Context-Aware Rate-Adaptive Beaconing for Efficient and Scalable Vehicular Safety Communication
Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed and heading, which enables each vehicle to track its neighboring vehicles in real time. This paper presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities.