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Leveraging Big Data to Improve Traffic Incident Management (2019)

Chapter: Chapter 2 - State of the Practice of TIM

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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
×
Page 13
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
×
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Suggested Citation:"Chapter 2 - State of the Practice of TIM." National Academies of Sciences, Engineering, and Medicine. 2019. Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: The National Academies Press. doi: 10.17226/25604.
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9 To improve TIM, attention is needed at all levels of TIM programs, including strategic, tactical, and support activities. Strategic activities focus on establishing TIM within the fabric of responder agencies through institutional structures, such as establishing a formal TIM performance measurement program and making the business case for TIM. Tactical TIM activities include operational efforts of incident response and include surveillance and detection, mobilization and response, scene management, and clearance and recovery. Support activities are typically those performed by practitioners who are not part of on-scene response and include communication, coordination, and management functions that enable incident responders to perform their jobs better and more efficiently. This chapter examines the state of the practice in TIM at all levels, as well as the current state of TIM data, and helps to set the stage for the broader objective of examining how Big Data might benefit TIM. 2.1 State of the Practice The practice of TIM centers on the activities associated with traffic incident response, from incident detection and verification through recovery of the roadway to its normal operation. The foundation for the state of the practice in TIM can be traced to a series of publications that were created over the past decade. The use of this intellectual capital by state and local responder communities typically is spearheaded by the transportation agency. The leadership of the FHWA, along with state departments of transportation, responder agencies, industry, and academia, have created a national model for TIM. Table 2-1 lists key information sources that provide strategies for effective TIM programs. FHWA’s Traffic Incident & Events Management (TI&EM) Knowledge Management System (KMS), also called the Traffic Incident Management Knowledgebase, is another excellent source of TIM-related documents (FHWA 2017c). In recent years, federal, state, and local institutions have driven significant change in the state of the practice in TIM through efforts to expand coordinated, multidisciplinary operations and to formalize TIM programs within the broader context of agency planning and operations. Improvements to individual and institutional effectiveness can be attributed in large part to: • Establishment of local, regional, and statewide TIM committees, • Implementation of TIM legislation, • Development and implementation of a National TIM Responder Training Program, • Development of local/statewide TIM strategic plans, • Development and implementation of agency operating agreements, and • Implementation of agency policies for safe quick clearance. C H A P T E R 2 State of the Practice of TIM

