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Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations (2020)

Chapter: Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure

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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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Suggested Citation:"Chapter 2: Issues Influencing Public Agency Investment in Connected Vehicle Infrastructure." National Academies of Sciences, Engineering, and Medicine. 2020. Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations. Washington, DC: The National Academies Press. doi: 10.17226/25946.
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18 CHAPTER 2: ISSUES INFLUENCING PUBLIC AGENCY INVESTMENT IN CONNECTED VEHICLE INFRASTRUCTURE Vehicle connectivity is likely to be ubiquitous in 20 years (NASEM, 2019). To address the evolving transportation landscape, DOTs must consider infrastructure investments to capitalize on the opportunities that CVs offer, while at the same time, changing the status quo with regard to the safety and mobility performance of their transportation networks. V2I applications enabled by CV infrastructure provide new tools in the toolbox for DOTs to consider in pursuit of their performance goals and objectives. Many such applications have been conceived and developed in literature and promise significant benefits to both DOT customers and internal DOT functions. Chapter 1 summarized recent planning initiatives from several state DOTs that clearly indicate interest, expectation, and momentum in larger scale deployments and incorporation of CV infrastructure into their capital, operating, and maintenance programs. These projects and plans show how state DOTs are actively preparing for and deploying CV infrastructure, including understanding benefits to agency effectiveness and customer service, the requirements of deployment, costs, and risks and ways to mitigate these risks. However, the path to larger scale investments must address a fundamental question: do public agencies need to make any investments in CV infrastructure to develop and implement V2I applications given the substantial role the private sector plays in the CV ecosystem (e.g., the private sector provides the CVs and roadside wireless communications infrastructure)? If such investments are warranted, which emerging candidate V2I applications must be prioritized and planned for in the next 5 to 10 years, what scale of investment is needed, and which of these investments should be advanced to a formal business case analysis? This chapter reviews a series of issues that influence public agency decision-making on investing in CV infrastructure. These fundamental considerations have direct bearing on the need for a business case to support public agency investment in CV infrastructure and the decision-making process an agency would go through to advance investments for business case analysis. The issues covered in this chapter are the types of V2I applications most in need of public CV infrastructure investment and their benefits, CV application deployment requirements and their state of readiness for deployment, and the costs of investment in V2I applications and CV infrastructure. METHODOLOGY AND DATA SOURCES Analysis in this chapter relies on a selection of current literature identifying and defining viable V2I applications and their benefits. As introduced in chapter 1, the CVRIA, published by the ITS JPO, provides an authoritative compilation of V2I, V2V, and V2X applications with detailed explanation of their functionality, requirements, and indication of benefits. The CVRIA forms the primary basis for V2I application selection and analysis. The research team consulted several other literature sources to augment and confirm the use of applications in the CVRIA, including: • NCHRP Project 03-101, Costs and Benefits of Public Sector Deployment of Vehicle-to- Infrastructure Technologies (Evans et al., 2014)

19 • AASHTO’s Connected Vehicle Field Infrastructure Footprint Analysis (Wright et al., 2014) • Cooperative Automated Transportation (CAT) Coalition’s CAT/Connected Automated Vehicle (CAV) Funding Initiatives in the States Survey Results (NOCoE, 2019) • How Locals Need to Prepare for the Future of V2V/V2I Connected Vehicles (Parikh et al., 2019) The identification of CV application deployment requirements also uses the architectures presented in the CVRIA. The CAT Coalition (2020a) provides a higher-level, generalized structure to the various components of the CV infrastructure environment. Cost data for CV infrastructure components was collected from DOTs with the most experience conducting pilot studies, operating test beds, or otherwise deploying CV technology. Additional sources of cost data include the ITS JPO Costs and Benefits Databases (ITS JPO, 2020) and Parikh et al. (2019) who, using similar methods, “obtained information about cost ranges for the critical equipment required for each application based on the experiences of pilot implementations, information from hardware vendors, and records collected by the [ITS JPO] for their Cost Database.” BENEFITS OF V2I APPLICATIONS AND NEED FOR PUBLIC CONNECTED VEHICLE INFRASTRUCTURE INVESTMENT The findings of this chapter begin by identifying emerging candidate V2I applications that DOTs should prioritize and plan for in the next 5 to 10 years and the benefits they can provide. The research identified a significant subset of V2I applications that provide safety and mobility benefits to DOT users, require DOT-provided network performance or usage information to enable, and rely on the high-speed, low-latency communication provided by CV infrastructure. V2I Applications of Interest to State Departments of Transportation As a first step, the research team analyzed all applications in the CVRIA to filter out those that are most dependent on V2I connectivity, and as a second criterion, those that depend the least on V2V market penetration (i.e., vehicles equipped with CV technology).2 The research team applied expert judgment and an understanding of the literature to assign levels of dependence on V2I connectivity and V2V market penetration, as defined below. • Dependence on V2I Connectivity o High – the presence of roadside infrastructure is absolutely required at a specific location to achieve anticipated benefits or if constant V2I connectivity is needed to enable the application. o Medium – the application can be enabled through V2I communications but can also be enabled for non-CV vehicles using traditional (non-CV) ITS technologies. 2 Refer to definitions of each CV application at https://local.iteris.com/cvria/html/applications/applications.html (ITS-JPO 2016).

20 Alternatively, the application does not necessarily require roadside equipment to be co-located at the location where benefits are anticipated, or if intermittent V2I connectivity could enable the application. o Low – the application does not use roadside infrastructure, or the roadside infrastructure does not include V2I communications. Example applications include FCW, Intersection and Left Turn Management Assist, and Road Weather Information and Routing for Emergency Responders. Reasons for the “low” dependence, among others, can include an application’s function can be achieved by a vehicle equipped with suitable sensors that does not rely on connectivity with infrastructure or other vehicles or does not rely on low-latency communications, and connectivity can be achieved through other means. • Dependence of High Market Penetration of V2V o High – high concentrations of CVs are needed for a consistent user experience, or safety is a factor. This generally applies to V2V safety applications. o Medium – the application can be enabled through V2V communications but can also be enabled for non-CV vehicles using traditional (non-CV) ITS technologies. o Low – the application did not include vehicles, or the application is infrastructure- based and only benefits vehicles with OBUs. Table 2 presents the results of applying the two criteria, which allowed the research team to filter for applications with higher levels of dependence on V2I connectivity in combination with lower levels of dependence on V2V market penetration. This filtering exercise identified more than 30 V2I applications (shaded in gray in Table 2) of potential primary interest to DOTs that would require investment in CV infrastructure. (Note: Table 2 also defines applications commonly referenced by their acronyms.) Table 2. CV Applications’ Dependence on V2I and V2V CV Application Dependence on V2I Connectivity Dependence on Market Penetration of V2V Advanced Automatic Crash Notification Relay Low Medium Advanced Traveler Information Systems* ATIS Medium Low Blind Spot Warning + Lane Change Warning BSW + LCW Low High Border Management Systems* Medium Low Connected Eco-Driving Medium High Container Security* Medium Low Cooperative Adaptive Cruise Control CACC Low High Curve Speed Warning CSW Medium Low Do Not Pass Warning DNPW Low High

