journal article·2022Open access

Cluster-Based Stable BSM Dissemination System for Safe Autonomous Platooning

Sagheer Abbas, Yousef Alhwaiti, Areej Fatima, Muhammad A. Khan, Muhammad Adnan Khan, Taher M. Ghazal, Asma Kanwal, Munir Ahmad, Nouh Sabri Elmitwally

Computers, Materials & Continua· Volume 71· Issue 1

Abstract

Recently, the importance of vehicle safety supporting system has been highlighted as autonomous driving and platooning has attracted the researchers. To ensure driving safety, each vehicle must broadcast a basic safety message (BSM) every 100 ms. However, stable BSM exchange is difficult because of the changing environment and limited bandwidth of vehicular wireless communication. The increasing number of vehicles on the road increases the competition to access wireless networks for BSM exchange; this increases the packet collision rate. An increased packet collision rate impairs the transmission and reception of BSM information, which can easily cause a traffic accident. We propose a solution, the vehicular safety support system (V3S), which exchanges BSMs reliably even when many vehicles are on the road. The V3S uses a clustering scheme to decrease network traffic by reducing the amount of data exchanged between a vehicle and the roadside unit (RSU). In addition, the V3S reduces the collision rate of wireless network packets by broadcasting the vehicle's BSM in an allocated timeslot using the time division multiple access (TDMA) MAC protocol. The V3S also deals with insufficient bandwidth for dedicated short-range communications (DSRC) by changing DSRC channels according to traffic flow. In evaluating the packet error rate for stable BSM packet delivery, the V3S demonstrates an excellent packet error rate of less than 1%, compared to the 802.11p with its packet error rate of 82%.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Vehicular Ad Hoc Networks (VANETs) · Traffic control and management · Transportation and Mobility Innovations

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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