Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections
Human error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (I...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/6677010 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832565263802826752 |
|---|---|
| author | Mohammad Khashayarfard Habibollah Nassiri |
| author_facet | Mohammad Khashayarfard Habibollah Nassiri |
| author_sort | Mohammad Khashayarfard |
| collection | DOAJ |
| description | Human error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (ITS) to minimize human error. In this study, the effect of Autonomous Vehicles (AVs) on the number of potential conflicts at two unsignalized intersections is investigated by using a microsimulation model in PTV Vissim software. For human-driven cars, the factor that is considered for calibration is driver distraction mainly caused by reading or writing text messages on a cellphone while driving. This factor can be estimated using driving simulators. In this paper, five different scenarios were defined for simulation, in addition to the primary state, according to the different market penetration rates of AVs in Vissim. Safety assessment was performed by the Surrogate Safety Assessment Model (SSAM) using Time to Collision (TTC) and Deceleration Rate to Avoid Crashes (DRAC) indicators to determine the number of accidents. It was concluded that the presence of 100% of AVs could reduce the potential for accidents by up to 93%. |
| format | Article |
| id | doaj-art-d82eb7019d0f40b8be90921d00371ae4 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-d82eb7019d0f40b8be90921d00371ae42025-02-03T01:08:52ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/66770106677010Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized IntersectionsMohammad Khashayarfard0Habibollah Nassiri1Civil Engineering Department, Sharif University of Technology, Tehran, IranCivil Engineering Department, Sharif University of Technology, Tehran, IranHuman error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (ITS) to minimize human error. In this study, the effect of Autonomous Vehicles (AVs) on the number of potential conflicts at two unsignalized intersections is investigated by using a microsimulation model in PTV Vissim software. For human-driven cars, the factor that is considered for calibration is driver distraction mainly caused by reading or writing text messages on a cellphone while driving. This factor can be estimated using driving simulators. In this paper, five different scenarios were defined for simulation, in addition to the primary state, according to the different market penetration rates of AVs in Vissim. Safety assessment was performed by the Surrogate Safety Assessment Model (SSAM) using Time to Collision (TTC) and Deceleration Rate to Avoid Crashes (DRAC) indicators to determine the number of accidents. It was concluded that the presence of 100% of AVs could reduce the potential for accidents by up to 93%.http://dx.doi.org/10.1155/2021/6677010 |
| spellingShingle | Mohammad Khashayarfard Habibollah Nassiri Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections Journal of Advanced Transportation |
| title | Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections |
| title_full | Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections |
| title_fullStr | Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections |
| title_full_unstemmed | Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections |
| title_short | Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections |
| title_sort | studying the simultaneous effect of autonomous vehicles and distracted driving on safety at unsignalized intersections |
| url | http://dx.doi.org/10.1155/2021/6677010 |
| work_keys_str_mv | AT mohammadkhashayarfard studyingthesimultaneouseffectofautonomousvehiclesanddistracteddrivingonsafetyatunsignalizedintersections AT habibollahnassiri studyingthesimultaneouseffectofautonomousvehiclesanddistracteddrivingonsafetyatunsignalizedintersections |