21 Table 2. CV Applications’ Dependence on V2I and V2V CV Application Dependence on V2I Connectivity Dependence on Market Penetration of V2V Dynamic Eco-Routing Low Low Dynamic Ridesharing Low Low Dynamic Transit Operations Low Low Eco-Approach and Departure at Signalized Intersections High High Eco-Cooperative Adaptive Cruise Control Low High Eco-Freight Signal Priority High Low Eco-Integrated Corridor Management Decision Support System Low Low Eco-Lanes Management Low Low Eco-Multimodal Real-Time Traveler Information* Medium Low Eco-Ramp Metering High Low Eco-Smart Parking Medium Medium Eco-Speed Harmonization Medium Medium Eco-Traffic Signal Timing High Medium Eco-Transit Signal Priority High Low Electric Charging Stations Management Low Low Electronic Toll Collection Medium Low Emergency Communications and Evacuation EVAC Low Low Emergency Electronic Brake Light EEBL Low High Emergency Vehicle Preemption EVP High Low Enhanced Maintenance Decision Support System Low Low Forward Collision Warning FCW Low High Freight Drayage Optimization High Low Freight Signal Priority FSP High Low Freight Specific Dynamic Travel Planning Low Low Incident Scene Pre-Arrival Staging for Emergency Responders RESP-STG Low Medium Incident Scene Work Zone Alerts for Drivers and Workers INC-ZONE Medium Low Integrated Multi-Modal Electronic Payment* Medium Low

22 Table 2. CV Applications’ Dependence on V2I and V2V CV Application Dependence on V2I Connectivity Dependence on Market Penetration of V2V Intelligent Traffic Signal System I-SIG High Medium Intermittent Bus Lanes IBL High Low Intersection Movement Assist IMA Low High In-Vehicle Signage High Low Low Emissions Zone Management High Medium Mobile Accessible Pedestrian Signal System PED-SIG Medium High Oversize Vehicle Warning OVW Medium Low Pedestrian in Signalized Crosswalk Warning PSCW High Medium Performance Monitoring and Planning Low Low Queue Warning Q-WARN High Medium Railroad Crossing Violation Warning RCVW High Low Red Light Violation Warning RLVW High Low Reduced Speed Zone Warning / Lane Closure RSZW Medium Low Restricted Lanes Warnings Medium Low Road Use Charging Medium Low Road Weather Information and Routing Support for Emergency Responders Low Low Road Weather Information for Freight Carriers Medium Low Road Weather Information for Maintenance and Fleet Management Systems Low Low Road Weather Motorist Alert and Warning Medium Low Roadside Lighting High Low Route ID for the Visually Impaired Medium Medium Smart Parking (Travel Info, Eco Application, Park-and-Ride) Medium Low Smart Roadside Initiative SRI Medium Low Speed Harmonization SPD-HARM High Medium Spot Weather Impact Warning SWIW Medium Medium Stop Sign Gap Assist SSGA High Low Transit Connection Protection Low Low Transit Pedestrian Indication Low High Transit Signal Priority TSP High Low

23 Table 2. CV Applications’ Dependence on V2I and V2V CV Application Dependence on V2I Connectivity Dependence on Market Penetration of V2V Transit Stop Request Medium Low Transit Vehicle at Station/Stop Warnings Medium Medium Variable Speed Limits for Weather-Responsive Traffic Management Low Low Vehicle Data for Traffic Operations VDTO High Medium Vehicle Turning Right in Front of a Transit Vehicle VTRFTV Low High * While these five applications satisfy the criteria of medium dependence on V2I / low dependence on V2V, they have been filtered out. Two applications (ATIS and Eco-Multimodal Real-Time Traveler Information) provide general traveler information that have several other avenues of user acquisition that do not require public infrastructure. Three applications (Border Management Systems, Container Security, and Integrated Multi-Modal Electronic Payment) relate to activities that are not the typical purview of a DOT. The V2I applications shown in Table 2 can be combined (or bundled) to create a targeted CV solution with net benefits greater than that of the individual applications included in the bundle. ITS JPO has supported research and development activities for several such application bundles as part of its Dynamic Mobility Applications (DMA) development initiative (ITS JPO, Undated B). Table 3 lists these DMA program bundles and their component applications. Those in bold correspond to applications that met the filtering criteria in Table 2. Table 3. Dynamic Mobility Application Program Bundles CV Application DMA Bundle Component V2I Applications Enable Advanced Traveler Information System EnableATIS Not defined Freight Advanced Traveler Information Systems FRATIS Freight Specific Dynamic Travel Planning, Freight Drayage Optimization Integrated Dynamic Transit Operation IDTO Dynamic Transit Operations, Transit Connection Protection, Dynamic Ridesharing Intelligent Network Flow Optimization INFLO Q-WARN, SPD-HARM, CACC Multi-Modal Intelligent Traffic Signal Systems MMITSS EVP, FSP, I-SIG, PED-SIG, TSP Response, Emergency Staging and Communications, Uniform Management, and Evacuation R.E.S.C.U.M.E. RESP-STG, INC-ZONE, EVAC

24 Individual elements of the DMA program bundles also may be implemented through applications other than those from the research and development products of the ITS JPO DMA bundles. In addition, other bundles of V2I applications can be packaged based on problems to be addressed and deploying agency context. Types of V2I Application Benefits Prior research, cited in Section 2.1, established the range of potential benefits from CV applications. Benefits can be categorized as follows: • External or societal benefits result when improved service is directly provided to transportation system users in terms of safety, mobility (to include congestion relief), and asset condition. External or societal benefits also include environmental mitigation through sustainable strategy applications (e.g., Eco-Traffic Signal Timing). • Internal or agency benefits result from improvements in agency efficiencies related to infrastructure avoidable costs and improved agency asset and fleet management. NCHRP 03-101 (Evans et al., 2014) identified specific sources of these benefits: o Crash cleanup reduction – cost avoidance from a reduction in crashes and cleanup o Work zone crash reduction (crash cleanup reduction plus cost avoidance from damage to ROW and property under construction and lost time for construction to address the accident) o Lower cost of pavement condition detection o Adaptive lighting o Reduction in infrastructure to monitor traffic Internal benefits also include acting as a source of revenue—directly from select applications such as road use charging, or indirectly such as TSP that improves transit service and increases ridership and fare box revenue. Generally, this project focused on the external benefits of improved service so as not to duplicate the findings of prior NCHRP research and because the magnitude of aggregated external benefits is greater and can potentially support a stronger business case for CV infrastructure investment. External benefits can be further categorized as location-specific or network-wide. • Location-specific benefits depend on installing CV infrastructure in specific locations and at a scale based on the number of equipped system users who receive the information communicated from that location (e.g., often a warning message that could be related to a sharp curve, or a stop sign, or an icy road condition). V2I applications that provide location-specific benefits focus predominantly on safety and mobility benefits. • Network-wide benefits require a threshold number of CV infrastructure installation locations along a corridor (e.g., a set of signals), along a set of interconnected corridors, or across a region. Often a critical number of equipped system users (CVs or AVs) are also necessary for the V2I application to deliver the benefits. In addition, network