10 Leveraging Big Data to Improve Traffic Incident Management 2.1.1 Establishment of Local, Regional, and Statewide TIM Committees The establishment of local, regional, and statewide TIM committees has led to better planning, coordination, and communications among TIM responder groups. Local TIM teams discuss tangible on-scene practices and operating considerations, and often debrief significant or problematic incidents. The local TIM team is a prominent part of Florida’s statewide strategy. In Florida, 25 individual TIM teams cover all urban and suburban areas and many rural areas of the state (Florida DOT TIM Teams 1996). The Traffic Incident Management for the Baltimore Region (TIMBR) Committee illustrates how regional stakeholders get together to plan and coor- dinate TIM activities as part of MPO planning efforts (Baltimore Metropolitan Council 2017). Statewide committees support TIM at a broader, institutional level. Many state TIM groups include representatives from individual disciplines, generally represented by leadership of state- wide associations or organizations for law enforcement, fire and rescue, transportation, and towing. Virginia provides an excellent example of an effective state TIM body (VA Exec. Order No. 58 [2013] and VA Exec. Order No. 15 [2015]). In 2010, the governor of Virginia established the Virginia Traffic Incident Management Committee (since renamed the Virginia Statewide Traffic Incident Management [VASTIM] Title Link Traffic Incident Management Handbook (Owens et al. 2010) http://www.ops.fhwa.dot.gov/eto_tim_pse/pu blications/timhandbook/tim_handbook.pdf Best Practices in Traffic Incident Management (Carson 2010) http://www.ops.fhwa.dot.gov/publications/fhw ahop10050/fhwahop10050.pdf Field Operations Guide for Safety/Service Patrols (Sparks, Schuh, and Smith 2009) http://www.ops.fhwa.dot.gov/publications/fhw ahop10014/fhwahop10014.pdf Traffic Incident Management in Hazardous Materials Spills in Incident Clearance (Daniell 2009) http://www.ops.fhwa.dot.gov/publications/fhw ahop08058/fhwahop08058.pdf Traffic Control Concepts for Incident Clearance (Birenbaum, Creel, and Wegmann 2009) http://www.ops.fhwa.dot.gov/publications/fhw ahop08057/fhwahop08057.pdf Federal Highway Administration Service Patrol Handbook (Houston et al. 2008) https://ops.fhwa.dot.gov/publications/fhwahop 08031/ffsp_handbook.pdf Simplified Guide to the Incident Command System for Transportation Professionals (Latonski and Ang-Olson 2006) http://www.ops.fhwa.dot.gov/publications/ics_ guide/ics_guide.pdf Alternate Route Handbook (Dunn Engineering Associates 2006) http://www.ops.fhwa.dot.gov/publications/ar_ handbook/arh.pdf Traffic Incident Management Quick Clearance Laws: A National Review of Best Practices (Carson 2008) https://ops.fhwa.dot.gov/publications/fhw ahop09005/quick_clear_laws.pdf “Comprehensive Framework for Planning and Assessment of Traffic Incident Management Programs” (Jin et al. 2014) https://journals.sagepub.com/toc/trra/247 0/1 “A National Unified Goal for Traffic Incident Management (TIM): What Is it, and Why Is it Needed” (Corbin 2008) https://www.pcb.its.dot.gov/t3/s080911/corbin .pdf “Traffic Incident Management Cost Management and Cost Recovery: Executive Level Briefing” (Rensel et al. 2012) https://ops.fhwa.dot.gov/eto_tim_pse/ppt/tim _cm_cr_exec_brief/tim_cm_cr_exec_brief.pdf Role of Transportation Management Centers in Emergency Operations: Guidebook (Krechmer et al. 2012) https://ops.fhwa.dot.gov/publications/fhwahop 12050/fhwahop12050.pdf Table 2-1. Key information sources on TIM program elements and practices.

State of the Practice of TIM 11 Committee) and designated the state police and state transportation agencies to lead the effort. The VASTIM Committee has been instrumental in advancing TIM in the state (VA Exec. Order No. 58 [2013], VA Exec. Order No. 15 [2015]). 2.1.2 Implementation of TIM Legislation TIM legislation has played an important role in advancing the state of the practice in TIM by promoting safety and quick clearance. Three principal TIM laws have been enacted to various degrees across the United States: • “Driver Removal” laws require drivers involved in crashes to move their vehicles out of the roadway, • “Authority Removal” laws give public officials the right to move cars and cargo at incidents, and • “Move Over” laws require drivers to vacate the lane adjacent to emergency responders on multi-lane roadways or to slow down if they cannot safely move over or where there is only one directional lane of travel. Move-over laws are present in every state, in the District of Columbia and in Puerto Rico. Although common, driver removal and authority removal laws are not found in every state (American Automobile Association 2017) (Carson 2008). 2.1.3 Development and Implementation of National TIM Responder Training At the heart of national TIM progress is the National TIM Responder Training Program, which was developed under the second Strategic Highway Research Program (SHRP 2) and deployed beginning in the summer of 2012 as part of the second phase of the FHWA’s “On-Ramp to Innovation: Every Day Counts” (EDC-2) initiative (FHWA 2012). Through July 2018, more than 344,000 incident responders had attended multidisciplinary training that was developed “by responders, for responders.” The nine lessons in the training program have established a foundation for the way that traffic incidents are handled, covering important topics such as scene safety, vehicle positioning, incident command, and traffic control. The National TIM Responder Training Program has become the de-facto national standard for the state of the practice, and most preexisting state products have gone through equivalency reviews. An online version of the National TIM Responder Training Program is hosted by the National Highway Institute (FHWA n.d.-a). 2.1.4 Development of TIM Strategic Plans Increasingly, TIM is being planned strategically in the form of guidance documents for program elements. Strategic plans at the local, regional, or state level stipulate the type of TIM activities, desired state, a time horizon, and a means to achieve objective. Strategic Highway Safety Plans (SHSPs), a type of state-level planning, are required by the FHWA for every state in which TIM has begun to find traction. Whether as a formal area of emphasis or a strategy, TIM and the components of TIM find the important nexus with safety in the SHSP. Several states have made TIM a priority emphasis area; other states mention the value of TIM to support other safety or mobility goals like managing congestion, reducing aggressive driving, or promoting safety among vulnerable road users. The effectiveness of these plans is evi- denced by the advanced state of the practice seen in states such as Florida, Oregon, and Maryland (Pecheux, Shah, and O’Donnell 2016). In addition, the FHWA notes that incorporating TIM

