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Can CAV Reduce Non-Recurrent Urban Road Congestion?

Authors :
Li, Yunkai
Li, Haotian
Martinez-Pastor, Beatriz
Wang, Shen
Publication Year :
2021

Abstract

A well-designed resilient and sustainable urban transportation system can recover quickly from the non-recurrent road congestion (NRC), which is often caused by en-route events (e.g., road closure due to car collisions). Existing solutions, such as on-board navigation systems and temporary rerouting road signs, are not effective due to delayed responses. Connected Autonomous Vehicles (CAV) can be helpful in improving recurrent traffic as they can autonomously adjust their speed according to their real-time surrounding traffic, sensed by vehicular communications. Preliminary simulation results in this short paper show that CAV can also improve traffic when non-recurrent congestion occurs. Other results in fuel consumption, CO2 emission, and traditional traffic safety indicators are open for future discussions.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2110.08507
Document Type :
Working Paper