Information Flow Topology in Mixed Traffic: A Comparative Study between "Looking Ahead" and "Looking Behind"

TL;DR

This study compares 'looking ahead' and 'looking behind' information flow strategies in mixed traffic with CAVs and HDVs, showing 'looking behind' enhances stability and larger platoons improve traffic flow.

Contribution

It introduces a dynamical modeling framework and a unified string stability analysis method for mixed traffic with different information flow topologies.

Findings

'Looking behind' topology outperforms 'looking ahead' in mitigating traffic perturbations.

Increasing maximum platoon size improves string stability.

Numerical results validate the effectiveness of 'looking behind' strategies.

Abstract

The emergence of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic where human-driven vehicles (HDVs) also exist, existing research mostly focuses on "looking ahead" (i.e., the CAVs receive information from preceding vehicles) strategies for CAVs, while recent work reveals that "looking behind" (i.e., the CAVs receive information from their rear vehicles) strategies might provide more possibilities for CAV longitudinal control. This paper presents a comparative study between these two types of information flow topology (IFT) from the string stability perspective, with the role of maximum platoon size (MPS) also under investigation. Precisely, we provide a dynamical modeling framework for the mixed platoon under the multi-predecessor-following (MPF) topology and the multi-successor-leading (MSL) topology. Then, a unified method for string stability analysis is presented, with explicit consideration of both IFT and MPS. Numerical results suggest that MSL ("looking behind") outperforms MPF ("looking ahead" ) in mitigating traffic perturbations. In addition, increasing MPS could further improve string stability of mixed traffic flow.