Cooperative Vehicles for Monitoring Urban Roads Based on Behavioral Rules

Abstract

In the near future, Intelligent Transportation Systems will integrate autonomous vehicles and roadside infrastructures in the current urban road setup to collect environment data and then disseminate the information to surrounding vehicles for road safety, traffic convenience, and travel comfort. Autonomous vehicles, individually, can perform traffic-specific tasks to accomplish certain objectives, such as exploring for unknown or unmapped road sections and searching for road accidents. In this work, a cooperative search algorithm based on behavioral rules are used to direct PBOT (no acronym definition) mobile robots to cooperatively search road accidents in the city. The PBOTs, emulating autonomous vehicles, follow a hierarchical set of behavioral rules to achieve a cooperative search and uses the cellular network for communication and data exchange among PBOTs. PBOTs are programmed to follow random and deterministic paths in sensing the urban grid map. Results show that deterministic paths provide lesser exploration time, but may not be realistically viable. On the other hand, the network delay is affected by both the number of PBOTs and change in the urban map size.