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

Chapter: Appendix A: CV Infrastructure Cost Components Based on Expert Judgment

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Suggested Citation:"Appendix A: CV Infrastructure Cost Components Based on Expert Judgment." 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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Page 80
Page 81
Suggested Citation:"Appendix A: CV Infrastructure Cost Components Based on Expert Judgment." 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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Page 81

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68 CV INFRASTRUCTURE COST COMPONENTS BASED ON EXPERT JUDGMENT Too few deployments outside pilot studies, field operational trials, and proving grounds currently exist to analyze costs that would not be skewed by 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 proxy. The research team determined the cost of CV infrastructure components as a function of a deployment requiring all identified cost components. Table A-1 summarizes the results of the research team’s analysis of CV infrastructure component cost shares. The key takeaway from Table A-1 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 A-1 holds for both C-V2X and DSRC. However, applications other than safety- and time-critical ones, where medium or low-latency communications speed might be adequate, may be supported by 4G-LTE or 5G cellular communications in a network mode without RSUs and related backhaul costs.

69 Table A-1. 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%

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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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