistics. The titles in bold letters indicate the Costs Database section used for the estimation.

82 changing road, weather, and congestion conditions. Motor- ists that use highway advisory radio have a positive opinion of the technology. In Spokane, Washington, about one third of interviewed motorists estimated that they would consider changing routes based on the information provided in high- way advisory radio systems; however, few drivers were able to identify feasible alternative routes (Gordon et al., 2008). This is an important limitation of driver information systems that provide en route information. In many cases, the oppor- tunity to change routes has passed by the time motorists receive traffic information through highway advisory radio. Thus, considering that the information transmitted through highway advisory radio would be useful only for a fraction of drivers, the research team considers that the mobility and sustainability impact of this technology is low. How- ever, given that highway advisory radio provides en route information that can avoid greater collision incidents, the research team estimates that this technology has a medium safety impact on the transportation network. Barriers, Highway advisory radio is a well-established technology. Perhaps the only barriers it faces are those related to drivers being unfamiliar with the technology or the pres- ence of other strong information systems that can provide a similar service (e.g., 511 systems, GPS, internet traffic pages). Costs & Agencies’ Role. The role of transportation agen- cies wanting to support the deployment of highway advisory radio systems would include data collection, data manage- ment and processing, and data dissemination. In Table C-4 the research team estimates which share of the technology implementation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. Dynamic Message Signs Impacts. The most common media for disseminating en route information are dynamic message signs and highway Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Remote Location (RM) Informational Kiosk 10 24 Kiosk Upgrade for Interactive Usage 5 9 Kiosk Software Upgrade for Interactive Usage 10 12 Integration of Kiosk with Existing Systems 2 27 Number of units in a medium size regional transportation network: 20 kiosks 20 units 20 units Total Cost 540 1,440 of which, Agencies’ Cost 540 1,440 Source: U.S.DOT, 2012 Table C-3. Cost estimates for deploying traffic kiosks. Figure C-2. Cost of telephone information systems. Source: Gordon et al., 2008

83 advisory radio. Dynamic message signs are used to disseminate en route information on freeways and arterials in approxi- mately 86 metropolitan areas in the United States. The most common types of information transmitted through DMS are incident information, maintenance and construction infor- mation, congestion conditions and weather alerts, as well as travel time and public service announcements (Gordon, 2008). In comparison to highway advisory radio, dynamic message signs transmit traffic and safety information to a narrower set of motorists who receive relevant traffic and safety information of the conditions ahead of their jour- neys. Thus, the probability that a driver receives opportune information does not depend on whether or not drivers are listening to the radio before they can no longer adjust their journey. Empirical studies have shown that real-time travel traffic and safety information posted on DMS indeed influ- ences motorists’ route choice. In a survey study carried out in Houston, Texas, 85 percent of respondents indicated that they changed their route based on the information provided by DMS. Among these respondents, 66 percent said that they saved travel time as a result of the route change (Fink, 2005). Thus, the research team estimates that DMS have a medium mobility and safety impact and a low sustainability impact. Barriers. Among the barriers that this technology faces are the uncertainty concerning its actual performance and the insufficient public acceptance of the technology. For example, even though motorists may support the implemen- tation of this technology, impacts of this technology may vary from region to region (Fink, 2005). Costs & Agencies’ Role. The role of transportation agen- cies wanting to support the deployment of dynamic message signs may engage them in data collection, data management and processing, and data dissemination. In Table C-5 the research team estimates which share of the technology imple- mentation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. dnuoB rewoL tpecnoC tsoC $K (2009 prices) Upper Bound $K (2009 prices) Roadside Informat )I-SR( noi 73 61 oidaR yrosivdA yawhgiH 60.8 55.4 sngiS oidaR yrosivdA yawhgiH Number of units in a medium size regional transportation network: 10 signs signsx10 signsx10 Transportation Management Center (TM) Software for Traffic Information Dissemination 18.80 22.77 Integration for Traffic Information Dissemination 89 109 73.285 3.314 tsoC latoT 73.285 3.314 tsoC ’seicnegA ,hcihw fo Source: U.S.DOT, 2012 Table C-4. Cost estimates for highway advisory radio. Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Roadside Information (RS-I) Dynamic Message Sign (10 units for regional system) 42.7 106.6 Dynamic Message Sign Tower (2 units for regional system) 28.5 136 Number of units in a medium size regional transportation network: 10 signs signsx10 signsx10 Number of sign towers in a medium size regional transportation network: 2 towers towersx2 towersx2 Transportation Management Center (TM) Software for Traffic Information Dissemination 19 23 Integration for Traffic Information Dissemination 89 109 Total Cost 592 1,470 of which, Agencies’ Cost 592 1,470 Source: U.S.DOT, 2012 Table C-5. Cost estimates for dynamic message signs.

