Details

Autor(en) / Beteiligte

• Lyu, Feng
• Cheng, Nan
• Zhu, Hongzi
• Zhou, Haibo
• Xu, Wenchao
• Li, Minglu
• Shen, Xuemin

Titel

Towards Rear-End Collision Avoidance: Adaptive Beaconing for Connected Vehicles

Ist Teil von

• IEEE transactions on intelligent transportation systems, 2021-02, Vol.22 (2), p.1248-1263

Ort / Verlag

IEEE

Erscheinungsjahr

2021

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Connected vehicles have been considered as an effective solution to enhance driving safety as they can be well aware of nearby environments by exchanging safety beacons periodically. However, under dynamic traffic conditions, especially for dense-vehicle scenarios, the naive beaconing scheme where vehicles broadcast beacons at a fixed rate with a fixed transmission power can cause severe channel congestion and thus degrade the beaconing reliability. In this paper, by considering the kinematic status and beaconing rate together, we study the rear-end collision risk and define a danger coefficient <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> to capture the danger threat of each vehicle being in the rear-end collision. In specific, we propose a fully distributed adaptive beacon control scheme, called ABC , which makes each vehicle actively adopt a minimal but sufficient beaconing rate to avoid the rear-end collision in dense scenarios based on individually estimated <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula>. With ABC , vehicles can broadcast at the maximum beaconing rate when the channel medium resource is enough and meanwhile keep identifying whether the channel is congested. Once a congestion event is detected, an NP-hard distributed beacon rate adaptation (DBRA) problem is solved with a greedy heuristic algorithm, in which a vehicle with a higher <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> is assigned with a higher beaconing rate while keeping the total required beaconing demand lower than the channel capacity. We prove the heuristic algorithm's close proximity to the optimal result and thoroughly analyze the communication overhead of ABC scheme. By using Simulation of Urban MObility (SUMO)-generated vehicular traces, we conduct extensive simulations to demonstrate the efficacy of our proposed ABC scheme. Simulation results show that vehicles can adapt beaconing rates according to the driving safety demand, and the beaconing reliability can be guaranteed even under high-dense vehicle scenarios.