Assessing the Impact of CAV Driving Strategies on Mixed Traffic on the Ring Road and Freeway

Abstract

The increasing traffic congestion has led to several negative consequences, with traffic oscillation being a major contributor to the problem. To mitigate traffic waves, the impact of the connected automated vehicles (CAVs) equipped with adaptive cruise control (ACC), FollowerStopper (FS), and jam-absorption driving (JAD) strategies on circular and linear scenarios have been evaluated. The manual vehicle is the intelligent driver model (IDM) and human driver model (HDM), respectively. The results suggest that on the ring road, the traffic performance of mixed traffic improves gradually with the increase of the proportion of CAVs under the ACC. Moreover, the traffic performance for the JAD strategy does not improve infinitely with the increase in the number of CAVs. Conversely, the FS strategy suppresses traffic waves at the cost of reducing traffic flow, and more CAVs are not beneficial for mixed traffic. It is interesting to note that under optimal performance in these three strategies, the FS strategy has the lowest number of CAVs, while the ACC strategy has the highest number of CAVs. For the linear road, it demonstrates that the JAD strategy exhibits a superior performance compared to the ACC. However, the FS strategy cannot dissipate traffic waves due to an insufficient buffer gap. Different models have varying effects on different strategies.

Simulating and Modelling the Safety Impact of Connected and Autonomous Vehicles in Mixed Traffic: Platoon Size, Sensor Error, and Path Choice

“…The second group includes studies that either perform a high-level simulation of CAVs [9] or focus on simulating only specific characteristics of CAVs, such as CAV platooning and CAV longitudinal control. For instance, Li et al [23] assessed the effects of three CAV driving strategies-adaptive cruise control, follower-stopper, and jam-absorption driving-on both ring roads and freeways in mixed traffic conditions. Hou [24] explored the impact of CAVs on traffic efficiency and safety in mixed traffic under varying weather conditions.…”

Molecular Dynamics-Based Car-Following Safety Characteristics and Modeling for Connected Autonomous Vehicles

“…The intelligent connected transportation system deeply integrates multi-dimensional elements, such as the human-vehicle-road-environment, resulting in heterogeneous vehicle group perceptions and interactions that present complex dynamic characteristics [1][2][3]. Therefore, systematically characterizing the intrinsic "self-driven particle" and the operating state evolution law of CAVS is crucial for ensuring the safety and stable operation of these vehicle groups [4].…”