84 Portable Dynamic Message Signs Impacts. There is an evident overlap between the capa- bilities of portable dynamic message signs and the more standard fixed dynamic message signs because they are used to disseminate the same sort of traffic and safety informa- tion. However, portable dynamic message signs are a more flexible technology that enables additional capabilities which can improve traffic and safety information services. A por- table dynamic message sign can be used to inform drivers about high congestion before they enter the road by moving the portable message sign to an intersection from which driv- ers can still opt for an alternative route. In addition, porta- ble dynamic message signs can be moved to locations where vehicle collisions have occurred or where maintenance work is being carried out (Gordon et al., 2008). However, it is dif- ficult to estimate whether portable dynamic message signs will have a significantly higher mobility and safety impact than traditional dynamic signs. However, the research team consider that expanding the options of drivers to avoid con- gested roads can increase the efficiency of the transportation network and result in a clear reduction of GHG emissions. Thus the research team estimates that portable dynamic mes- sage signs have medium mobility, safety, and sustainability impacts in the transportation network. Barriers. In addition to the existing barriers for dynamic message signs, it can be expected that portable dynamic mes- sage signs demand further requirements (e.g., training and the development of new operational protocols). Costs & Agencies’ Role. The role of transportation agen- cies wanting to support the deployment of portable dynamic message signs may engage them in data collection, data man- agement and processing, and data dissemination. In Table C-6 the research team estimates which share of the technology implementation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. Cooperative Adaptive Cruise Control (V2V) Impacts. Recent developments in mobile technologies have led to the emergence of vehicle-to-vehicle communi- cation networks that can be used for providing traffic and safety information to drivers. Using these communication networks, motorists can receive information from other trav- elers and disseminate relevant data to other vehicles within communication range. The information disseminated can be predictive or descriptive depending on the sophistication of the adaptive cruise control system being used (Delot and Ilarri, 2012). Cooperative adaptive cruise control systems can expand motorists’ adaptability to changing road conditions. Drivers (or, more properly, their vehicles) can react more rapidly to vehicle collisions, reducing the damage and impact ratio of this type of incident. Such systems can also increase the frequency at which drivers receive traffic information and increase their opportunities to adapt to changing traffic conditions. Recent studies have found that cooperative adap- tive cruise controls systems are most effective at improving safety when bundled with collision warning systems. In a sce- nario of widespread deployment, these systems also have the potential of reducing vehicle GHG emissions and increasing the effective capacity of roadways (Bose, 2001). Considering these elements, the research team estimates that this emerg- ing technology could have high safety impacts, medium mobility impacts, and medium sustainability impacts. Barriers. Cooperative adaptive cruise control systems are recent technologies and are still unfamiliar to motorists. This creates barriers for introduction related to motorists’ Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Roadside Information (RS-I) Dynamic Message Sign-Portable (10 units for regional system) 16.4 22.4 Dynamic Message Sign Tower (2 units for regional system) 28.5 136 Number of units in a medium size regional transportation network: 10 signs signsx10 signsx10 Number of sign towers in a medium size regional transportation network: 2 towers towersx2 towersx2 Transportation Management Center (TM) Software for Traffic Information Dissemination 19 23 Integration for Traffic Information Dissemination 89 109 Total Cost 329 628 of which, Agencies’ Cost 329 628 Source: U.S.DOT, 2012 Table C-6. Cost estimates for portable dynamic message signs.

