Authors
Filippos N. Tzortzoglou, Andreas A. Malikopoulos
Abstract
This website is provided to facilitate the comprehension of our paper titled "Handling Pedestrian Uncertainty in Coordinating Autonomous Vehicles at Signal-Free Intersections". While autonomous vehicles are increasingly penetrating the market, signal-free intersections may become more prevalent in the coming years. However, no approach in the literature addresses the problem of pedestrian uncertainty at signal-intersections. This issue is critical due to the nature of autonomous vehicles.
The full paper is available at this link.
Finding a solution in optimal control problem
As discussed in the manuscript, in order to find a solution in (8), we initialize a feasible range of exit times. We then select the minimum one that satisfies the corresponding constraints. Especially, we derive the optimal control trajectory and check if the solution satisfies all the constraints. If it does, we have found our solution. Otherwise, we increase the exit time by a time step and repeat the process. To understand this better, we can visualize the feasible trajectories for a CAV in the specific scenario depicted in the following figure.
In the following video, we demonstrate the application of Lemma 1 and Theorem 1 in a scenario where two CAVs simultaneously enter the control zone from two conflicting paths
Next, we present a video from RoadRunner that demonstrates how our approach effectively manages critical situations and illustrates the functioning of our replanning mechanism, even when more than two CAVs enter the control zone. It is important to note that once a CAV detects a pedestrian through its sensors, all other CAVs gain access to the pedestrian's location.
In the following video, we present video simulations conducted in MATLAB, demonstrating that different CAVs exhibit varying levels of conservativeness concerning the unsafe region associated with pedestrians. It is important to note that as the size of the ellipse increases, the CAVs are afforded less freedom to adjust their steering angles.
Compared to the previous video, the current simulation illustrates that the critical CAV adopts a less conservative model. This is reflected in the smaller ellipse associated with the unsafe region, indicating that the CAV closer to the pedestrian exhibits more abrupt changes in its steering angle in order to avoid a collision.