Classification of Roadway Infrastructure and Collaborative Automated Driving System

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Authors Abstract
Content
The latest developments in vehicle-to-infrastructure (V2I) and vehicle-to-anything (V2X) technologies enable all the entities in the transportation system to communicate and collaborate to optimize transportation safety, mobility, and equity at the system level. On the other hand, the community of researchers and developers is becoming aware of the critical role of roadway infrastructure in realizing automated driving. In particular, intelligent infrastructure systems, which leverage modern sensors, artificial intelligence, and communication capabilities, can provide critical information and control support to connected and/or automated vehicles to fulfill functions that are infeasible for automated vehicles alone due to technical or cost considerations. However, there is limited research on formulating and standardizing the intelligence levels of road infrastructure to facilitate the development, as the SAE automated driving levels have done for automated vehicles. This article proposes a five-level intelligence definition for intelligent roadway infrastructure, namely, connected and automated highway (CAH). The CAH is a subsystem of the more extensive collaborative automated driving system (CADS), along with the connected automated vehicle (CAV) subsystem. Leveraging the intelligence definition of CAH, the intelligence definition for the CADS is also defined. Examples of how the CAH at different levels operates with the CAV in the CADS are also introduced to demonstrate the dynamic allocation of various automated driving tasks between different entities in the CADS.
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DOI
https://doi.org/10.4271/12-06-04-0026
Pages
10
Citation
Ran, B., Cheng, Y., Li, S., Li, H. et al., "Classification of Roadway Infrastructure and Collaborative Automated Driving System," Connected and Automated Vehicles 6(4):387-395, 2023, https://doi.org/10.4271/12-06-04-0026.
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Publisher
Published
May 9, 2023
Product Code
12-06-04-0026
Content Type
Journal Article
Language
English