85 unfamiliarity with the technology and the uncertainty about its performance to say nothing of their willingness to use such systems if available on their vehicles. Such systems also require modifications to automobiles by the manufacturers. This involves the familiar chicken-and-egg situation in which OEMs would need to be convinced of the business case for such systems. Costs & Agencies’ Role. Transportation agencies want- ing to support the deployment of cooperative adaptive cruise control technologies would only be engaged in data collec- tion to integrate this technology with their current systems. In Table C-7 the research team estimates which share of the technology implementation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. In-Vehicle Navigation Systems with GPS Impacts. The maturity of GPS technology and its inte- gration with the internet, mobile devices, and PDAs have made in-vehicle navigation systems widely available for motorists. In-vehicle navigation systems provide motorists with descrip- tive and predictive pre-trip and en route traffic information. This is a versatile type of driver information system, depending on its level of sophistication. Using traditional GPS, motor- ists can find optimal routes before and during their journey while more advanced GPS can recommended proper fol- lowing distance, appropriate speed limits, and receive infor- mation about vehicle collisions, weather conditions, and other possible concerns. Simulation studies estimate that in-vehicle navigation systems can improve fuel economy by 10 percent by selecting less congested routes and increase average travel speed. In addition, empirical studies estimate that wasted mileage and emissions can be reduced by 15 percent using in-vehicle navigation systems (Kamal, 2009). Another important feature of in-vehicle navigation systems is that they can be integrated with other driver information systems, such as 511 integrated telephone systems. This fur- ther expands the capabilities of these systems. Therefore, the research team considers that in-vehicle navigation systems can have high mobility and safety impacts and a medium sustainability impact in transportation networks. Barriers. In-vehicle GPS navigation systems are a popular technology that is going through changes and is finding new application niches. Nevertheless, as with many new-to-market technologies, GPS navigation systems face deployment barriers related to motorists’ unawareness of the capabilities of this tech- nology and uncertainty concerning actual system performance. Costs & Agencies’ Role. Transportation agencies want- ing to support the deployment of in-vehicle GPS navigation systems may become engaged in data collection to integrate this technology with their current systems. In Table C-8 the research team estimates which share of the technology implementation costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. In-Vehicle Vision Enhancement (V2I) Impacts. In-vehicle vision enhancement technologies provide en route traffic and safety information to motorists using vehicle-to-infrastructure communications. The IT architecture infrastructure in roadways collects traffic and safety information through various monitoring devices (e.g., cameras, sensors, and hot spots). This information Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Vehicle On-board Advanced Steering Control 0.3 0.4 Advanced Cruise Control 0.1 0.2 Sensors for Longitudinal Control 0.2 0.3 Communication Equipment 0.2 0.4 In-Vehicle Display 0.0 (included in vehicle) 0.1 In-Vehicle Signing System 0.1 0.3 Driver and Vehicle Safety Monitoring System 0.5 0.9 Number of private vehicles using this system in a regional transportation network: 100,000 vehicles vehiclesx100,000 vehiclesx100,000 Transportation Management Center (TM) Integration for Traffic Information Dissemination 89 109 Total Cost 140,089 260,109 of which, Agencies’ Costs 89 109 Source: U.S.DOT, 2012 Table C-7. Cost estimates for cooperative adaptive cruise control (v2v).

