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Development of a Knowledge Base for Multiyear Infrastructure Planning for Connected and Automated Vehicles.
- Source :
- Journal of Transportation Engineering. Part A. Systems; Apr2022, Vol. 148 Issue 4, p1-24, 24p
- Publication Year :
- 2022
-
Abstract
- Connected and automated vehicles (CAVs) require proper infrastructure for safer and more reliable operations. Many state and local planning agencies have developed multiyear capital programs to provide such infrastructure in a timely manner within their limited budgets. Meanwhile, the traffic environment will evolve over time as CAV technologies become available (i.e., toward the mixed environment of CAVs and human-driven vehicles), which requires infrastructure plans specific to different planning terms (i.e., short-, medium-, and longterm) to accommodate changing infrastructure needs. To develop an effective multiyear infrastructure plan, planning agencies need to understand changing infrastructure needs with time, identify alternative infrastructure options for different planning terms, and select the most appropriate ones based on their long-term vision. This study performed a systematic literature review to develop a knowledge base for multiyear infrastructure planning for CAVs. To be more specific, the literature review aims to develop the following knowledge areas: (1) identification of existing and future infrastructure options for the operation of CAVs, (2) understanding the role of infrastructure to support different functions of CAVs to realize safety, mobility, and environmental benefits, and (3) integration of the aforementioned findings into planning agencies’ multiyear infrastructure plans for CAVs. Based on the review, this study categorizes different CAV infrastructure into existing infrastructure and future infrastructure options while considering five system functions of CAVs (i.e., cooperative merging, platooning, intersection movement, dynamic routing, and cooperation and connected functions) to illustrate the role of these infrastructure options under different traffic scenarios. The implementation of the developed knowledge base is demonstrated through a case study of two selected state agencies’ long-term infrastructure planning for CAVs. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 24732907
- Volume :
- 148
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Journal of Transportation Engineering. Part A. Systems
- Publication Type :
- Academic Journal
- Accession number :
- 155349655
- Full Text :
- https://doi.org/10.1061/JTEPBS.0000656