Affiliation:
1. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada
2. Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan, Hubei, China
Abstract
Microscopic detail of complex vehicle interactions in mixed traffic, involving manual driving system (MDS) and automated driving system (ADS), is imperative in determining the extent of response by ADS vehicles in the connected automated vehicle (CAV) environment. In this context, this paper proposes a naïve microscopic car-following strategy for a mixed traffic stream in CAV settings and specified shifts in traffic mobility, safety, and environmental features. Additionally, this study explores the influences of platoon properties (i.e., intra-platoon headway, inter-platoon headway, and maximum platoon length) on traffic stream characteristics. Different combinations of MDS and ADS vehicles are simulated in order to understand the variations of improvements induced by ADS vehicles in a traffic stream. Simulation results reveal that grouping ADS vehicles at the front of traffic stream to apply Cooperative Adaptive Cruise Control (CACC) based car-following model will generate maximum mobility benefits for upstream vehicles. Both mobility and environmental improvements can be realized by forming long, closely spaced ADS vehicles at the cost of reduced safety. To achieve balanced mobility, safety, and environmental advantages from mixed traffic environment, dynamically optimized platoon configurations should be determined at varying traffic conditions and ADS market penetrations.
Funder
Natural Sciences and Engineering Research Council of Canada
Subject
Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering
Cited by
33 articles.
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