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Connected and automated vehicles (CAVs) provide various valuable and advanced services to manufacturers, owners, mobility service providers, and transportation authorities. As a result, a large number of CAV applications have been proposed to improve the safety, mobility, and sustainability of the transportation system. With the increasing connectivity and automation, cybersecurity of the connected and automated transportation system (CATS) has raised attention to the transportation community in recent years. Vulnerabilities in CAVs can lead to breakdowns in the transportation system and compromise safety (e.g., causing crashes), performance (e.g., increasing congestion and reducing capacity), and fairness (e.g., vehicles fooling traffic signals). This paper presents our perspective on CATS cybersecurity via surveying recent pertinent studies focusing on the transportation system level, ranging from individual and multiple vehicles to the traffic network (including infrastructure). It also highlights threat analysis and risk assessment (TARA) tools and evaluation platforms, particularly for analyzing the CATS cybersecurity problem. Finally, this paper will provide valuable insights into developing secure CAV applications and investigating remaining open cybersecurity challenges that must be addressed.
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Co-Benefits and Tradeoffs Between Safety, Mobility, and Environmental Impacts for Connected and Automated Vehicles
A large number of Connected and Automated Vehicle (CAV) applications are being designed, developed, and deployed in order to greatly improve our transportation systems in terms of safety, mobility, and reducing environmental impacts. These benefits can be quantified by a variety of performance measures that are often cited in the literature. However, most of these CAV applications are typically designed to improve transportation systems only in a particular dimension, usually focusing on either safety, mobility, or the environment. Very few research papers have considered a wider range or combination of performance measures across multiple dimensions, examining potential co-benefits or tradeoffs between these measures. For example, you can design a CAV application that greatly improves safety, but it might come at the cost of reducing traffic throughput. Further, the design of the CAV applications is often static and limited to specific traffic scenarios and conditions. CAVs that can adapt to different conditions, and be “tunable” for different societal needs will have much greater impact and versatility. In this presentation, we examine various co-benefits and tradeoffs of current CAV applications and consider how we can design these systems to have greater flexibility when it comes to deployment. We cite not only different CAV applications evaluated in simulation, but also real-world CAV deployments that operate on various testbeds, such as the Innovation Corridor located in Riverside, California. Based on this analysis, we can consider several new research directions for future CAV deployments.
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- Award ID(s):
- 2152258
- PAR ID:
- 10511097
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE Transactions on Intelligent Transportation Systems
- Volume:
- 25
- Issue:
- 4
- ISSN:
- 1524-9050
- Page Range / eLocation ID:
- 184 to 213
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/TITS.2024.3376869
