Abstract
Connected and autonomous vehicle (CAV) technologies are likely to be gradually implemented over time. In this paper, an adaptive cruise control, named Smart Driver Model (SDM), is proposed to describe the autonomous vehicles flow. The stability criteria is proposed for SDM to judge the stability of homogeneous traffic flow. Numerical simulations were conducted to verify the results of the theoretical analysis. Single-lane vehicle dynamics in a traffic stream with connected and autonomous vehicles are simulated by varying model parameters. Simulation results are consistent with the results of linear stability analysis. As a result, a set of parameters is proposed to investigate the stabilization effect of the proposed model on homogeneous traffic flow considering realistic driving cycle and cut-in condition. By simulating a platoon with a lead vehicle which follows the Urban Dynamometer Driving Schedule (UDDS), we find out that the proposed model can stabilize the traffic flow with proposed parameters. The results from simulation and linear stability analysis show that SDM outperforms the IDM-ACC and the ACC proposed by Milanés and Shladover in terms of stabilization effect on homogeneous traffic flow. The simulation result shows that the SDM-equipped vehicles are able to stabilize the homogeneous traffic flow under cut-in condition.
Highlights
Connected and autonomous vehicle (CAV) technologies have gained a lot of attention all over the world because of its potential in improving safety and congestion of the road transportation system
Existing rule-based adaptive cruise control (ACC) are based on three main headway selection policies: Constant Space-Headway (CSH), Constant Time-Headway (CTH) and Variable Time-Headway
When the traffic density is low (i.e. Δx is much larger than the desired spacing), Smart Driver Model (SDM)-equipped vehicles will accelerate to the maximum speed
Summary
Connected and autonomous vehicle (CAV) technologies have gained a lot of attention all over the world because of its potential in improving safety and congestion of the road transportation system. Davis [25] investigated the impact of mechanical response of the dynamics and string stability of a platoon of adaptive cruise control vehicles. Considering different models with the technology-appropriate assumption, Talebpour and Mahmassani [16] proposed a framework to investigate the impact of the connected and autonomous vehicle on traffic flow stability. Li et al [30] proposed an extended intelligent driver model and analyzed the stability against a small perturbation by use of the linear stability method for the proposed model on a single lane They found that the traffic flow stability can be improved by increasing the proportion of the direct power cooperation of the preceding vehicle. We propose a rule-based adaptive cruise control to improve the stability and behavior of Intelligent Driver Model [15].
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