25 benefits depend on combining information about the connected vehicle (speed, heading, and location) with other network information in DOT control (e.g., signal phase and timing (SPaT), traffic probes, or work zone or special event information). Information collected from and transmitted to CVs passes through a centralized or regional hub (e.g., a TMC) that aggregates and processes information from multiple systems in real-time (for time-critical applications) or near real-time. Network benefits contrast with location- specific benefits that accrue to individually equipped vehicles and do not require information about other vehicles’ performance characteristics. V2I applications that provide network-wide benefits largely offer mobility and environmental benefits. Observations on V2I Application Benefits The research team further analyzed the filtered V2I applications for the types of benefits they provide as introduced in the previous section. Table 4 indicates the types of external and internal benefits that the more than 30 individual applications and 2 DMA program bundles provide and identifies whether those benefits are primary (P) or secondary (S). The table also indicates whether the external benefits are location-specific or network-wide. In addition, some of these applications require real-time information exchanges with minimal latency to serve either safety of life (safety-critical) or dynamic mobility (time-critical) applications, as indicated in the last column of Table 4. The criticality of communications refers to the speed with which information is wirelessly exchanged between CVs or AVs and RSUs integrated with traffic control systems (e.g., signal controllers) and backhaul connections to TMCs. Some of the safety--critical V2I applications require high-speed, reliable, low-latency communications such as those provided by DSRC or C-V2X. These V2I applications strongly depend on CV infrastructure investments from DOTs as they relate to RSUs, central hub, network data management, and telecommunications infrastructure. They are some of the more expensive applications to deploy but, in return, offer the greatest benefit by saving lives and time. Time-critical applications also need high-speed communications, but the latency requirements are less stringent (by at least an order of magnitude). While V2I applications that are not time- or safety-critical (e.g., TSP) do not need high-speed, low-latency information exchanges, they will benefit from such communications infrastructure and the supporting CV environment, if available. For example, TSP applications benefit from any DSRC/C-V2X infrastructure deployed in conjunction with SPaT/MAP message broadcasts because of resulting direct device-to-device communications improves the reliability of the application.

26 Table 4. V2I Applications Requiring CV Infrastructure Investment V2I Applications External Benefits Internal Benefits Benefit Type Criticality of Wireless Commu- nications Mobility Safety Enviro. User Cost Avoid Agency Cost Avoid Improved Asset/ Fleet Mgt Revenue Source Curve Speed Warning P S Loc Safety Eco-Ramp Metering P P S Net Time Eco-Traffic Signal Timing P P S Net Time Electronic Toll Collection P P Loc - Emergency Vehicle Preemption P Net - Freight Drayage Optimization P S S Net - Freight Signal Priority (Also Eco-App) P P S Net - Incident Scene Work Zone Alerts for Drivers and Workers P S S Loc Safety Intelligent Traffic Signal System P S S Net Time Intermittent Bus Lanes P Net Time In-vehicle Signage P Loc Time Low Emissions Zone Management P Net - Mobile Accessible Pedestrian Signal System P Net Safety OVW S P S Loc - Pedestrian in Signalized Crosswalk Warning P Loc Safety Probe-based Vehicle Data for Traffic Operations S P Net - Queue Warning P S S Loc - Railroad Crossing Violation Warning P S Loc Safety Red Light Violation Warning P S Loc Safety Reduced Speed Zone Warning S P S Loc -

27 Table 4. V2I Applications Requiring CV Infrastructure Investment V2I Applications External Benefits Internal Benefits Benefit Type Criticality of Wireless Commu- nications Mobility Safety Enviro. User Cost Avoid Agency Cost Avoid Improved Asset/ Fleet Mgt Revenue Source Restricted Lane Warnings P S S Loc - Road Use Charging S P Loc - Road Weather Motorist Alert and Warning (and Freight) P S Loc - Roadside Lighting P S S S Net - Smart Parking (Travel Info, Eco Application, Park-and-Ride) P P S Loc - Smart Roadside Initiative (Electronic Safety Screening) P P S Loc - Speed Harmonization P S S Net Time Stop Sign Gap Assist P Loc Safety Transit Signal Priority (Also Eco-App) P P S S S S Net - Transit Stop Request P Loc - Transit Vehicle at Station/Stop Warning P Loc Safety V2I Application DMA Bundles* Intelligent Network Flow Optimization (INFLO) P S S S Net Time Multi-Modal Intelligent Traffic Signal Systems (MMITSS) P P P S S S S Net Both Notes: P = Primary Benefit; S = Secondary Benefit Enviro. = Environmental Mitigation; User Cost Avoid = User Cost Avoidance; Agency Cost Avoid = Agency Cost Avoidance; Improved Asset/Fleet Mgt = Improved Asset/Fleet Management; Benefit Type refers to location-specific (Loc) or network-wide benefits (Net); Comms Critical = Communications Criticality: Time-critical or Safety-critical; DMA = USDOT ITS JPO Dynamic Mobility Applications Program; * INFLO includes Q-WARN, SPD-HARM, and cooperative adaptive cruise control, which depends on a high-level of equipped vehicles; MMITSS includes EVP, FSP, I-SIG, PED-SIG, and TSP

28 A sequence of logical observations on the individual applications in Table 4 can help DOTs prioritize applications and identify those for which a business case may be made for investment beyond pilots and small-scale deployments. • While it is commonly understood that V2V applications address many of the safety- related benefits CVs offer, there is a substantial subset of V2I applications that provide safety benefits beyond what V2V can accomplish. Of the individual applications in Table 4, 11 (35 percent) indicate safety as a primary benefit, including RLVW, RSZW (to include work zones), RCVW, Stop Sign Gap Assist, PED-SIG, OVW, PSCW, Roadside Lighting, and Transit Vehicle at Station/Stop Warning. • Beyond safety, a significant number of V2I applications provide greater mobility benefits than those afforded by traditional ITS and vehicle sensor or V2V-enabled solutions. Of the applications in Table 4, 17 (55 percent) indicate mobility as a primary benefit: Eco- Ramp Metering, Eco-Traffic Signal Timing, Electronic Toll Collection, EVP, Freight Drayage Optimization, FSP, INC-ZONE, I-SIG, Intermittent Bus Lanes, Q-WARN, Restricted Lanes Warning (to include work zones), Road Weather Motorist Alert and Warning, Smart Parking, Smart Roadside Initiative, SPD-HARM, TSP, and Transit Stop Request. Both the INFLO and MMITSS bundles comprise these kinds of applications. • Many of these safety and mobility benefits are enabled by combining information about the performance of the transportation network with individual vehicle information. This observation is also supported by other research. A European study (Asselin-Miller et al., 2016) concluded that reduced travel times as a result of increased network efficiency was the dominant contributor to the overall benefits accrued from V2I (or C-ITS as it is referred to in Europe) deployments. The study reported that mobility benefits outweighed the safety-related benefits from V2I deployments by 3:1. Together, the combination of system performance and individual CV information allows agencies and travelers to make better decisions about how to operate and travel on the system, respectively. This knowledge would not be feasible without the network level information processed by the V2I application. Among the applications in Table 4, nearly one-half (42 percent) are network oriented, most of which (35 percent of the total) provide primary safety and/or mobility benefits. Examples include TSP and timing applications and SPD-HARM. • Finally, most of the safety and mobility benefits achievable through network applications are time- or safety-critical, meaning they rely on high-speed, low-latency communications, like those offered by DSRC and C-V2X. However, other entities (e.g., regulatory agencies and private companies) control the communication technologies and vehicles that include the technology that enables time- or safety-critical communication technology. In addition, many other applications that provide location-specific benefits also require this type of communication. CV Infrastructure Investment Value Proposition Because DOTs are responsible for transportation system networks, agencies have a motivation, and indeed, obligation, to make investments that realize greater safety and mobility benefits, in

