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In this paper, we offer an algorithm for intelligent decision making about travel path planning in mobile vehicular ad-hoc networks (VANETs), for scenarios where agents representing vehicles exchange reports about traffic. One challenge that arises is how best to model the trustworthiness of those traffic reports. To this end, we outline an algorithm for effectively soliciting, receiving and analyzing the trustworthiness of these reports, to drive a vehicle’s decision about the path to follow. Distinct from earlier work, we clarify the need for specifying the conditions under which reports are exchanged and for processing non-binary reports, culminating in a proposed algorithm to achieve that processing, as part of the trust modeling and path planning. To validate our approach we then offer a detailed evaluation framework that achieves large scale simulation of traffic, travel and reporting of information, confirming the value of our proposed approach by demonstrating the average speed of vehicles which follow our algorithm (compared to ones that do not). This experimental framework is promoted as a significant contribution towards the goal of evaluating trust algorithms for intelligent decision making in traffic scenarios.

A trust-based framework for vehicular travel with non-binary reports and its validation via an extensive simulation testbed