These videos are part of the results presented in the conference paper titled "Joint trajectory optimization for multiple automated vehicles in lane-free traffic with vehicle nudging". A group of 8 connected and automated vehicles are moving on a lane-free straight road with 10.2 m width. All the vehicles start from 10 m/s longitudinal speed and try to reach their respective longitudinal desired speeds, [17, 16, 15, 14, 13, 12, 11, 10] m/s, and zero lateral speed. At the initial state, the 8 vehicles are aligned behind each other in the middle of the road in ascending order (from downstream to upstream) of their longitudinal desired speeds. Therefore, the vehicles need to overtake one another and create intelligent maneuvers in order to reach their desired speeds and reverse their longitudinal positioning. In both videos the camera is tracking the fourth vehicle of the group (the one with 14 m/s desired speed). Videos are recorded for the whole optimization time horizons and played at 3x speed. At the end of every scenario, all the vehicles have reached their desired speeds and are longitudinally ordered according to their desired speeds. Joint movement trajectories are obtained by solving an optimal control problem.
In this video a group of 8 vehicles is considered. At the start, vehicles are longitudinally located 40 m behind each other. Lateral initial positions of the vehicles are around the center of the road. Vehicles are seen to intelligently overtake one another or at some points get nudged towards the lateral road boundary, in order to make room for faster vehicles behind to pass. At the end of the video, it can be seen that the fastest vehicle of the group is the first vehicle of the group, the second-fastest vehicle is second in positioning order and so on.
In this video the same group of 8 vehicles is considered (shown with the color blue), albeit with the addition of 3 independent vehicles, acting as moving obstacles (shown with the color red), whose longitudinal and lateral speeds are kept constant during the whole optimization time horizon. Two of these obstacles are stopped at the road boundary, emulating an incident; and the third obstacle is moving with a constant speed of 10 m/s at the road boundary. This scenario is more challenging than the previous one, as each vehicle is dealing with obstacles as well as other vehicles of the group. Therefore, the amount of required maneuvers increases. It can be observed that all the vehicles reach their desired speeds and orders safely.