Current Volume 8
Abstract
Ensuring the safety of hazardous material (Hazmat) transportation is critical. One of the most widely occurred traffic accidents is the run-off-road (ROR) incident. It is needed for exploring effective means of avoiding or even warning of ROR accidents for hazmat transportation. In particular, it is important to note that in many cases, vehicles are not driven on regular roads, but in "off-road" situations such as mountainous areas, where off-road detection is a hazard detection for abnormal driving. In this paper, we point out that it is a viable path for monitoring and detecting ROR incidents using an onboard camera. We reviewed existing literature in terms of the algorithm and the data that can be used. We also illustrate the shortcomings and provide insights into the future development of algorithms for detecting ROR incidents. Our research tailored a path to an effective ROR monitoring and detecting scheme that enhances the safety of hazardous material transportation.
Keywords
Algorithm design, Hazardous material transportation, Safety sciences.
Citations
IRE Journals:
Shuashua Mao , Lifeng Zhao; Changqing Tian; Xiang Liu , Long Lin; Helix Xie; Ning Zhou , Yiping Zeng; Guangpu Zhang; Chenhui Pan , Kang Yao; Xiaoxin Pi; T. R. Chen
"Off-road Detection Using Vision Techniques for Hazardous Material Transportation Vehicles" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 243-246
IEEE:
Shuashua Mao , Lifeng Zhao; Changqing Tian; Xiang Liu , Long Lin; Helix Xie; Ning Zhou , Yiping Zeng; Guangpu Zhang; Chenhui Pan , Kang Yao; Xiaoxin Pi; T. R. Chen
"Off-road Detection Using Vision Techniques for Hazardous Material Transportation Vehicles" Iconic Research And Engineering Journals, 6(1)
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IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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