29 line with their missions—provided the costs are affordable and justified given other investment alternatives and risks. Considering the sequence of observations on V2I application benefits as a whole, it follows that there is an important subset of V2I applications that (1) provide safety and mobility benefits to DOT users, (2) require DOT-provided network performance or usage information to enable, and (3) rely on time- or safety-critical communication infrastructure. DOTs interested in availing these benefits are in a unique position to shortlist and prioritize the applications of interest and to examine the investments to be made in CV infrastructure that support these applications. V2I APPLICATION DEPLOYMENT READINESS The previous section established a clear set of benefits for V2I applications, along with a value proposition for V2I application deployment and investment in CV infrastructure by DOTs. The research team next analyzed the readiness of V2I applications for real-world deployment by examining the CV infrastructure components required for any given V2I application and assessing their readiness and impact on CV infrastructure investment decision-making. The research team also analyzed readiness by examining a current set of DOT pilot projects, test bed activities, and plans. These observations on current and planned deployments by DOTs provide a real-world indication of what V2I applications are feasible (or “ready”), and indeed, are considered worthy of investment by agencies today. Assessing Readiness by CV Infrastructure Component Deployment readiness of an application or a set of applications depends on the availability of various components of the CV infrastructure environment required to support them. Figure 4 depicts CV infrastructure components and their relationships. Table 5 presents the key CV infrastructure components necessary to enable V2I applications, their current state of readiness, and their impact on CV infrastructure investment decision-making within the 5- to 10-year time frame of this study. The table organizes the CV infrastructure components by (1) roadside systems, (2) other ITS equipment, (3) in-vehicle systems, (4) communications, and (5) support systems.

30 Source: CAT Coalition 2020a Figure 4. Connected Vehicle Deployment Environment

31 Table 5. CV Infrastructure Components, their Readiness Assessment and Impact on CV Infrastructure Investment Decision-making Key CV Infrastructure Component Readiness Level Observations Assessment of Impact on CV Infrastructure Decision-making in a 5- to 10-year Time Frame • Roadside Systems RSU radio transceiver technology for wireless communications with vehicles • DSRC-based RSUs that are brought into vehicles (as opposed to natively installed in vehicles by OEMs) field-tested and ready for deployment. • Dual channel RSUs that support DSRC and C-V2X are emerging but not fully tested. Safety- and time-critical V2I applications can be designed and implemented using DSRC technology today. Any investments made in RSUs using DSRC technology may be at risk and will need to be replaced. ASSESSMENT: A reasonable path forward would be to understand the cost impacts of DSRC-based RSU depreciation based on an expected timeframe for market penetration of equipped vehicles with alternate technologies. These costs can then be considered as part of the financial analysis. A 10-year lifetime for RSUs is reasonable to assume. Another important consideration is to ensure that the deployed radio technology of today can be cost effectively swapped as alternate technology emerges. Traffic Signal Controllers (for signalized intersection applications) • Commercial equipment available to support the necessary information exchanges—SPaT messages and storing the intersection geometry information. • Message sets exist based on DSRC technology. Allows signalized intersection applications to be considered for CV infrastructure investments.

32 Table 5. CV Infrastructure Components, their Readiness Assessment and Impact on CV Infrastructure Investment Decision-making Key CV Infrastructure Component Readiness Level Observations Assessment of Impact on CV Infrastructure Decision-making in a 5- to 10-year Time Frame Network interface devices to receive and transmit information via backhaul communications to the TMCs and back office systems • Generally ready, however, IP version 6 (IPv6) upgrades to the backhaul network might alleviate challenges related to implementing a SCMS. • Systemwide analysis and upgrades may be needed to improve performance and support of CV related features. Permits connections between roadside systems and other ITS network and TMC support systems. ASSESSMENT: An investment to modernize and upgrade related infrastructure will improve performance of network interface devices and must be considered as part of the costs of CV deployments. CV information message sets, i.e., the standard messages that must be exchanged between vehicles and between vehicles and infrastructure • The message sets, their data frames and data elements are defined by the SAE J2735 standard intended to be used with DSRC deployments. Examples of relevant V2I messages include, the Basic Safety Message, SPaT, Intersection Geometry (MAP), Traveler Information Message (TIM), Signal Request Message (SRM), and Signal Status Message (SSM). • Equivalent C-V2X standards are also emerging but are not yet available. Data exchanges are defined adequately for V2I applications in current or planned use. Wireless communication technology choice is not expected to have an impact on this component. • Other ITS Equipment Other ITS equipment necessary to enable certain applications. Examples include traffic sensors, pedestrian sensors, and environmental sensing stations • Commercial equipment available to provide the necessary inputs to V2I applications. Equipment is readily available and only requires integration other equipment such as a traffic controller or connection directly to a network interface device. • In-Vehicle Systems OBUs (integrated or brought in) and ASDs • In-vehicle OBUs that are built-in by OEMs do not exist in private autos today except for a few purpose-built vehicles. The lack of suitably equipped vehicles from OEMs delay DOT investment decisions.

33 Table 5. CV Infrastructure Components, their Readiness Assessment and Impact on CV Infrastructure Investment Decision-making Key CV Infrastructure Component Readiness Level Observations Assessment of Impact on CV Infrastructure Decision-making in a 5- to 10-year Time Frame • ASDs or OBUs brought into the vehicle are available. • Standards for information exchange do not exist except for the Basic Safety Message. OBUs that can be brought into the vehicle or ASDs can be used on a limited basis for V2I applications that support fleet operations, but they are expensive. ASSESSMENT: A reasonable path forward could include focusing on time-critical mobility applications involving DOT fleet vehicles into which OBUs can be installed. If technology changes over time, these costs will need to be replaced and depreciated as part of a financial plan. • Backhaul Communications Backhaul communications that fulfill the bidirectional broadband communications between RSUs and vehicles OBUs and from the TMC to the roadside, using wired (e.g., optical fiber) or wireless communication technologies (e.g., satellite) • The backhaul communication network to support a SCMS needs to be IPv6 compatible. • For a large number of wireless devices to connect to the backhaul network, IPv6 will eventually be needed because IPv4 will not be able to handle the addressing demand at a certain point. Significant investments may be needed to install and/or upgrade backhaul networks to IPv6 at least in areas or regions where V2I time-critical applications are being deployed. This is a large upfront cost to agencies. • Support Systems Security Credential Management System that ensures that messages from OBUs and RSUs can be trusted • Proof of concept SCMS solutions exist today that are operating in coordination with USDOT for implementation today. More guidance will need to be developed on how vehicles will be enrolled by a SCMS certification authority. ASSESSMENT: National SCMS guidance is near-at-hand and is not expected to affect short- term CV investments.