86 is then transmitted to motorists using vehicle data sensors or other wireless networks. Information that can be trans- mitted to drivers includes vehicle collision warnings, weather and congestion alerts, and other descriptive information to improve drivers’ visibility in conditions of reduced sight dis- tance, night driving, inadequate lighting, and snow and other unexpected weather conditions. As with other driver informa- tion systems, motorists can use this information to adapt to changing road conditions and to avoid dangerous situations. Empirical studies of similar technological concepts show that in-vehicle vision enhancement systems can be considerably effective in assisting drivers in unexpected weather conditions, increasing the safety of roadways (Kato, 2000). The research team considers that in-vehicle vision enhancement systems can have medium mobility and sustainability impacts and a high safety impact on transportation networks. Barriers. In addition still being a young technological concept, vision enhancement barriers include those related to the challenges that transportation agencies would need to face implementing this technology in the road (e.g., addi- tional infrastructure requirements and new regulations and standards to manage the communication interaction between vehicles with the transportation infrastructure). Costs & Agencies’ Role. Transportation agencies want- ing to support the deployment of in-vehicle vision enhance- ment technologies may become engaged in data collection and data managing and processing. In Table C-9 the research team estimates which share of the technology implementa- tion costs would need to be incurred by both motorists and the transportation agency and which share would need to be incurred only by the transportation agency. Summary Table C-10 summarizes the discussion of the Character- ize step. Compare In this phase of the analysis, the information provided in the characterization phase is used to compare the effects of each technology application on transportation agencies’ goals and Table C-8. Cost estimates for in-vehicle navigation systems with gps. Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Vehicle On-Board GPS/DGPS 0.1 0.1 GIS Software 0.1 0.2 Number of private vehicles using this system in a regional transportation network: 100,000 vehicles vehiclesx100,000 vehiclesx100,000 Hard to Quantify Integration for Traffic Information Dissemination 89 109 Total Cost 20,089 30,109 of which, Agencies’ Costs 89 109 Source: U.S.Department.of.Transportation, 2012 Table C-9. Cost estimates for in-vehicle vision enhancement (v2I). Cost Concept Lower Bound $K (2009 prices) Upper Bound $K (2009 prices) Vehicle On-board (VS) Vision Enhancement System 1.75 2.18 Communication Equipment 1.9 3.8 Software, Processor for Probe Vehicle 0.5 1.5 Number of private vehicles using this system in a regional transportation network: 100,000 vehicles vehiclesx100,000 vehiclesx100,000 Transportation Management Center (TM) Software for Traffic Information Dissemination 19 23 Hardware for Traffic Information Dissemination 2 2.79 Integration for Traffic Information Dissemination 89 109 Total Cost 415,110 748,134 of which, Agencies’ Costs 110 134 Source: U.S.DOT, 2012

87 (continued on next page) Table C-10. Characteristics of driver information systems. Characteristics Driver information system Impact Estimate Costs ($K) Transportation Agency Role Technology Barriers Mobility Safety Sustainability Internet traffic pages Low- Medium Low Low 514.03- 872.85 Data Collection, Data Management and Processing, Data Dissemination Insufficient public acceptance; Additional implementation requirements. Kiosks Low Low Low 540-1,440 Data Collection, Data Management and Processing, Data Dissemination Insufficient public acceptance; Uncertainty concerning actual performance; Lacking precedence of necessary vendor or support base. Telephone information systems Medium Low Low 1,500- 1,800 Data Collection, Data Management and Processing, Data Dissemination Inertia of existing processes and methods. Integrated telephone information systems High Medium Medium 1,800- 2,300 Data Collection, Data Management and Processing, Data Dissemination Inertia of existing processes and methods; Additional implementation requirements. Highway Advisory Radio Low Medium Low 413.3- 582.37 Data Collection, Data Management and Processing, Data Dissemination Inertia of existing processes and methods. Dynamic Message Signs Medium Medium Low 592-1,470 Data Collection, Data Management and Processing, Data Dissemination Uncertainty concerning actual performance; Insufficient public acceptance. Portable Dynamic Message Signs Medium -High Medium Medium 329-628 Data Collection, Data Management and Processing, Data Dissemination Uncertainty concerning actual performance; Insufficient public acceptance; Additional implementation requirements. Cooperative Adaptive Cruise Control (V2V) Medium High Medium 140,000- 260,000 Data Collection (partly) Unfamiliarity with core or applied technology; Insufficient political or public acceptance; Uncertainty concerning actual performance; Extended or problematic approval processes. In-vehicle navigation systems with GPS High Medium Medium 20, 089- 30,109 Data Collection Unfamiliarity with core or applied technology; Uncertainty concerning actual performance.

