Abstract Connected Automated Vehicles (CAVs) bring promise of increasing traffic capacity and energy efficiency by forming platoons with short headways on the road. However at low CAV penetration, the capacity gain will be small because the CAVs that randomly enter the road will be sparsely distributed, diminishing the probability of forming long platoons. Many researchers propose to solve this issue by platoon organization strategies, where the CAVs search for other CAVs on the road and change lanes if necessary to form longer platoons. However, the current literature does not analyze a potential risk of platoon organization in disrupting the flow and reducing the capacity by inducing more lane changes. In this research, we use driving model of Cooperative Adaptive Cruise Control (CACC) vehicles and human-driven vehicles that are validated with field experiments and find that platoon organization can indeed drop the capacity with more lane changes. But when the traffic demand is well below capacity, platoon organization forms longer CAV platoons without reducing the flow. Based on this finding, we develop the Flow-Aware platoon organization strategy, where the CAVs perform platoon organization conditionally on the local traffic state, i.e., a low flow and a high speed. We simulate the Flow-Aware platoon organization on a realistic freeway network and show that the CAVs successfully form longer platoons, while ensuring a maximal traffic flow.

    Graphical abstract Display Omitted

    Highlights Connected Automated Vehicles (CAVs) promise to increase capacity by forming platoons. At low CAV penetration, the capacity gain will be small with few, short platoons. CAVs can change lanes to form platoons, but risk to disrupt flow and drop capacity. We propose a Flow-Aware strategy to form longer platoons with maximal traffic flow. We validate the Flow-Aware strategy by simulating traffic on a freeway network.


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    Title :

    Flow-aware platoon formation of Connected Automated Vehicles in a mixed traffic with human-driven vehicles


    Contributors:


    Publication date :

    2021-10-14




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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