34 Table 5. CV Infrastructure Components, their Readiness Assessment and Impact on CV Infrastructure Investment Decision-making Key CV Infrastructure Component Readiness Level Observations Assessment of Impact on CV Infrastructure Decision-making in a 5- to 10-year Time Frame CV Back Office System, which as part of the set of TMC ITS Systems, supports CVs and related applications by accessing data from DOT sources, generating and signing messages for security purposes, and accepting and managing data received from CVs and related processes like over-the- air download management. Its functions can also include data management to support information message sets and CV roadside infrastructure management. • This key system is still being perfected at early deployment agencies. The level of readiness required for field operations is low because few large-scale deployments exist. Significant investments need to be made in this area by DOTs and their regions to prepare for a CV future. The architectures for security and data management and processes will need to be developed. These costs need to be considered in investment decision-making. Availability of open-source software for V2I applications • Open-source software support exists for the following commonly deployed V2I applications: RCVW, CSW, RLVW, Eco-Approach and Departure at Signalized Intersection, Q-WARN, SPD-HRM, SWIW, MMITSS (TSP, FSP, EVP, PED-SIG). DOTs can begin leveraging open-source software to deploy applications for which software exists. Investments will need to be made by applications that are unsupported. ASSESSMENT: DOTs can prioritize time- and safety-critical applications for which software exists but will have to consider further development to adapt the software to their systems.

35 Observations on the assessments presented in Table 5 will be used in chapter 3 to construct a decision-making rationale that considers the uncertainties complicating a clear path forward, including selection and availability of communication technology and market availability of equipped vehicles. These uncertainties will influence DOTs’ logical selection and prioritization of V2I applications along several investment pathways. However, examining the table’s assessments in total, it is clear that the readiness of key infrastructure components outside communication technology selection and widespread availability of OBU-equipped vehicles indicates few obstacles to making targeted investments in V2I applications today. This conclusion is further supported by examining the investments DOTs are actually making across current pilot programs, test bed activities, and projects. Assessing Readiness of V2I Applications Based on Department of Transportation Pilot and Test Bed Activities and Plans The previous section assessed CV infrastructure readiness based on observed technology trends across the necessary components that enable V2I applications. This section adds to those findings by assessing the readiness of V2I applications based on the existing set of DOT pilot, test bed, and early deployment activities. When combined with statements of intent made in DOT CV planning documents, several of which were presented in chapter 1 (Table 1), this information indicates which applications DOTs consider ready today (pilots, test beds, and early deployments) and which applications they see being ready in the near future (planning documents). The planning documents also indicate a commitment to invest in CV infrastructure and provide evidence that such investments are not only ready to be made, but are worthwhile— and if large enough, in need of business case support. Table 6 lists 30 of the most advanced and extensive CV infrastructure investment pilots, test beds, and projects among DOTs across the country. Figure 5 orders the totals of each V2I application deployed, in active deployment, or seriously contemplated for deployment in the near term using the existing or stated CV infrastructure investment represented in these DOT activities. This graph indicates current priorities and perceived readiness of V2I applications among those agencies currently investing in CV infrastructure. Table 6. Existing V2I Applications – Deployed or Deploying Pilot, Test Bed, or Project Scope of CV Infrastructure AZ Anthem Test Bed, Maricopa County 11 intersections (expanding to I-17 planned) AZ ADOT/MCDOT MC-85 19 intersections AZ ADOT Loop 101 Mobility Project (ATCMTD) 61-mile loop CA Palo Alto Test Bed 7-mile corridor, 31 intersections CO CDOT I-70 Mtn. Cor. 100 RSUs CO Denver Smart City (ATCMTD) Connected TMC - 1,500 city vehicles, “Connected Freight” and “Connected Citizens” FL Tampa Hillsborough Expressway Authority (THEA) USDOT CV Pilot 40 RSUs, 1,600 cars, 20 transit vehicles, 500 pedestrians

36 Table 6. Existing V2I Applications – Deployed or Deploying Pilot, Test Bed, or Project Scope of CV Infrastructure FL FDOT US 90 Tallahassee 21 intersections, 4 OBUs FL FDOT Gainesville SPaT Trapezium 50 RSUs, 7-mile corridor FL FDOT I-75 Florida's Regional Advanced Mobility Elements (FRAME) 75-mile corridor, 93 intersections, 35 ITS locations FL FDOT SR 434 CV Deployment 8 RSUs GA Atlanta Region CV Deployment 654 RSUs (1,700 planned), 53 OBUs MD MDSHA US1 Howard County 20 intersections MI SE Michigan Test Bed 125-mile corridor, 115 RSUs MI Ann Arbor Test Environment (UMTRI) City-wide, 74 RSUs, 2,650 OBUs MI MDOT RSUs in Southeast Michigan Various deployments (I-275, I-94, M-53, M-43) MN MN Connected Corridor (Hwy 55) 22 signals NV Las Vegas Innovation District 6 intersections NC NCDOT NC 55 20+ intersections NY NYCDOT USDOT CV Pilot 3 city regions, 8,000 vehicles, 100 pedestrians OH Columbus USDOT Smart City 100 RSUs, 1,800 OBUs OH ODOT US-33 Smart Mobility + Connected Marysville 27 intersections in Marysville (94 RSUs total including US 33), fiber, 500 OBUs UT UDOT/UTA MMITSS - Redwood Rd bus 11-mile corridor with 24 intersections, 10 buses UT UDOT/UTA MMITSS - Provo-Orem UVX BRT 47 intersections, 25 buses UT UDOT snowplow priority 5 corridors, 55 intersections, 46 snowplows UT UDOT-Panasonic CV expansion 200 RSUs, 2,000 OBUs (5-year plan) VA VDOT NoVa Test Bed 65 RSUs, 72 OBUs, 50 light vehicles, 5 safety service patrol vehicles WA Washington State DOT (WSDOT) (US 2 Spokane, SR 522 cor., SR 305, SR 500) 24 intersections WI Madison Park Street Connected Corridor 20-30 intersections WY WYDOT USDOT CV Pilot 400-mile corridor, 75 RSUs, 400 OBUs

37 TSP = Transit Signal Priority; PED-SIG = Mobile Accessible Pedestrian Signal System; RLVW = Red Light Violation Warning; FSP = Freight Signal Priority; EVP = Emergency Vehicle Preemption; RSZW = Reduced Speed Zone Warning; I-SIG = Intelligent Traffic Signal System; CSW = Curve Speed Warning; SWIW = Spot Weather Impact Warning; Q-WARN = Queue Warning; INC-ZONE = Incident Scene Work Zone Alerts for Drivers and Workers; ATIS = Advanced Traveler Information System; PSCW = Pedestrian in Signalized Crosswalk Warning; RW alert = Road Weather Motorist Alert and Warning; SPP = Snowplow Priority; SPD-HARM = Speed Harmonization; VDTO = Vehicle Data for Traffic Operations; RCVW = Railroad Crossing Violation Warning; Eco-App/Dep = Eco-Approach and Departure at Signalized Intersections; IBL = Intermittent Bus Lane; RZW = Restricted Zone Warning; IVS = In-vehicle Signage; Eco-TST = Eco-Traffic Signal Timing Figure 5. Existing V2I Applications Deployed or Deploying, by Number While the popularity of an application does not mean it is ready to be deployed at scale immediately, it does indicate the level of interest among DOTs to study it and document its benefits. From this standpoint, the applications in Figure 5 illustrate the viability of certain priority V2I applications. Key observations from Figure 5 related to V2I priority applications are: • The top five applications in terms of popularity target signalized intersections; TSP is the application with the most interest. • Seven of the top 10 popular applications use DOT-provisioned network data (SPaT, weather, work zones, traffic volumes of non-CVs) to deliver benefits. 0 2 4 6 8 10 12 14 TSP PED-SIG RLVW FSP EVP RSZW I-SIG CSW SWIW Q-WARN INC-ZONE ATIS PSCW RW alert SPP SPD-HARM VDTO RCVW Eco App/Dep IBL RZW IVS Eco TST No. of Deployments