88 functions. The research team was interested in analyzing which tradeoffs exist between the different technologies in terms that bear on agency decisions. For this, the research team translated the Characterize metrics into a set of normative measures. The research team continued to assume that the implementation of these technologies was to be compared at the regional level. Therefore, even though some of the technology applications may have a wider geographical scope, the research team did not consider this so as to compare these technologies on an equiva- lent basis. As discussed in greater detail below, the research team considered the total system’s costs of implementing the technology, including costs incurred by the transportation agency and costs incurred by drivers (which is important from a societal and efficiency point of view). Finally, even though the research team provides a set of numerical comparative metrics in this section, the reader must consider the analysis to be essentially qualitative. The research team recommends that further STREAM analyses of this sphere of agency function relax this assumption and carry out more detailed costs and effects studies of these driver information systems in specific transportation networks. Metrics Mobility The research team used a qualitative scale to define the fol- lowing normative metric: • Metric value 1: The technology has a low mobility impact in the transportation network. • Metric value 2: The technology has a medium mobility impact in the transportation network. • Metric value 3: The technology has a high mobility impact in the transportation network. Safety The research team used a qualitative scale to define the fol- lowing normative metric: • Metric value 1: The technology has a low safety impact in the transportation network. • Metric value 2: The technology has a medium safety impact in the transportation network. • Metric value 3: The technology has a high safety impact in the transportation network. Sustainability The research team used a qualitative scale to define the fol- lowing normative metric: • Metric value 1: The technology has a low sustainability impact in the transportation network. • Metric value 2: The technology has a medium sustainabil- ity impact in the transportation network. • Metric value 3: The technology has a high sustainability impact in the transportation network. Technology Barriers (POSI) • Metric value 1: The technology faces four or more of the barriers discussed in Chapter 3 for its implementation. • Metric value 2: The technology faces three of the barriers discussed in Chapter 3 for its implementation. • Metric value 3: The technology faces two of the barriers discussed in Chapter 3 for its implementation. • Metric value 4: The technology faces only one of the barri- ers discussed in Chapter 3 for its implementation. • Metric value 5: The technology faces none of the barriers discussed in Chapter 3 for its implementation. In-vehicle vision enhancement (V2I) Medium High Medium 415,110- 748,134 Data Collection, Data Management and Processing Unfamiliarity with core or applied technology; Uncertainty concerning actual performance; Insufficient political or public acceptance; Additional implementation requirements; Need for new or conflict with existing regulations and standards. Characteristics Driver information system Impact Estimate Costs ($K) Transportation Agency Role Technology Barriers Mobility Safety Sustainability Table C-10. (Continued).

