Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams. FINAL REPORT

Hao Liu, Lin Xiao, Xingan David Kan, Steven E. Shladover, Xiao-Yun Lu, Meng Wang, Wouter Schakel and Bart van Arem

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: Freeway capacity and throughput can be significantly improved via CACC vehicle string operations. This research aims to provide authoritative predictions regarding impacts of CACC on traffic flow and quantitative estimations of the influences of CACC operation strategies that might create the capacity and throughput improvement in the freeway traffic stream. To this end, the PATH and Delft team have independently developed micro simulation platforms that represent the behaviors of CACC vehicles and their interactions with human drivers. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR-99 freeway near Sacramento, California for an 8-hour period in which the traffic fluctuated between free-flow and congested conditions. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. With the simulation platforms, we have explored the effects of CACC under various market penetrations and the impacts of a CACC managed lane (ML) strategy, a vehicle awareness device (VAD) strategy and discretionary lane change (DLC) restrictions on the traffic flow dynamics of a simple four-lane freeway section and the 13-mile freeway corridor.

Keywords: Engineering (search for similar items in EconPapers)
Date: 2018-05-17
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Citations: View citations in EconPapers (2)

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