38 • Only four of the top 10 popular applications require safety-critical communications provided by DSRC; the remainder of the applications are mobility focused and do not need DSRC equipment. However, DOTs are testing these mobility applications in a DSRC CV environment. • An overwhelming majority of the applications are focused on mobility-related benefits. These observations align with the assessment of CV infrastructure decision-making presented in Table 5. The focus on applications for signalized intersections reflects the availability of traffic signal controllers that support the necessary information exchanges (SPaT and MAP messages) to enable mobility-related applications that prioritize certain vehicles’ use or increase the efficiency of signalized intersections. Many of these applications also benefit public fleets, such as transit and maintenance vehicles, that can be retrofitted with the necessary on-board technology absent any OEM-supplied equipment. Deployed applications also have largely taken advantage of the availability of open-source software. Nonetheless, DOTs are also exploring safety- and time-critical applications that either depend on a significant number of equipped private vehicles or the future development of V2I application software to build on initial investments and deployment outcomes and eventual increases in market penetration. Several applications are active and are providing benefits to the agency or system users, or at the very least are demonstrating the feasibility of the application and the likelihood of benefit given broader infrastructure deployment, further V2I application development, or a greater threshold number of equipped users. This observation is supported by looking more closely at the status of several deployments in Table 6. Table 7 highlights several pilots or projects that indicate V2I applications of interest to DOTs that may be targeted for widespread deployment and investment in CV infrastructure. The readiness of certain V2I applications as reflected in pilot and small-scale projects, alongside agencies’ commitment to aggressively expand on these early deployments as reflected in planning documents, suggests that developing a business case to support the significant investment required in CV infrastructure would help agencies realize this commitment.

39 Table 7. Select Active V2I Application Deployments Agency Deployed Project and V2I Applications UDOT • 11-mile Redwood Road bus corridor, 24 intersections and 10 buses equipped with TSP • Active since November 2017 • Providing up to a 6 percent improvement in schedule reliability • Provo-Orem UVX BRT corridor, 47 intersections and 25 buses equipped with TSP • Active since December 2018 • Benefit study underway • 5 Salt Lake Valley corridors, 55 intersections, and 46 snowplows equipped with snowplow priority • Active since March 2019 • Benefit study underway Maricopa County DOT • 11-intersection test bed in Anthem, Arizona, with implementation of the full suite of MMITSS applications • Successful pilot tests of pilot test EVP, TSP, FSP, and pedestrian signal priority with equipped school buses, transit buses, and emergency vehicles • Expansion to the adjacent I-17 and to equipping Anthem residents’ vehicles and public agency vehicles with OBUs FDOT • SPaT equipment (SPaT and MAP broadcasts) installed at 21 signalized intersections along US 90 in Tallahassee, along with integration with CV and AV-ready traffic controllers • FDOT fleet vehicles equipped with portable OBUs • Active since March 2018 • Gainesville SPaT Trapezium installed SPaT equipment at 27 signalized intersections Deploying pedestrian and bicyclist safety applications for both web-based and/or Smartphone-based applications • Active since September 2019 • Integrated Corridor Management solution along I-75 and state highways between Gainesville and Ocala, incorporating TSP, FSP, INC-ZONE, RCVW • In design as of May 2020 CONNECTED VEHICLE INFRASTRUCTURE COSTS The previous sections identified V2I applications of interest and their benefits and then assessed the readiness of the required CV infrastructure components to implement them. Investment decision-making also requires an understanding of cost. The scale of investment can be estimated on an application-by-application basis by identifying and costing the CV components that must be provided or upgraded. To understand these costs, the research team identified a set of cost categories and components within them and collected real-world cost data from current DOT pilots, test beds, and project investments. The research team also applied expert judgment on individual components’ cost share. This supplementary analysis was performed to balance any ambiguity in available data as a result of the opportunistic nature of the projects investigated and to understand the degree to which the most at-risk cost components contribute to the overall cost

40 of investment. The team used these findings to begin to ascertain feasible investment pathways in the face of uncertainty. Connected Vehicle Infrastructure Investment Cost Categories The research team reviewed research literature and project documents related to DOT V2I application deployments to develop a set of CV infrastructure cost categories and components with which to collect, organize, and analyze cost data. For example, Parikh et al. (2019) identify the following set of cost categories to estimate rough order of magnitude cost ranges for a number of V2I applications: • Equipment costs (hardware purchase) • Installation/Deployment costs (in the field or at a TMC, comprising both labor and training costs) • Software and integration costs (commercial software purchase or custom software development plus integration with existing systems) • Operations and maintenance (comprising both labor and training) • Backhaul fiber (for select safety- or time-critical applications) After applying its expert judgment, the research team settled on a set of cost categories and components with additional granularity and specificity to better capture actual cost data from existing deployments. Table 8 presents this set of cost categories, along with some explanatory notes or examples.

41 Table 8. CV Infrastructure Cost Categories Cost Category / Component Note / Examples Roadside Units / Roadside Equipment – Hardware Consider inclusion of RSU, mounting hardware, cabling, connection to traffic signal/ITS cabinet. Can also include cost of network interface devices (modem/switches). – Design, Deployment, Integration, Testing Signal Controller Upgrade To enable SPaT messages Other ITS Equipment For example, weather sensors, surveillance/detection equipment for traffic and pedestrians OBUs / On-board Equipment Presumed to be a cost borne by the user sometime in the future (i.e., provided as standard OEM equipment) but often a significant cost for current pilots and early deployments that provide units to pilot participants. This is also a cost for early investments in applications for public fleet vehicles (transit, maintenance). – Hardware – Design, Deployment, Integration, Testing Backhaul Network – Fiber Optic Cable (design, ROW, installation) As necessary, usually existing or considered part of a separate “project” – IPv6 Upgrade – Security Credential Management System Back Office / TMC – Servers, Data Storage, Device/Systems Monitoring Necessary expansion and upgrade within a central monitoring location – Data For example, third-party data purchase CV Application Development – CV Application Systems Engineering and Development Development of the application(s) itself, such as SPD-HARM; open-source platforms exist for some applications but likely require adaptation to a specific DOT’s context.

