Speed Harmonisation Strategy for Human-Driven and Autonomous Vehicles Co-existence

Autonomous vehicle emergence with the potential to improve the traffic system efficiency and user comfort have made the co-existence of human-driven and autonomous vehicles inevitable in the near future. The different vehicle type co-existence has facilitated vehicle speed harmonisation to enhance traffic flow efficiency and prevent vehicle collision risk on the road. To a large extent, speed control and supervision of mix-traffic behaviours will go a long way to ameliorate the concerns envisaged in the autonomous vehicle integration process. A model predictive control-based autonomous vehicle speed adjustment technique with safe distance is developed to optimise the flow of mixed vehicles based on estimated driving behaviour. The main contribution of this work is employing the autonomous vehicle speed adjustment to the existing car-following model in mixed traffic. A mixed-traffic simulator is developed to test the proposed method in a car following model using a merging road to quantify the benefit of the proposed speed control strategy. The proposed simulation model is validated, and experiments are conducted with varying traffic intersection control strategies and vehicle type proportions. The obtained results demonstrate that the speed adjustment strategy has about 18.2% performance margin.