89 Costs For the comparison of costs, the research team used the average of the nominal values presented in Chapter 3. As in the bridge deck evaluation example, a fuller treatment would represent the ranges of current thinking about possible costs. Because the research team was modeling the decisions by trans- portation agencies, the costs considered were those that would be borne directly by the agency itself. For several of the technol- ogy applications discussed in this section these represent total costs as well. For others, a substantial or even preponderant share would need to be borne by private individuals and ven- dors such as automobile OEMs. For the present analysis, these latter were assumed to present a barrier to external acceptance in the form of resistance by the public (one of the factors in the external dimension of the POSI scale). This would then be reflected in a less favorable POSI measure which, in turn, would affect the relative standing of that technology alternative.73 Comparison of Technologies Table C-11 illustrates the tradeoffs involved in implement- ing different driver information systems. There are strong differences among the different technologies. Mobility-Safety Tradeoffs Figure C-3 shows that a considerable number of technolo- gies have significant equivalent mobility and safety impacts. These technologies are dynamic message signs, cooperative adaptive cruise control, in-vehicle vision enhancement, in- vehicle navigation systems with GPS, integrated telephone information systems, and portable dynamic message signs. The rest of the technologies only have a marginal effect in one or both of the safety and mobility dimensions. In this grouping, the most recent technologies offer the better results in terms of safety and mobility. As mentioned in the Iden- tify section, this may be because the newest designs of driver information systems have evolved into systems designed to serve multiple purposes. Mobility-Cost Tradeoffs Figure C-4 shows one estimate of the relationship between mobility and agency costs. Systems that can provide the highest mobility impact are also the most expensive (i.e., integrated telephone information systems and in-vehicle navigation systems with GPS). However, the costs incurred by transportation agencies with respect to these two tech- nologies differ. For instance, in-vehicle navigation systems with GPS provide the same mobility benefit as integrated telephone information systems, but at a much lower cost. Nevertheless, transportation agencies should consider that, in the case of in-vehicle navigation systems with GPS, they would only need to incur a minimal share of the total sys- tem costs with the rest paid by drivers. By omitting drivers’ costs, in-vehicle navigation systems with GPS become a less expensive option for transportation agencies than integrated Driver information system Mobility Safety Sustainability Agency Costs Total Costs ($M) Technology Barriers (POSI) Internet traffic pages 1.5 1 1 0.69 0.69 3 Kiosks 1 1 1 0.99 0.99 2 Telephone information systems 2 1 1 1.65 1.65 4 Integrated telephone information systems 3 2 2 2 2 3 Highway Advisory Radio 1 2 1 0.497 0.497 4 Dynamic Message Signs 2 2 1 1.031 1.031 3 Portable Dynamic Message Signs 2.5 2.5 2 0.478 0.478 2 Cooperative Adaptive Cruise Control (V2V) 2 3 1 0.099 200 1 In-vehicle navigation systems with GPS 3 2 2 0.099 25.09 3 In-vehicle vision enhancement (V2I) 2 3 2 0.122 582 1 Table C-11. value-based comparison for driver information systems. 73 In a full STREAM analysis, a more quantitative tally of how much of a barrier the externally borne costs might be would be examined. There may (or may not) be less reluctance to install a $40 device than a $400 one but anything greater than zero would likely pose some challenge. Further, there is also the issue of whether the device in question would be solely devoted to the intended pur- pose or might be (like a mobile telephone) something that already exists that could be further repurposed to perform a traffic information function. The fundamental approach to the partitioning and treatment of costs that has been employed in this analysis would remain.

90 telephone information systems. As reflected in the POSI scores, transportation agencies could opt for supporting the implementation of a technology that would be less expensive for them but that would have higher system costs but pos- sibly less-wide public acceptance. Mobility-Sustainability Tradeoffs Figure C-5 shows that integrated telephone information systems and in-vehicle navigation systems provide the highest combined mobility and sustainability impact. Another good option is portable dynamic message signs, and, to a lesser extent, in-vehicle vision enhancement. The most recent and advanced driver information systems are designed to meet multiple goals. For instance, in this case, reductions in travel time and increasing travel speeds can also result in reductions to GHG emissions. Safety-Cost Tradeoffs Figure C-6 shows technology options that could offer superior safety effects for relatively low expected average costs. For example, portable dynamic message signs are a technology that can offer the highest safety impact at the lowest possible cost. Other technologies worth noting are highway advisory radio, dynamic message signs, and inte- Figure C-3. Mobility and safety tradeoff. Figure C-4. Mobility and cost tradeoff.

91 grated telephone information systems. Two other technolo- gies could offer high safety impacts at apparently low agency cost (i.e., in-vehicle navigation systems with GPS and coop- erative adaptive cruise control technologies). In these cases, costs would be primarily covered by motorists and not by transportation agencies. Comparison of Technology Alternatives The research team compared technology alternatives in terms of an overall value metric that is the product of the metric value for mobility, safety, and sustainability. By treat- ing each of the metric values defined as representing a dis- tribution of random variables, the research team obtained a proxy for the total benefit in terms of agency goals of the technology alternative when implemented. This was plotted against the metric value for POSI with the two values being taken as an approximation of relative expected value among the alternatives being considered. Figure C-7 shows this total value metric, the product of the mobility, safety, and sustainability values versus the measure of degree of implementation difficulty. Each point in the plot represents the assessment of an alterna- tive’s relative expected value (i.e., the farther from the ori- gin, the higher this value is assumed to be) while the error bars show an estimate of the degree of uncertainty in each Figure C-5. Mobility and sustainability tradeoff. Figure C-6. Safety and cost relationship.