42 Table 8. CV Infrastructure Cost Categories Cost Category / Component Note / Examples – CV Platform / Analytics Systems Engineering and Development Application-specific platform to manage its use in the field and analyze and make operational decisions based on real-time conditions if necessary. – Back Office Provisioning of J2735 (DSRC) or 5G Messages to Application All deployments to date have used DSRC communication. Other Costs Not exhaustive and potentially incorporated among other costs above and difficult to specifically identify. Provided as an option to the user. – ITS Architecture Update – ITS Standards Update – Workforce Addition / Training – Industry-wide CV Standards Committee Participation – Program Management Ongoing System Operations and Maintenance Post-deployment recurring costs

43 Connected Vehicle Infrastructure Investment Cost Data The research team collected CV infrastructure cost data from available pilot studies, test bed activities, and deployments. First, the team compiled a comprehensive “long list” of existing and planned deployments, focused on the United States, with some consideration of international initiatives. These data are presented in Appendix A. From this comprehensive list, the research team identified 26 deployments sufficiently advanced for a more detailed review of costs, as indicated by the column in Table A.1 labeled “Explore for Cost Info.” These deployments include SPaT challenge sites, USDOT pilots, and some state DOT pilots. This subset of projects totaled 20 distinct agencies (states, municipalities, or academic institutions) to contact for cost information. The research team ultimately contacted 17 of these 20 sites and received information from 10. Table 9 presents a summary of these deployments, indicating the scope of infrastructure deployed and what CV applications are in place or planned, as well as contextual information about whether the project is a pilot or test bed. Appendix B summarizes the data collected from the 10 sites. Because most of these deployments are pilots or test beds, cost data are best presented with deployment-specific context to understand, for example, the variability in the cost ranges, why a cost component may not apply to that project, or why a single component’s cost may be difficult to isolate from more aggregated expenditures. Costs by Individual CV Infrastructure Component and V2I Application The research team combined the data collected for this study with several other sources, including similar data available in the ITS JPO Costs and Benefits Databases (ITS JPO, 2020) and collected by Parikh et al. (2019). Table 10 organizes these data to present unit cost estimates for CV infrastructure. The cost categories and components have been reorganized based on the data collected and to align with those used in the readiness assessment.

44 Table 9. CV Deployment Projects Providing CV Infrastructure Cost Information Sponsor Project Scope Pilot/ Test Bed Builds on Prior Test/ Pilot/ Deployment Applications to be Deployed over Planning Horizon (Currently in Use)1 Ann Arbor, MI / UMTRI Ann Arbor CV Test Environment City-wide, 74 RSUs, 2,650 OBUs ✓ ✓ CSW, RLVW, pedestrian detection Columbus, OH Smart Columbus 100 RSUs, 1,800 OBUs VDTO, RLVW, EVP, RSZW, TSP, freight platoon, FSP Florida DOT Gainesville SPaT Trapezium 7-mile corridor, 50 RSUs ✓ ✓ SPaT, PED-SIG, PSCW Georgia DOT (GDOT) Atlanta Region CV Deployment 654 RSUs (1,700 planned), 53 OBUs ✓ Connected Eco-Driving, SPaT, RLVW, PSCW Maricopa County, AZ Anthem CV Test Bed 10+ miles, 11 RSUs ✓ ✓ I-SIG, TSP, PED-SIG, EVP, FSP Marysville, OH Connected Marysville (33 Smart Mobility Corridor) 27 intersections in Marysville (94 RSUs total including Route 33), 500 OBUs CSW, Q-WARN, Road Weather Motorist Alert and Warning, SPaT, RLVW, RCVW, RSZW, PED-SIG Minnesota DOT Connected Corridor (Hwy 55) 22 signals SPaT, Eco-Traffic Signal Timing, RSZW, TSP (snowplow), PED-SIG UDOT / Utah Transit Authority Provo-Orem UVX BRT 11-mile corridor with 47 RSUs/intersections, 25 OBUs ✓ SPaT, TSP, TSP (snowplow) Virginia DOT / VTTI Northern VA Connected Corridors Test Bed 65 RSUs, 72 OBUs, 50 light vehicles, 5 safety service patrol vehicles ✓ ✓ RSZW, SPaT, RLVW, Eco- App/Dep, EVP, TSP Wyoming DOT I-80 CV Pilot 400-mile corridor, 78 RSUs, 409 OBUs ✓ INC-ZONE, RSZW, Road Weather Motorist Alert and Warning, SWIW, ATIS, In- Vehicle Signage 1 Applications deemed to have low dependence on V2I (e.g., FCW) are not included.

45 Table 10. CV Infrastructure Component Unit Costs Equipment (per unit unless indicated otherwise) Design/Systems Engineering, Deployment, Integration, Testing Annual Operation and Maintenance Note Primary Source Roadside Systems RSU Hardware (RSU, mounting hardware, cabling, connection to traffic signal/ITS cabinet) $5,000 $5,000 $250 a - $1,000 - b Traffic Signal Controller $6,000– $11,000 $10,000 $850 Controller only a $1,000– $13,000 - - Low end – upgraded ancillary equipment in cabinet High end – new controller and network interface b Network Interface Devices (modem/switches) - - - Included in RSU hardware CV Information Message Sets - - - Included in V2I application development Other ITS Equipment Traffic Sensor (Microwave) $7,000– $10,000 $10,000 $280 a Pedestrian Sensor (Microwave) $400–$800 $800 $60 a Environmental Sensing Station $10,000– $35,000 $15,000 $2,250 a In-Vehicle Systems OBU Hardware (after market) $700– $2,500 $2,500 n/a Required for public fleet-based apps b Backhaul Communications Fiber Optic Cable Installation (urban region, per mile) $150,000– $200,000 - n/a b Fiber Optic Cable Installation (rural, $21,000– $55,000 - n/a a

46 Table 10. CV Infrastructure Component Unit Costs Equipment (per unit unless indicated otherwise) Design/Systems Engineering, Deployment, Integration, Testing Annual Operation and Maintenance Note Primary Source suburban regions, per mile) $100,000 - n/a b IPv6 Upgrade - - - Typically incorporated in other comms or network upgrades (e.g., backhaul or SCMS) Support Systems Security Credential Management System (SCMS) - - $15,000– $50,000 Assumed to be developed by others and purchased as a subscription on an annual basis (SaaS) b CV Back Office System $50,000–$800,000 n/a Varies considerably based on existing systems, application(s), and extent. Low end – 50 RSU SPaT deployment High end – small urban region test bed environment b V2I Application Software - $100,000– $200,000 10 percent maintenance, support, and enhancement per year Per discrete app. Projects may deploy multiple apps and net economies of scale a, b - $500,000 n/a UDOT modification of MMITSS software to implement TSP b a. Parikh et al., 2019 b. Data collection from NCHRP Project 20-102(12) To provide an alternative perspective on the magnitude of CV infrastructure investment, Table 11 summarizes rough order of magnitude cost ranges to deploy 10 V2I applications on a minimum deployment size basis, as estimated by Parikh et al. (2019). Nearly all the applications

47 tabulated are among the top considerations by DOTs as presented previously in Figure 5 and Table 9. These costs are sufficient to assess if a CV investment opportunity crosses a monetary threshold and warrants a more detailed business case analysis. Table 11. Rough Order of Magnitude Costs for Select V2I Investments V2I Application Minimum Deployment Size Initial Capital Cost Annual Operations and Maintenance Cost Curve Speed Warning (CSW) 1 location $110,000 $11,500 Pedestrian in Signalized Crosswalk Warning (PSCW) 1 intersection $120,000 $11,500 Railroad Crossing Violation Warning (RCVW) 1 intersection $11,500 $11,500 Red Light Violation Warning (RLVW) - hub architecture 10 intersections $230,000– $430,000 $11,500 Reduced Speed Zone Warning (RSZW) 1 location $110,000 $11,500 Incident Scene Work Zone Alerts for Drivers and Workers (INC- ZONE) 1 location $110,000 $11,500 Queue Warning (Q-WARN) 1 bottleneck $400,000 $43,000 Eco-Traffic Signal Timing/ - hub architecture Transit Signal Priority (TSP) 3 arterials (15 intersections) $280,000– $580,000 $16,500 Intelligent Traffic Signal System (I-SIG) 30 intersections $660,000– $1,060,000 $82,000 Speed Harmonization (SPD-HARM) 1 bottleneck $400,000 $43,000 Source: Parikh et al., 2019 Costs by Connected Vehicle Infrastructure Component Share As the cost data collection summary results of the previous section indicate, few deployments outside pilot projects and test beds currently exist with which to analyze costs. This reality tends to skew the data because of the opportunistic nature of these early deployments (e.g., capitalizing on available grant funding or existing investments in fiber backhaul infrastructure, or CV platform or application development by others such as a research effort by a university). Therefore, expert judgment is a necessary supplement to the data collected. Absent additional hard cost data, the research team determined the cost of CV infrastructure components as a function of a deployment requiring all identified cost components. Table 12 summarizes the results of the research team’s analysis of CV infrastructure component cost shares. As a point of validation, these cost shares were compared with those for the 10 projects (see Table 9) that provided cost data. Appendix C contains this comparison.

