A Knowledge-Based Analysis of Intersection Protocols

TL;DR

This paper models vehicle intersection management as a protocol problem, introducing a knowledge-based framework that guarantees safety, liveness, and optimality even with faulty vehicles, advancing autonomous traffic coordination.

Contribution

It presents a novel knowledge-based framework for designing intersection protocols that ensure safety, liveness, and optimality, including in faulty vehicle scenarios.

Findings

Protocols guarantee safety and liveness.

Protocols achieve optimality under certain conditions.

Fault-tolerant protocols maintain safety and liveness.

Abstract

The increasing wireless communication capabilities of vehicles creates opportunities for more efficient intersection management strategies. One promising approach is the replacement of traffic lights with a system wherein vehicles run protocols among themselves to determine right of way. In this paper, we define the intersection problem to model this scenario abstractly, without any assumptions on the specific structure of the intersection or a bound on the number of vehicles. Protocols solving the intersection problem must guarantee safety (no collisions) and liveness (every vehicle eventually goes through). In addition, we would like these protocols to satisfy various optimality criteria, some of which turn out to be achievable only in a subset of the contexts. In particular, we show a partial equivalence between eliminating unnecessary waiting, a criterion of interest in the distributed mutual-exclusion literature, and a notion of optimality that we define called lexicographical optimality. We then introduce a framework to design protocols for the intersection problem by converting an intersection policy, which is based on a global view of the intersection, to a protocol that can be run by the vehicles through the use of knowledge-based programs. Our protocols are shown to guarantee safety and liveness while also being optimal under sufficient conditions on the context. Finally, we investigate protocols in the presence of faulty vehicles that experience communication failures and older vehicles with limited communication capabilities. We show that intersection protocols can be made safe, live and optimal even in the presence of faulty behavior.