12 Leveraging Big Data to Improve Traffic Incident Management into the planning process is a good business practice and recommends it as a way of formalizing and institutionalizing TIM within an agency and the broader agency goals (Pecheux, Shah, and O’Donnell 2016). 2.1.5 Development and Implementation of Agency Operating Agreements Public agencies are quite accustomed to formalizing relationships with each other to accomplish organizational objectives. Many state and local agencies have developed memo- randa of understanding, operating policy statements, and agreements to work cooperatively, establish roles and responsibilities, and/or set forth targets for TIM performance. One of many examples is the Joint Operating Program Statement (JOPS) by the Washington State Patrol, Washington Fire Chiefs, and the Washington State Department of Transportation (Washington State DOT 2016a). 2.1.6 Implementation of Agency Policies for Safe and Quick Clearance Policies for safe and quick clearance on traffic incidents have led to improvements in TIM performance and have advanced the state of the practice in TIM. In early 2011, a major policy revision in Arizona required police officers to move vehicles involved in incidents completely off the roadway (away from view) as quickly as possible. The Arizona Department of Public Safety (AZDPS) used data collected via the crash report on roadway and incident clearance times before and after this policy change to determine if the policy had an impact on TIM performance. The results showed significant reductions in both roadway and incident clearance times for non-injury and injury crashes (Pecheux 2016). 2.2 The Use of Data to Support TIM Continued advancements in TIM will require more and better data to quantify improve- ments, justify funding, and guide future development of the practice. Reviewing the incident timeline sets the stage for data collection and opportunities for Big Data to improve TIM. The incident timeline is shown in Figure 2-1 (FHWA 2013b). At any point along the timeline—detection, verification, response, roadway clearance, incident clearance, and return to normal flow—possibility exists for improvement. The identification of where these improvements could be made can be facilitated by the collection and analysis of data, including Big Data. The current state of the practice in the use of data for TIM primarily relates to TIM performance measurement and management and in making the business case for TIM programs. 2.2.1 TIM Performance Measurement and Management TIM performance measurement and management is another way in which agencies are advancing the state of the practice of TIM. Performance measurement and management, which are becoming more and more important, require the collection of data. In cooperation with 11 states as part of a Focus State Initiative, the FHWA has defined three national performance measures for TIM (Owens et al. 2009): • Roadway clearance time (RCT): The time between the first recordable awareness of the incident by a responsible agency and the time that all lanes are available for traffic flow.

State of the Practice of TIM 13 • Incident clearance time (ICT): The time between the first recordable awareness of the incident by a responsible agency and the time at which the last responder has left the scene. • Secondary crashes: Subsequent crashes are crashes that occur at the scene of an original incident or in the queue, including crashes involving vehicles traveling in the opposite direc- tion. (The FHWA has more recently suggested that a crash-to-crash relationship between the primary and secondary incident be used for simplicity). The TIM timeline in Figure 2-1 shows the importance of T1, T5, and T6; these points represent the data points needed to calculate RCT and ICT. Work performed under NCHRP Project 07-20, “Guidance for Implementation of Traffic Incident Management Performance Measurement,” (Pecheux, Brydia, and Holzbach 2014) and subsequent direction from the FHWA have provided guidance to agencies on TIM data collection, analysis, and performance measurement, including a comprehensive list of the types of data central to measuring TIM performance (Pecheux 2016). To date, the primary sources of data for TIM performance analysis have been transportation management centers (TMCs) and SSP programs. The state of the practice has expanded more recently to include the use of data from law enforcement crash reports and computer-aided dispatch (CAD) systems, as well as integration of data from various systems to improve the quality and quantity of data. Nonetheless, the current state of data collection and use by TIM programs varies significantly between states, between agencies/regions within states, and even within agencies. The following are highlights of the current and emerging TIM data practices from leading agencies/states: • Use of data from crash reports: The AZDPS has both pioneered and championed the use of data in TIM. In 2010, AZDPS officers in the metropolitan Phoenix area began collecting additional data elements in conjunction with traffic crash investigations. Using electronic reporting software, the agency modified the officer input interface and underlying data- base to add RCT, ICT, and secondary crashes to the myriad data elements on the statewide reporting format. The program later expanded to AZDPS officers statewide and ultimately CAD = computer-aided dispatch; PSAP = public safety answering point; TMC = traffic management center Source: FHWA (2013b) Figure 2-1. Incident timeline.

