Distributed Algorithm for Collision Avoidance at Road Intersections in the Presence of Communication Failures

Abstract: Vehicle-to-vehicle (V2V) communication is a crucial component of the future autonomous driving systems since it enables improved awareness of the surrounding environment, even without extensive processing of sensory information. However, V2V communication is prone to failures and delays, so a distributed fault-tolerant approach is required for safe and efficient transportation. In this paper, we focus on the intersection crossing (IC) problem with autonomous vehicles that cooperate via V2V communications, and propose a novel distributed IC algorithm that can handle an unknown number of communication failures. Our analysis shows that both safety and liveness requirements are satisfied in all realistic situations. We also found, based on a real data set, that the crossing delay is only slightly increased even in the presence of highly correlated failures.

• The paper introduces a distributed algorithm that leverages V2V communication and MTI metrics to prioritize vehicle crossing orders at intersections.
• It details a dual-mode control strategy using SAFECTRL and MAINCTRL to manage decision-making under communication failures.
• Numerical analysis confirms the method’s efficiency and robustness, significantly improving intersection safety for autonomous vehicles.

Distributed Algorithm for Collision Avoidance at Road Intersections in the Presence of Communication Failures

This paper presents a distributed algorithm designed to address the intersection crossing (IC) problem in autonomous vehicles that use vehicle-to-vehicle (V2V) communication. Given the potential for communication failures within V2V infrastructures, the paper focuses on developing an approach that maintains safety and efficiency without relying on a centralized intersection manager.

Problem and Approach

Autonomous vehicles use V2V communication to enhance their environmental awareness beyond the scope of onboard sensors. However, V2V communication is vulnerable to delays and failures, which could compromise safety, especially at road intersections where the majority of accidents occur.

Problem Formulation

The paper formulates the problem by considering scenarios with two autonomous cars equipped with minimal sensing units (GPS and IMU) and a V2V communication module. The vehicles' goal at a road intersection is to coordinate their crossing order without collisions despite potential communication loss.

• Metrics for Decision: The mean time to intersection (MTI) is computed from each vehicle's position and dynamics. The vehicle with the lower MTI is given priority.
• Handling Communication Failures: The algorithm is designed to handle unknown and large numbers of communication failures. It relies on 'ENTER' and 'EXIT' messages, verified by heartbeat (HB) messages, to manage crossing priorities safely.

Algorithm Description

A key innovation is the distributed management of the IC problem via autonomous decision-making by vehicles without centralized dependency:

Control Actions

• Safe Control (SAFECTRL): Initiated when failures are detected, the vehicle decelerates to stop before reaching the collision area.
• Main Control (MAINCTRL): Executed when both vehicles have agreement on crossing order based on MTI values, ensuring orderly intersection passage.

Algorithm Phases

1. Before ENTER Phase: Triggers when the vehicle's probability to enter the capture area exceeds a threshold.
2. ENTER Phase: Begins when a vehicle senses imminent intersection entry. Vehicles communicate 'ENTER' messages to negotiate crossing order.
3. Wait for EXIT Phase: Non-priority vehicles wait for the 'EXIT' message from the priority vehicle.
4. EXIT Phase: The priority vehicle signals successful intersection crossing, allowing others to proceed.

Numerical Analysis

The authors provide a numerical analysis based on real-world observations of packet delivery reliability, with results showing that the algorithm efficiently handles communication failures even in demanding environments. With correlated failures or high transition probabilities, delays increase but remain manageable compared to crossing times.

Implications and Future Work

The methodology extends collision avoidance strategies for autonomous vehicles at intersections by not requiring centralized control. This increases system robustness in environments with unreliable communication.

Future extensions include adaptation to multiple vehicle interactions and integration into simulation frameworks consistent with industry standards.

Conclusion

The proposed distributed IC algorithm demonstrates proficiency in maintaining road safety at intersections amid V2V communication challenges. The effort contributes to advancing autonomous vehicle technology by mitigating risks associated with intersection traversal, providing resilience against communication faults.

The scope for development remains extensive, including handling malicious messages and improving scalability with more vehicles. The approach has practical implications for traffic management systems in reducing autonomous vehicle reliance on infrastructure and enhancing network-level vehicular cooperation.