48 Table 12. Relative Costs of CV Infrastructure Investment Requirements – Expert Judgment Cost Component Cost Share Roadside Units 15% Signal Controller Upgrade 10% ITS Equipment – New or Upgrade 10% Backhaul Network 10% Back Office / TMC 14% CV Platform and Application Development 25% Other – CV Standards Committee Participation 2% Other – Program Management 13% Other - Training 1% The key takeaway from Table 12 is the cost of the RSUs—the most at-risk cost component because of uncertainty around communication technology—relative to the total cost of V2I application deployments is on the order of 15 percent if new backhaul communication infrastructure is required to support the RSUs. While proportional costs of system components are highly variable at this early stage of maturity, this analysis is intended to show, in general terms, that the relative cost of the RSU equipment (the system component with the greatest risk) is many times smaller than the total cost of implementing networked V2I applications. Several caveats must be noted about this analysis. First, it excludes the cost of OBUs, presuming that in the long run, they will be an external cost to a project, borne by the system user as a part of the purchase price of a new vehicle. In the near term, however, OBUs (or ASDs) are an expected cost among deployments involving public fleet connectivity. This share will be low, though, as OBUs generally cost half as much as RSUs, and fleet sizes generally number in the 10s or 100s (e.g., maintenance vehicles or buses) and therefore do not represent a sizeable or risky investment. The expert judgment analysis also assumes that the implementing DOT has made some ITS infrastructure investments in the past and is not “starting from scratch” in deploying communication equipment, TMC connectivity and systems, and other supportive sensors and devices. An “average” level of existing ITS infrastructure is assumed, upon which new systems or upgrades will be required, as captured by the “ITS equipment” cost component. Lastly, the cost categories are based on state DOT experience primarily using DSRC-based systems. Although there have been some pilot deployments of C-V2X-based applications, the implications of C-V2X—whether indirect V2I or network modes—on overall system costs are limited. Therefore, for this study, in the absence of better data, the total deployment cost categorization articulated in Table 12 holds for both C-V2X and DSRC. However, applications other than safety- and time-critical ones, where medium or low-latency communications speed

49 might be adequate, may be supported by 4G-LTE or 5G cellular communications in a network mode without RSUs and related backhaul costs. Conclusions on Connected Vehicle Infrastructure Costs Consistent with the conclusions drawn from the assessment of CV infrastructure component readiness, the cost share analysis supports identifying several investment pathways for DOTs to follow, despite uncertainty over wireless radio communication technology and the timing of a significant share of OBU-equipped vehicles on roadways. The cost share for RSUs is manageable for DOTs in the context of the full cost of investment, even if the communication technology becomes obsolete or is superseded. Moreover, as chapter 3 describes, certain “no regrets” investments can be made in technology agnostic components of V2I application deployment that do not come with those risks. In addition, applications focused on publicly equipped vehicles can be implemented absent market penetration of privately equipped vehicles. CHAPTER SUMMARY This chapter reviewed a series of issues that influence public agency decision-making on investing in CV infrastructure. The questions focused on whether public agencies need to make investments in CV infrastructure, and if so, what emerging and feasible V2I application candidates can be advanced to a formal business case analysis to aid with decision-making. These questions were addressed through an analysis of the types of V2I applications of interest, their benefits, states of readiness, and costs. This analysis relied largely on a combination of available literature, information gathered from pilot studies, and expert judgment. The set of applications documented in the CVRIA reveals emerging candidate V2I applications that DOTs should prioritize and plan for in the next 5 to 10 years and the benefits they can provide. The research identified a significant subset of V2I applications that provide safety and mobility benefits to DOT users, require DOT-provided network performance or usage information to enable, rely on the high-speed, low-latency communication provided by CV infrastructure, and lower dependence on V2V market penetration. DOTs interested in capitalizing on these benefits are in a unique position to shortlist and prioritize the applications of interest and to examine the investments to be made in CV infrastructure that support these applications. This chapter also established a range of potential benefits, both internal (agency) and external (societal), in terms of cost savings or avoidance, safety, mobility, environmental, and increased revenue. The types of external and internal benefits for more than 30 individual applications and 2 DMA program bundles were identified. Generally, safety- or time-critical V2I applications require high-speed, reliable, and low-latency communications and supporting infrastructure to enable real-time information exchange. Such applications are often more expensive but are also commensurate with expected benefits associated with saving lives and time, while those applications that are not safety- or time-critical may not need high-speed, low-latency information exchange. Making such investment decisions, however, requires understanding the V2I applications’ level of readiness for real-world deployment and the costs of doing so. The research examined the

50 readiness of CV infrastructure components required for any given V2I application alongside a current set of DOT pilot projects, test bed activities, and plans. It concluded that the readiness of key infrastructure components, outside communication technology selection and widespread availability of OBU-equipped vehicles, indicates few obstacles to making targeted investments in V2I applications today. This conclusion was further supported by the investments DOTs are actually making across current pilot programs, test bed activities, and projects. The chapter also identified a set of cost categories and components and then estimated their scale from real-world cost data as well as expert judgment on individual components’ cost share. These fundamental considerations have direct bearing on the need for a business case to support public agency investment in CV infrastructure and the decision-making process an agency would go through to advance investments for business case analysis. Both the readiness and cost assessments support identifying several investment pathways for DOTs to follow, despite uncertainty over wireless radio communication technology and the timing of a significant share of OBU-equipped vehicles on roadways. Chapter 3 will use these observations and assessments to construct a decision-making rationale that considers the uncertainties complicating a clear path forward, including selection and availability of communication technology and market availability of equipped vehicles. These uncertainties will influence DOTs’ logical selection and prioritization of V2I applications along several investment pathways.

Next: Chapter 3: Connected Vehicle Investment Decision Process and Options »
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State Departments of Transportation (DOTs) and other government agencies recognize the value of connected vehicle (CV) technologies in helping achieve the strategic objectives of saving lives and relieving congestion. Several agencies are currently planning and preparing for a future where CV technologies could become a part of their routine business operations. A core consideration in any such planning effort is an assessment of the need for and the nature of public CV infrastructure investments to support applications based on CV technologies.

The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 289: Business Models to Facilitate Deployment of Connected Vehicle Infrastructure to Support Automated Vehicle Operations presents methods to identify the most plausible CV infrastructure investments, shows how to build effective business case arguments, and details specific business model options during project procurement and delivery.

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