92 dimension.74 The vertical axis represents the total mission goal value considering the three metrics of the analysis: mobility, safety and sustainability. The points further from the origin represent those technologies that offer the high- est combined assessment of potential agency mission value. The horizontal axis represents the probability of successful implementation (POSI) of each technology. The points fur- ther from the origin represent technology options with the highest POSI (i.e., the fewest identified potential obstacles or barriers). The research team also plotted iso-curves that show the contours of equivalent (in relative expected value terms) tradeoffs between the presumed total agency mission benefit and the POSI metric. Movement along these curves away from the origin would imply trading some potential benefit in exchange for a higher POSI while maintaining the same expected value. Viewing the information in this way makes it possible to present in an integrated illustration what would otherwise be a complicated set of information: the results of the metric value analyses in terms of mobility, safety and sustainability; the range of uncertainty about these values for the different technologies; the barriers to implementation identified for each alternative; and the tradeoffs between the characteristics of a group of technologies now placed on the same scale. As noted in the other STREAM case studies, other views of this same type could be generated to more fully represent in a two-dimensional format what is a multi-dimensional space. Figure C-7 shows what may not before have been clear for such a disparate and heterogeneous set of technology alternatives—Irrespective of the technical basis for each approach or the industry sector from which it might have emerged, from the transportation agency mission (i.e., func- tional) perspective, the technologies form several groups. In the bottom of the graph are kiosks and internet traffic pages (which have a low expected value due to both relatively lesser potential value to improving transportation agencies’ func- tions of providing traffic and safety information and also somewhat low POSI). Telephone information systems and highway advisory radio belong to group of technologies that may offer only marginal benefit for transportation agencies but that can be readily implemented in light of minimal bar- riers. This can be seen by their placement on a higher equal- value contour than the first group. Along a yet higher contour is the group representing in- vehicle vision enhancement technologies, cooperative adaptive cruise control, and dynamic message signs. The first two offer a very high potential mission value, but the existing difficulties for their implementation give them an expected value equiva- lent to the less demanding alternative of dynamic message signs. In-vehicle vision enhancement requires the coordination of multiple parties (i.e., transportation agencies, car manufac- turers, and motorists) for successful implementation. It is also a novel technology with uncertain expected benefits. In addition, when analyzing its combined mobility, safety, and sustainabil- ity effect, it is clear that a few other technologies present fewer implementation difficulties and similar functional returns to Figure C-7. Product of mobility, safety, and sustainability values compared to implementation barriers. 74 These uncertainties do not vary greatly in this case because of the method used to form these measures. A more detailed approach employing a survey or expert panel, for example, would yield substantial differences in uncertainty among the technology applications with the more speculative, leading edge alternatives displaying the greater uncertainty.

