Abstract
Connected and automated vehicle (CAV) technologies have great potential to improve road safety. However, an emerging type of mixed traffic flow with human-driven vehicles (HDVs) and CAVs has also arisen in recent years. To improve the overall safety of this mixed traffic flow, a novel car-following model is proposed to control the driving behaviors of the above two types of vehicles in a platoon from the perspective of a mechanical system, mass-spring-damper (MSD) system. Furthermore, a quantitative index is proposed by incorporating the psychological field theory into the MSD model. The errors of spacing and speed in the car-following processes can be expressed as the accumulation of the virtual total energy, and the magnitude of the energy is used to reflect the danger level of vehicles in the mixed platoon. At the same time, the optimization model of minimum total energy is solved under the constraints of vehicle dynamics and the mechanical characteristics of the MSD system, and the optimal solutions are used as the parameters of the MSD car-following model. Finally, a mixed platoon composed of 3 CAVs and 2 HDVs without performing lane changing is tested using the driver-in-the-loop test platform. The test results show that, in the mixed platoon, CAVs can optimally adjust the intervehicle spacing by making full use of the braking distance, which also provides sufficient reaction time for the driver of HDV to avoid rear-end collisions. Furthermore, in the early stage of the emergency braking, the spacing error is the dominant factor influencing the car-following behaviors, but in the later stage of emergency braking, the speed error becomes the decisive factor of the car-following behaviors. These results indicate that the proposed car-following model and quantitative index are of great significance for improving the overall safety of the mixed traffic flow with CAVs and HDVs.
Highlights
Due to the slow expansion of the road network, traffic oscillations, and traffic accidents occur frequently in road traffic. e emerging connected and automated vehicle technologies, offer great potential for enhancing traffic operations and improving the roadway capacity under existing road infrastructure, which helps make traffic flow more stable, more efficient, and safer. is is because Connected and automated vehicle (CAV) are able to share driving information with others in real time, which makes the motion of CAVs more cooperative [1]
The minimum distance between the fourth human-driven vehicles (HDVs) and the CAV in the middle position is 3.39 m. e above results indicate that each CAV in the mixed platoon can make full use of the braking distance and adjust the gap between each vehicle optimally, which can provide the driver of HDV with sufficient reaction time and braking distance to effectively avoid rear-end collisions
From the perspective of a mechanical system, a novel car-following model for mixed platoons with CAVs and HDVs was established based on the mass-springdamper theory
Summary
Due to the slow expansion of the road network, traffic oscillations, and traffic accidents occur frequently in road traffic. e emerging connected and automated vehicle technologies, offer great potential for enhancing traffic operations and improving the roadway capacity under existing road infrastructure, which helps make traffic flow more stable, more efficient, and safer. is is because CAVs are able to share driving information with others in real time, which makes the motion of CAVs more cooperative [1]. All the proposed MSD models were only applicable to the platoons that are entirely made up of HDVs or CAVs. Because the MSD system has natural stability characteristics and is widely used to represent interactions with uncertain environments [24], we propose a novel car-following model for the mixed platoon under the same simplified framework based on the virtual MSD theory, which has a great advantage over the traditional platoon model in both the stability analysis and the stable operation.
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