Flow-Aware Platoon Formation of Connected Automated Vehicles

TL;DR

This paper introduces a flow-aware platoon formation strategy for connected automated vehicles that optimizes platoon length and traffic flow by considering local traffic conditions, addressing limitations of existing methods.

Contribution

It develops a novel conditional platoon organization strategy based on local traffic state, validated through simulations on realistic freeway networks.

Findings

Platoon organization can reduce capacity with many lane changes at high demand.

When demand is low, platoon organization increases platoon length without flow reduction.

Flow-aware strategy maintains maximal traffic flow while forming longer platoons.

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.