14 Leveraging Big Data to Improve Traffic Incident Management led to changes in the statewide reporting format for all agencies in 2014 (Pecheux 2016). AZDPS actively measures and reports the TIM performance measures as part of its standard operating procedures. • Integration of TMC and SSP datasets: The integration of TMC and SSP data increases the transportation dataset, as SSP operators handle a significant number of incidents as single responders, and many of their activities are self-initiated. The move from paper responder logs and voice communications to mobile computing platforms and smart devices to docu- ment times and activities has improved the quantity and quality of data available from SSP programs (Florida DOT 2011). In Washington State, incident response (IR) crew members enter incident data using laptop computers in their trucks to create an electronic incident report. After each shift, the data is uploaded to the Washington Incident Tracking System (WITS), a centralized statewide database (Washington State DOT 2016b). Operators at the Niagara International Transportation Technology Coalition (NITTEC) traffic operations center (TOC) in Buffalo, New York, can see both their incident entry screen and Buffalo’s SSP activity log. The TOC data entry screen contains data elements for the entire incident timeline, as well as a checkbox for secondary crashes (Pecheux 2016). • Integration of TMC and CAD datasets: A key step for improved data has been the inte- gration of TMC and law enforcement computer-aided dispatch (CAD) systems. Integration enables data to be captured for a larger proportion of statewide incidents and, in particular, those outside TMC or SSP geographic and temporal operations. Minnesota, Wisconsin, and Virginia have integrated their CAD and TMC or advanced traffic management systems (ATMS) (Pecheux 2016). Other states (e.g., New Jersey) are implementing changes to facili- tate integration (NJ TIM n.d.). • Use of crowdsourced data: Crowdsourced mobile applications (e.g., Waze) and data consoli- dators (e.g., INRIX and HERE) are providing new data that agencies use to various degrees, such as in the National Performance Management Research Data Set (NPMRDS) (FHWA 2013a). These data sources offer opportunities to expand TIM practices beyond major urban freeways to suburban and rural freeways as well as major arterials. These data sources are now being applied by a few agencies for incident detection and are approaching the realm of Big Data, but this data is still on the cusp of being used for TIM performance measurement and management. Some states, including Florida and Massachusetts, have begun using Waze to supplement existing surveillance and detection systems. Other states, such as North Carolina and Iowa, use INRIX for analytics-based incident detection (Barichello and Knickerbocker 2017, Oerter 2010). Waze Connected Citizen Program data and 511 travel infor- mation system data are being integrated to enhance both datasets and to improve situational awareness for both TMC operators and Waze users (Smith 2016). • Use of unmanned aerial vehicle (UAV) technology: Information specific to the location and nature of incidents enables a more effective response among fire and rescue, EMS, transportation, towing and recovery, hazardous materials, coroner, and other entities. Some agencies (e.g., in New York City and Toronto) are beginning to explore the potential of UAV technology to capture incident details for accident investigation before and during scene management (Durkin 2015). 2.2.2 Making the Business Case for TIM Ultimately, to advance the state of the practice in TIM, TIM programs must be consistently supported and funded. The need for justification is no more evident than in the competition for agency funds, which occurs more and more often amidst dwindling agency operating budgets. TIM programs often are targeted for defunding because their value is not readily recognized. For example, SSP programs may be seen only from the lens of their motorist assistance function, rather than as a service that enhances safety, reduces roadway congestion, and mitigates the

