Enhancing vehicle safety through IIoT-based collision avoidance systems

Rising automobile populations have led to increased accident rates, resulting in significant fatalities and property damage worldwide. The collision avoidance system (CAS) is one of the significant components in vehicle safety enhancement. The integration of industrial internet of things (IIoT) with CAS, the advantages of this technology, and its drawbacks have all been examined in this study. Furthermore, in order to enhance the IIoT-based CAS for automobiles, analytical techniques, algorithms, and protocols have been suggested. The results show that IIoT-based CAS can improve vehicle safety through accident reduction and faster response times. Also, the number of IIoT-based CAS (i.e., capacity analysis) that can be accommodated using different generations of WLAN standards like IEEE 802.11b/g/n/ac/ax/be has been obtained. The simulation and experimental results show that the IIoT-enabled CAS can achieve a 13.26% higher average collision-avoidance success rate compared to the traditional CAS as the baseline. We have also conducted a formal STRIDE threat modeling along with an ad hoc attack simulation to prove that our solution can incur > 93% lower success rates of spoofing and denial of service (DoS) attacks. Collectively, the results provide a promising, scalable, and secure solution towards the global goal of Vision Zero.