Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures
Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little resea...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2019
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| Online Access: | https://hdl.handle.net/10356/105472 http://hdl.handle.net/10220/48708 http://dx.doi.org/10.1155/2018/6135183 |
| _version_ | 1826124896452739072 |
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| author | Morando, Mark Mario Tian, Qingyun Truong, Long T. Vu, Hai L. |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Morando, Mark Mario Tian, Qingyun Truong, Long T. Vu, Hai L. |
| author_sort | Morando, Mark Mario |
| collection | NTU |
| description | Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p < 0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p < 0.05). |
| first_indexed | 2024-10-01T06:27:51Z |
| format | Journal Article |
| id | ntu-10356/105472 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:27:51Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/1054722019-12-06T21:52:01Z Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures Morando, Mark Mario Tian, Qingyun Truong, Long T. Vu, Hai L. School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering Surrogate Safety Measure Autonomous Vehicle Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM’s car-following model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at p < 0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at p < 0.05). Published version 2019-06-13T03:23:45Z 2019-12-06T21:52:01Z 2019-06-13T03:23:45Z 2019-12-06T21:52:01Z 2018 Journal Article Morando, M. M., Tian, Q., Truong, L. T., & Vu, H. L. (2018). Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures. Journal of Advanced Transportation, 2018, 6135183-. doi:10.1155/2018/6135183 0197-6729 https://hdl.handle.net/10356/105472 http://hdl.handle.net/10220/48708 http://dx.doi.org/10.1155/2018/6135183 en Journal of Advanced Transportation © 2018 Mark Mario Morando et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 11 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Civil engineering Surrogate Safety Measure Autonomous Vehicle Morando, Mark Mario Tian, Qingyun Truong, Long T. Vu, Hai L. Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title | Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title_full | Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title_fullStr | Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title_full_unstemmed | Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title_short | Studying the safety impact of autonomous vehicles using simulation-based surrogate safety measures |
| title_sort | studying the safety impact of autonomous vehicles using simulation based surrogate safety measures |
| topic | DRNTU::Engineering::Civil engineering Surrogate Safety Measure Autonomous Vehicle |
| url | https://hdl.handle.net/10356/105472 http://hdl.handle.net/10220/48708 http://dx.doi.org/10.1155/2018/6135183 |
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