State of the Practice of TIM 15 likelihood of secondary crashes. The FHWA recently developed a guide for agencies on how to make the business case for TIM in which data plays a critical role—particularly data that documents the need for or benefits from a program’s activities in a way that can be balanced against its cost (Pecheux, Shah, and O’Donnell 2016). Few agencies maximize the use of data for this purpose. Given the growing availability of TIM data, however, the business case for TIM is one that can be more readily supported. Demonstrating the usefulness of data that supports decisions is a powerful technique for making the business case, as is evidenced by the following examples from Oregon and Maryland: • In Oregon, maintenance crews were routinely tasked with supporting TIM functions, often at the expense of their other responsibilities. In one area of the state, the Oregon DOT used data to demonstrate the need for a dedicated incident responder to improve both traffic and maintenance operations. A maintenance position was sacrificed to create a position for a dedicated incident responder, with a positive outcome for both functions (Pecheux, Shah, and O’Donnell 2016). • The Maryland State Highway Association analyzed data on incident clearance times to demonstrate the need for and value of expanding their TIM operations. By making the business case for TIM, the program secured funding for expanded SSP operations to include all major routes within the state and to modify the patrol hours for three of the TOCs from a 15-hour, 5-days-per-week operation to a 24-hour, 7-days-per-week operation (Pecheux, Shah, and O’Donnell 2016). 2.3 Further Advancing the State of the Practice of TIM TIM committees, national responder training, legislation, quick-clearance policies, and operating agreements have advanced the state of the practice of TIM over the past decade. The resulting improvements in responder effectiveness, combined with emerging TIM data collection systems and processes, have positioned TIM to make another step forward in the coming years. Toward this end, the FHWA has undertaken an ambitious program to accelerate the nationwide implementation of TIM data collection and use by states. Running through calendar years 2017 and 2018, the fourth iteration of the FHWA’s Every Data Counts program (EDC-4) has been a 2-year effort to assist adopting states in gathering a greater quantity and quality of TIM data, focused on RCT, ICT, and secondary crashes. Thirty-five states worked to implement the EDC-4 TIM data innovation, and EDC-4 was successful at evolving the state of the practice in the collection and use of TIM data, as 20 states reported advancing at least one level during the 2-year period. Although the recent and ongoing progress is promising, another step has yet to be taken from the current state of practice to apply Big Data analytics in TIM. The increased quantity and improved quality of TIM-related data shows promise that the application of Big Data can further advance the state of the practice by uncovering trends and relationships that lead to improvements in TIM strategic, tactical, and support activities. Big Data analytics have the potential to spur modifications to policies, procedures, and training, thereby improving the safety and effectiveness of incident responders, enabling them to perform their jobs better. The application of Big Data could advance the state of the practice in TIM performance manage- ment and provide ammunition to make a far more compelling business case for TIM programs and strategies. Advanced analytics could equip practitioners with information for decision support. If those analytics can be used in real time and are even predictive of traffic impact, responder actions, on-scene activities, traveler information, traffic management, and clearance strategies might be adjusted, leading to reductions in congestion and secondary crashes.

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"Big data" is not new, but applications in the field of transportation are more recent, having occurred within the past few years, and include applications in the areas of planning, parking, trucking, public transportation, operations, ITS, and other more niche areas. A significant gap exists between the current state of the practice in big data analytics (such as image recognition and graph analytics) and the state of DOT applications of data for traffic incident management (TIM) (such as the manual use of Waze data for incident detection).

The term big data represents a fundamental change in what data is collected and how it is collected, analyzed, and used to uncover trends and relationships. The ability to merge multiple, diverse, and comprehensive datasets and then mine the data to uncover or derive useful information on heretofore unknown or unanticipated trends and relationships could provide significant opportunities to advance the state of the practice in TIM policies, strategies, practices, and resource management.

NCHRP (National Cooperative Highway Research Program) Report 904: Leveraging Big Data to Improve Traffic Incident Management illuminates big data concepts, applications, and analyses; describes current and emerging sources of data that could improve TIM; describes potential opportunities for TIM agencies to leverage big data; identifies potential challenges associated with the use of big data; and develops guidelines to help advance the state of the practice for TIM agencies.

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