93 transportation agencies. A similar logic applies for cooperative adaptive cruise control. However, the high functional returns of these technologies should be noted. This suggests both the value of keeping technologies with different maturities in an integrated perspective as well as revisiting how the expected value of different alternatives might change as their underlying technologies mature. These assessments might also well change if there is more detailed analysis than could be provided here as well as taking into closer account the specific challenges faced by individual local or regional agencies and the environment in which they operate. What a preliminary view such as this, and the underlying analysis that supports it, does is to highlight where limited resources for assessment might be most usefully directed to support the local decisions required. The portable dynamic message signs alternative is sep- arated from the other groups because it is a technology alternative that offers a clear higher benefit than the tech- nologies in the bottom of the graph; however, its relatively low POSI score remains a cause of concern for transporta- tion agencies and reduces what would otherwise be a higher expected value. Again, given its potential benefit, it would be interesting for transportation agencies to explore ways to mitigate some of the obstacles to it. This is a technology for which transportation agencies can play the leading role in its distribution. Finally, there are two clear “winners” in this analysis: inte- grated telephone information systems and in-vehicle navigation systems with GPS. They offer the same high potential functional value for transportation agencies and the same relatively high POSI. When compared to all other alternatives, these two tech- nologies provide the highest expected value. In terms of POSI, these technologies face a similar number of implementation barriers as dynamic message signs and internet traffic pages. Both the latter have already penetrated transportation systems at significant levels, thus it is possible that existing barriers for integrated telephone information systems and in-vehicle navi- gation systems with GPS could be overcome as well. This would require both a closer look at those barriers and a local assess- ment for how serious they might be and what options might exist for surmounting them. One thing not brought out clearly in this figure is that syn- ergies may exist between these two leading technologies that transportation agencies could exploit. For example, there is already a tendency to incorporate in-vehicle navigation systems with GPS into internet-based mobile devices and PDAs. Therefore, in the future motorists using these naviga- tion systems might also access integrated telephone informa- tion systems and receive traffic and weather information as well access traffic cameras and local maps. This could expand how motorists could adapt to changing road conditions and improve significantly the quality of the information that motorists use for planning their trips. It could create an addi- tional purpose for those telephone information systems in which transportation agencies have already invested. Decide At this stage of the analysis, transportation agencies inter- ested in driver information systems can use the information provided in the last four sections to decide which technologies to adopt and which technologies to monitor. The results of this analysis are highly sensitive to the realities of transportation agencies, which are heterogeneous in terms of culture, administration, personnel, and financial capabilities. The decisions resulting from applying STREAM to the case of driver information systems would need to acknowledge this heterogeneity and not assume that what works in one region will necessarily work in another. Generally, the analysis shows that synergies can be exploited at the technology level and at the institutional level. New driver information systems have opened new possibilities for integrating existing systems with novel applications (e.g., inte- grated telephone information systems and in-vehicle naviga- tion systems with GPS). In addition it is possible that the most radical designs (e.g., in-vehicle vision enhancement and coop- erative adaptive cruise control) could both yield and require synergies that transportation agencies could pursue with other relevant actors (e.g., automakers, transportation companies, and information providers) who very likely would be needed to support the distribution of these novel technologies.

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TRB’s National Cooperative Highway Research Program (NCHRP) Report 750: Strategic Issues Facing Transportation, Volume 3: Expediting Future Technologies for Enhancing Transportation System Performance presents the systematic technology reconnaissance, evaluation, and adoption methodology (STREAM).

STREAM is a process that transportation agencies can use to identify, assess, shape, and adopt new and emerging technologies to help achieve long-term system performance objectives. The process reflects relevant trends in technologies and their applications and is designed to help transportation agencies anticipate, adapt to, and shape the future.

NCHRP Report 750, Volume 3 is the third in a series of reports being produced by NCHRP Project 20-83: Long-Range Strategic Issues Facing the Transportation Industry. Major trends affecting the future of the United States and the world will dramatically reshape transportation priorities and needs. The American Association of State Highway and Transportation Officials (AASHTO) established the NCHRP Project 20-83 research series to examine global and domestic long-range strategic issues and their implications for state departments of transportation (DOTs); AASHTO's aim for the research series is to help prepare the DOTs for the challenges and benefits created by these trends.

Other volumes in this series currently available include:

• NCHRP Report 750: Strategic Issues Facing Transportation, Volume 1: Scenario Planning for Freight Transportation Infrastructure Investment

• NCHRP Report 750: Strategic Issues Facing Transportation, Volume 2: Climate Change, Extreme Weather Events, and the Highway System: Practitioner’s Guide and Research Report>

• NCHRP Report 750: Strategic Issues Facing Transportation, Volume 4: Sustainability as an Organizing Principle for Transportation Agencies

• NCHRP Report 750: Strategic Issues Facing Transportation, Volume 5: Preparing State Transportation Agencies for an Uncertain Energy Future

• NCHRP Report 750: Strategic Issues Facing Transportation, Volume 6: The Effects of Socio-Demographics on Future Travel Demand

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