The importance of V2X simulation: An in-depth comparison of intersection control algorithms using a high-fidelity communication simulation

The rapid evolution of vehicle-to-vehicle and vehicle-to-infrastructure communication opens doors to various control algorithms, one particular domain being intersection control. Several researchers have proposed communication-based intersection control algorithms omitting traditional traffic lights with the promise of enhanced throughput and improved traffic safety. On the other hand, the majority of these algorithms ignore the uncertainties and delays of communication and overlook new cyberattack vectors that are opened by connected traffic. The present study employs a highly detailed simulation of vehicular communication to highlight the sensitivity of different autonomous intersection control algorithms (both centralized and decentralized) to communication-related imperfections. The paper investigates five different algorithms borrowed from the literature in a comparative way. This research focuses on traffic-related parameters such as average speed, occupancy, and network throughput while also analyzing communication-related parameters (e.g., packet loss, computational demand) and considering possible attack vectors. Simulation results suggest that even the simplest control logic is sensitive to communication failures, degrading intersection throughput below traditional intersection control or even compromising traffic safety. For centralized algorithms, in the presence of noise, average speeds drop significantly, suggesting reduced intersection throughput and even gridlock for the First Come First Serve algorithm. Decentralized algorithms can be heavily affected by incoming message orders, which can lead to dangerous situations. During the simulations, multiple collisions were registered for the Monte-Carlo Tree Search algorithm. More complex algorithms that rely on accurate prediction on vehicle trajectories are more sensitive to noise and even produce accidents in the simulation. In conclusion, regardless of control architecture, the evaluated algorithms require additional fallback solutions and redundancies to retain traffic safety. (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).