To improve traffic congestion of urban intersections, this article presents a cooperative vehicle intersection control scheme without using any traffic lights, based on model predictive control theory. The assumptions are that all vehicles are fully automated and that a control unit is installed at the intersection to coordinate vehicle movements. Using connected vehicles technology, vehicles approaching the intersection from all directions are globally coordinated by integrating their states all together. The trajectories of vehicles are predicted and adjusted based on collision avoidance under relevant constraints and preferences. The control scheme prevents each pair of conflicting vehicles from approaching conflicting areas at the same time and minimizes the total collision risks of all pairs of conflicting vehicles. The simulation platform was developed to quantifiably evaluate the overall performance of the scheme. Simulation results show that the proposed scheme can significantly improve the mobility, safety, and environmental aspects of the intersection compared with conventional actuated controls. In addition, we also found that better performance can be achieved when the intersection is being operated under oversaturated conditions, and the market penetration rates of equipped vehicles exceed 30%.
This article introduces the b phase plane method to determine the stability state of the vehicle and then proposes the electronic stability program fuzzy controller to improve the stability of vehicle driving on a low adhesion surface at high speed. According to fuzzy logic rules, errors between the actual and ideal values of the yaw rate and sideslip angle can help one achieve a desired yaw moment and rear wheel steer angle. Using genetic algorithm, optimize the fuzzy controller parameters of the membership function, scale factor, and quantization factor. The simulation results demonstrate that not only the response fluctuation range of the yaw rate and sideslip angle, but also the time taken to reach steady state are smaller than before, while reducing the vehicle oversteer trend and more closer to neutral steering. The optimized fuzzy controller performance has been improved.
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