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A Crash Injury Model Involving Autonomous Vehicle: Investigating of Crash and Disengagement Reports by Sinha, Amolika (author);Vu, Vincent (author);Chand, Sai (author);Wijayaratna, Kasun (author);Dixit, Vinayak (author) is a Environmental Science article available to read on EtoBox.
What is A Crash Injury Model Involving Autonomous Vehicle: Investigating of Crash and Disengagement Reports about?
Autonomous vehicles (AVs) are being extensively tested on public roads in several states in the USA, such as California, Florida, Nevada, and Texas. AV utilization is expected to increase into the future, given rapid advancement and development in sensing and navigation technologies. This will eventually lead to a decline in human driving. AVs are generally believed to mitigate crash frequency, although the repercussion of AVs on crash severity is ambiguous. For the data-driven and transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. This study performed a comprehensive assessment of CA DMV data from 2014 to 2019 from a safety standpoint, and some trends were discerned. The results show that decrement in automated disengagements does not necessarily imply an improvement in AV technology. Contributing factors to the crash severity of an AV are not clearly defined. To further understand crash severity in AVs, the features and issues with data are identified and discussed using different machine learning techniques. The CA DMV accident report data were
Who reads A Crash Injury Model Involving Autonomous Vehicle: Investigating of Crash and Disengagement Reports?
It is typically read by researchers, students, and practitioners in Environmental Science.
- Author
- Sinha, Amolika (author);Vu, Vincent (author);Chand, Sai (author);Wijayaratna, Kasun (author);Dixit, Vinayak (author)
- Publisher
- MDPI AG
- Published
- 2021
- Language
- EN
- Field
- Environmental Science (Social Sciences)