Managing Emergency Situations in VANET Through Heterogeneous Technologies Cooperation

Santamaria, Amilcare Francesco; Tropea, Mauro; Fazio, Peppino; De Rango, Floriano · 2018 · OpenAlex-citations

DOI: 10.3390/s18051461

archive: archived pipeline: cataloged verified

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Summary

This paper addresses the critical issue of road safety and traffic management in Vehicular Ad-hoc Networks (VANETs), motivated by high global accident rates and the limitations of centralized Intelligent Transportation Systems (ITS). The authors propose a scalable, decentralized architecture that integrates heterogeneous technologies—specifically IEEE 802.11p, GPS, and on-board sensors—to detect and manage emergency situations, such as collisions and congestion, in real-time. The goal is to reduce reaction times and prevent secondary accidents by enabling cooperative awareness among vehicles and infrastructure. The proposed solution utilizes a three-layer architecture: a Cloud layer for global traffic optimization (High Road Traffic Manager, HRTM), an Edge layer for local management (Low Road Traffic Manager, LRTM), and an End System layer comprising vehicles with Extended On-Board Units (E-OBUs) and Road-Side Units (RSUs). E-OBUs integrate vehicle sensors and GPS to monitor the environment and detect dangerous conditions. The system employs a custom communication protocol based on the WAVE Short Message Protocol (WSMP) to minimize overhead. Key defined messages include Register messages for vehicle identification, Position Update (POSUP) messages for neighbor tracking, Warning Beacons for immediate hazard alerts, and high-layer messages like Street Status and Rerouting Orders to dynamically adjust traffic flow and path weights. The study validates the architecture through extensive simulation campaigns. The results demonstrate that the proposed layered approach effectively manages dangerous situations by distributing computational load to the edge, thereby reducing system latency compared to centralized models. The simulations show significant improvements in traffic redistribution and traveling time reduction. By using graph-based metrics (weight, density, and delay) updated via the protocol, the system successfully reroutes vehicles away from incident zones. The use of WSMP proved efficient in reducing network flooding, ensuring that alert messages reach relevant vehicles quickly without overwhelming the network. The significance of this work lies in its contribution to scalable, real-time ITS solutions. By shifting from centralized cloud processing to a hybrid cloud-edge model, the architecture enhances the responsiveness of traffic management systems to emergencies. The integration of sensor data with standardized VANET protocols provides a robust framework for improving road safety, reducing congestion, and optimizing travel times. This approach offers a practical pathway for implementing cooperative driving systems that can dynamically adapt to changing road conditions and prevent accidents through timely information dissemination.

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• v2x connected vehicle