Indian Journal of Science and Technology

Abstract

Objective: To design and develop an enhanced Misbehaviour Detection Scheme (MDS) that addresses the problem of transmitting false information in Vehicular Ad hoc Network (VANET). Methods/Analysis: To achieve the purpose of this paper, data was collected through simulating a vehicle crash in different traffic scenarios. The data collected was then used to design a Misbehaviour Detection Scheme considering two inputs of Emergency Electronic Brake Light (EEBL) and Lane Change (LC). To confirm the veracity of transmitted Post-Crash Notification (PCN) alert, Bayes’ rule was used to combine the two alert evidences. Findings: In each of the experiments conducted, the scenario belief values (probability of individual events) were calculated and Bayes’ rule was used for combining the two evidences to obtain a better belief value. Simulation results show that increasing vehicle speed improves detection accuracy. Traffic scenarios having vehicles with low speed transmits fewer secondary alerts. Existing MDS uses single secondary alerts for verifying received PCN alerts. The proposed scheme combines evidences from more than one secondary alert to enhance the belief value of received PCN alert. Applications/Improvements: Combining multiple alert evidences shows that the proposed MDS makes significant enhancement to the existing scheme. Testing the proposed scheme with vehicles on high speeds shows 100% detection accuracy for transmitted PCN alerts. 

Keywords: Braking Alerts, Lane Change, Misbehaviour Detection, Post-Crash Notification, VANET