Mixed Traffic of Connected and Autonomous Vehicles and Human-Driven Vehicles: Traffic Evolution and Control using Spring-Mass-Damper System

Abstract

This paper sheds light on mixed-traffic dynamics considering the differences in driving characteristics, namely acceleration/deceleration rate, desired speed, and response time, between connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs). In light traffic, these differences were found to induce platoon formations, headed by vehicles with a lower acceleration rate and propensity not to exceed the desired speed (HDV in this study). Platoon formations lead to large inter-platoon spacing that can be utilized to accommodate cut-in vehicles. In a near-capacity condition, however, the differences in driving characteristics can induce voids and undermine traffic throughput when traffic is disturbed by merging vehicles. Based on these findings, a simple CAV control method is proposed based on the spring-mass-damper (SMD) system approach that directly considers the HDV behavior to mitigate disturbance propagation and throughput reduction. The main principle is to adjust the control parameters (lower spring coefficient and higher damping coefficient in the SMD control model) with an aim to control CAVs to absorb the cut-in impact (i.e., spacing shortage) before it reaches the first upstream HDV. A simulation experiment suggests the feasible region of the control parameters, subject to the recovery time, the number of controllable CAVs, and the cut-in impact.