TY - GEN
T1 - A software framework of roadside units for traffic condition perception and broadcast
AU - Wang, Shao Hua
AU - Yiu, Wei Liang
AU - Tu, Chia Heng
AU - Chang, Da Wei
AU - Lee, Wei Hsun
N1 - Funding Information:
This work is financially supported in part by the "Intelligent Manufacturing Research Center" (iMRC)from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. This work is supported in part by the Ministry of Science and Technology, Taiwan, under the grants MOST-111-2221-E-006-116-MY3 and MOST-110-2221-E-006-085-MY3.
Publisher Copyright:
© 2022 ACM.
PY - 2022/10/3
Y1 - 2022/10/3
N2 - While vehicle-to-everything technology has been proposed to improve road traffic efficiency and safety, it would suffer from the low coverage during an early stage of vehicle-to-everything deployment. The infrastructure-based solutions have been developed to tackle the problem by gathering traffic status on a roadside unit and broadcasting the detected information to nearby connected vehicles. In this work, we aim to augment such an infrastructure-centric design by proposing a multiple applications software framework to broadcast the sensed traffic conditions to connected vehicles in the vicinity. In addition, we propose a software module to improve the handling of multiple applications for the roadside unit. We have evaluated the proposed software in indoor tests, which shows that the framework can significantly improve traffic safety while conforming to the performance specifications of the standards defined by the Society of Automotive Engineers.
AB - While vehicle-to-everything technology has been proposed to improve road traffic efficiency and safety, it would suffer from the low coverage during an early stage of vehicle-to-everything deployment. The infrastructure-based solutions have been developed to tackle the problem by gathering traffic status on a roadside unit and broadcasting the detected information to nearby connected vehicles. In this work, we aim to augment such an infrastructure-centric design by proposing a multiple applications software framework to broadcast the sensed traffic conditions to connected vehicles in the vicinity. In addition, we propose a software module to improve the handling of multiple applications for the roadside unit. We have evaluated the proposed software in indoor tests, which shows that the framework can significantly improve traffic safety while conforming to the performance specifications of the standards defined by the Society of Automotive Engineers.
UR - http://www.scopus.com/inward/record.url?scp=85141044899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141044899&partnerID=8YFLogxK
U2 - 10.1145/3538641.3561480
DO - 10.1145/3538641.3561480
M3 - Conference contribution
AN - SCOPUS:85141044899
T3 - ACM International Conference Proceeding Series
SP - 1
EP - 8
BT - Proceedings of the 2022 Research in Adaptive and Convergent Systems, RACS 2022
PB - Association for Computing Machinery
T2 - 2022 Conference on Research in Adaptive and Convergent Systems, RACS 2022
Y2 - 3 October 2022 through 6 October 2022
ER -