Recent developments in wireless communication technologies have led to the evolution of connectivity between vehicles. Maintaining connectivity between vehicles increases a vehicle’s awareness of other nearby vehicles, which can be used in safety applications. Identification of malicious misbehaving vehicles plays an important role in road safety. This research establishes the minimum detectable error (MDE) boundary for relative position between the observer and status vehicles (SV) using vehicle sensor and GPS error profile from field tests and established minimum standards. The results demonstrated that the MDE increases in the lateral direction (side-to-side) with the increase in relative distance between the observer and status vehicles (OV and SV) while remaining the same in the longitudinal direction (front-to-back). This research effort explores the use of Sensor-Based Misbehavior Detection (SBMD) with current specifications and the defined MDE boundary for implementation in the Intersection Movement Assist (IMA) safety application to rectify false positive and false negative hazard messages propagated by a malicious misbehaving vehicle. The simulation approach used in this research quantifies the total number of false positive/negative hazard detections received by a third-party vehicle (TPV) using the IMA safety application and assesses the capability of the OV equipped with SBMD to rectify the false positive/negative hazard detection. In cases where there was no hazard, SBMD produced an 83% to 90% improvement in the reduction of false positive hazard detections. In the cases with hazard scenario, where the SV is in the not-safe-to-cross zone, SBMD produced an 80% to 99% improvement in application performance.
Misbehavior Detection in Ephemeral Networks: A Local Voting Game in Presence of Uncertainty