Transportation Planning for Connected Autonomous Vehicles: How It All Fits Together
Abstract
As connected and autonomous vehicle (CAV) technology continues to evolve and rapidly develop new capabilities, it is becoming increasingly important for transportation planners to consider the effects that these vehicles will have on the transportation network. It is evident that this trend has already started; over 60% of long-range transportation plans in the largest urban areas now include some discussion of CAVs, up from just 6% in 2015. There are also numerous CAV pilot programs currently underway that entail testing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) interaction in both isolated and real-world environments. In this review of the current assessments for CAV impacts, two primary trends are identified. First, there is a great deal of uncertainty that is not being explicitly considered and properly accounted for in the transportation-network planning process. Second, the predictions that are being made are not considering potential policy or planning actions that could shape or affect the impacts of CAVs. This paper provides a picture of how ongoing CAV research interacts with current transportation planning practices by examining how the methods, the ranges of predictions, and the different sources of uncertainty in each method impact the planning process and potential system outcomes. Finally, it will identify best practices from decision analysis to help plan the best possible future transportation networks.
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Developing and implementing ITS that enable AVs to interact with one another and with infrastructure features such as traffic lights, road sensors, and other vehicles can enhance overall traffic flow and safety.
“Developing and implementing ITS that enable AVs to interact with one another as well as with infrastructure features such as traffic lights, road sensors, and other vehicles can enhance overall traffic flow and safety [70].”
From Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature (2024) · cites this paper as [70]
AVs navigate and make choices using a variety of sensors and communication technologies.
“AVs navigate and make choices using a variety of sensors and communication technologies [70].”
From Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature (2024) · cites this paper as [70]
AVs have the potential to influence urban structure and development.
“AVs have the potential to influence urban structure and development [70].”
From Assessing the Role of Autonomous Vehicles in Urban Areas: A Systematic Review of Literature (2024) · cites this paper as [70]
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References 5 · Cited by 15
- Authors
- Cottam, B. J.
- Affiliations
- University of Arkansas at Fayetteville (US)
- Corresponding author
- Cottam, Bobby J.
- Venue
- Transportation Research Record: Journal of the Transportation Research Board
- Publisher
- SAGE Publications
- Published
- 2018-03-29
- Volume
- 2672
- Issue
- 51
- Pages
- 12-19
- ISSN
- 0361-1981 (ISSN-L)
- 2169-4052
- OpenAlex
- W2794760842
- Cited by
- 15
- References
- 5
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 5 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 1
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Record Journal of the Transportation Research Board (publishedVersion)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Keywords
- connected and autonomous vehicles, transportation planning, long-range transportation plan, vehicle-to-vehicle communication, vehicle-to-infrastructure communication, planning under uncertainty, transport network planning, decision analysis
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