Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident
To address the need for an in-depth exploration of traffic accidents involving intelligent vehicles and to elucidate the influence mechanism of road environment interference factors on both assisted driving systems and human drivers during such accidents, a comprehensive analysis has been conducted...
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| Format: | Article |
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MDPI AG
2025-03-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/3/158 |
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| author | Yanbin Hu Wenhui Zhou |
| author_facet | Yanbin Hu Wenhui Zhou |
| author_sort | Yanbin Hu |
| collection | DOAJ |
| description | To address the need for an in-depth exploration of traffic accidents involving intelligent vehicles and to elucidate the influence mechanism of road environment interference factors on both assisted driving systems and human drivers during such accidents, a comprehensive analysis has been conducted using the System-Theoretic Process Analysis (STPA) framework. This analysis focuses on road static facilities, traffic dynamic characteristics, and instantaneous weather conditions in automobile traffic accidents that occur under the human-machine co-driving paradigm with integrated assisted driving functions. Based on these insights, an interference model tailored to road environment factors in traffic accidents of assisted driving vehicles has been constructed.Utilizing recent traffic accident cases in China, the Accident Map (AcciMap) methodology was employed to systematically classify and analyze all accident participants across six levels. Through this rigorous process, 59 accident factors were refined and optimized, culminating in a method for assessing the degree of interference posed by road environment factors in traffic accidents involving assisted driving vehicles. The ultimate objective of this research is to enhance the investigation of road environment interference factors following accidents that occur with diverse assisted driving functions in human-machine co-driving scenarios. By providing a structured and analytical approach, this study aims to support future research endeavors in developing effective traffic accident prevention countermeasures tailored to assisted driving vehicles. |
| format | Article |
| id | doaj-art-8e0c9c26703b441a848cba1e01a8e89b |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-8e0c9c26703b441a848cba1e01a8e89b2025-08-20T03:43:58ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-03-0116315810.3390/wevj16030158Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic AccidentYanbin Hu0Wenhui Zhou1Research Institute for Road Safety of the Ministry of Public Security, Beijing 100741, ChinaResearch Institute for Road Safety of the Ministry of Public Security, Beijing 100741, ChinaTo address the need for an in-depth exploration of traffic accidents involving intelligent vehicles and to elucidate the influence mechanism of road environment interference factors on both assisted driving systems and human drivers during such accidents, a comprehensive analysis has been conducted using the System-Theoretic Process Analysis (STPA) framework. This analysis focuses on road static facilities, traffic dynamic characteristics, and instantaneous weather conditions in automobile traffic accidents that occur under the human-machine co-driving paradigm with integrated assisted driving functions. Based on these insights, an interference model tailored to road environment factors in traffic accidents of assisted driving vehicles has been constructed.Utilizing recent traffic accident cases in China, the Accident Map (AcciMap) methodology was employed to systematically classify and analyze all accident participants across six levels. Through this rigorous process, 59 accident factors were refined and optimized, culminating in a method for assessing the degree of interference posed by road environment factors in traffic accidents involving assisted driving vehicles. The ultimate objective of this research is to enhance the investigation of road environment interference factors following accidents that occur with diverse assisted driving functions in human-machine co-driving scenarios. By providing a structured and analytical approach, this study aims to support future research endeavors in developing effective traffic accident prevention countermeasures tailored to assisted driving vehicles.https://www.mdpi.com/2032-6653/16/3/158assisted driving vehicletraffic accident investigationSystem-Theoretic Process AnalysisAccident Map |
| spellingShingle | Yanbin Hu Wenhui Zhou Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident World Electric Vehicle Journal assisted driving vehicle traffic accident investigation System-Theoretic Process Analysis Accident Map |
| title | Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident |
| title_full | Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident |
| title_fullStr | Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident |
| title_full_unstemmed | Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident |
| title_short | Correlation Method of Assistance Driving Function and Road Environment Factors in Investigation of Intelligent Vehicle Traffic Accident |
| title_sort | correlation method of assistance driving function and road environment factors in investigation of intelligent vehicle traffic accident |
| topic | assisted driving vehicle traffic accident investigation System-Theoretic Process Analysis Accident Map |
| url | https://www.mdpi.com/2032-6653/16/3/158 |
| work_keys_str_mv | AT yanbinhu correlationmethodofassistancedrivingfunctionandroadenvironmentfactorsininvestigationofintelligentvehicletrafficaccident AT wenhuizhou correlationmethodofassistancedrivingfunctionandroadenvironmentfactorsininvestigationofintelligentvehicletrafficaccident |