Abstract
In this paper, we present an enhanced Collision Avoidance (eCA) service that leverages vehicle connectivity through a cellular network to avoid vehicle collisions and increase road safety at intersections. The eCA service is assumed to be deployed at the edge of the network, thus curbing the latency incurred by the communication process. The core of the eCA service is composed of a Collision Avoidance Algorithm (CAA), and a Collision Avoidance Strategy (CAS). The former predicts the vehicle’s future trajectory through the positional information advertised by periodic beacons and detects if two vehicles are on a collision course. The latter decides which of the vehicles potentially involved in a collision should yield. The vehicles are then notified of both the impending danger and of the actions needed to avoid it. We have simulated our solution using SUMO (Simulation of Urban MObility) and ns-3 (network simulator 3) with the LENA (LTE-EPC Network simulAtor) framework on a Manhattan-grid road topology, and observed its good performance in terms of avoided collisions percentage as a function of vehicle speed and different vehicles densities.
Highlights
The number of traffic fatalities on roads remains unacceptably high
In this paper, we address road-safety services and focus in particular on vehicle Collision Avoidance at intersections, in which an application server deployed at the edge of the network infrastructure gathers all the Cooperative Awareness Messages (CAMs) periodically sent by the vehicles, runs a Collision Avoidance application detecting vehicles on a collision course, and transmits Decentralized Environmental Notification Messages (DENMs) to the vehicles possibly involved in the detected collision
We provide the following main contributions: (i) we design an edge-based, enhanced Collision Avoidance service, which, thanks to its architecture, allows the investigation and the selection of strategies to avoid vehicle collisions and increase road safety at intersections; (ii) we develop an open source simulation framework that closely mimics real-world conditions and dynamics, combining a realistic cellular network model and realistic mobility traces (SUMO)
Summary
The number of traffic fatalities on roads remains unacceptably high. With a peak of 1.35 million, as reported in the ‘‘Global status report on road safety 2018’’, traffic accidents represent the 8th leading cause of death for people of all ages and the 1st for children and young adults from 5 to 29 years of age [1]. In this paper, we address road-safety services and focus in particular on vehicle Collision Avoidance at intersections, in which an application server deployed at the edge of the network infrastructure (i.e., close to vehicles) gathers all the Cooperative Awareness Messages (CAMs) periodically sent by the vehicles, runs a Collision Avoidance application detecting vehicles on a collision course, and transmits Decentralized Environmental Notification Messages (DENMs) to the vehicles possibly involved in the detected collision In this context, we provide the following main contributions: (i) we design an edge-based, enhanced Collision Avoidance (eCA) service, which, thanks to its architecture, allows the investigation and the selection of strategies to avoid vehicle collisions and increase road safety at intersections; (ii) we develop an open source simulation framework that closely mimics real-world conditions and dynamics, combining a realistic cellular network model (ns-3 LENA) and realistic mobility traces (SUMO).
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