A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems
This paper proposes a test scenario design method that reflects the longitudinal characteristics of reality for effective verification of advanced driver assistance systems (ADAS) and autonomous driving systems (ADS). Since the target systems interact with the external environment differently from t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/2/716 |
| _version_ | 1797446736373874688 |
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| author | Kunhee Cho Changwoo Park Hyeongcheol Lee |
| author_facet | Kunhee Cho Changwoo Park Hyeongcheol Lee |
| author_sort | Kunhee Cho |
| collection | DOAJ |
| description | This paper proposes a test scenario design method that reflects the longitudinal characteristics of reality for effective verification of advanced driver assistance systems (ADAS) and autonomous driving systems (ADS). Since the target systems interact with the external environment differently from the existing vehicle control system, realistic and various verification scenarios are required for verification. The proposed method consists of a vehicle model for simulating the vehicle behavior and a driver model to actively respond to the driving environment. In particular, the driver model used a model predictive control (MPC) algorithm to reflect the characteristic of human drivers. The longitudinal driving characteristics of human drivers were derived through a large-scale driving database analysis and considered in the driver model. The proposed method was compared with an existing car-following model using computer simulations. It was confirmed that its longitudinal driving behavior is similar to that of human drivers and that various scenarios can be designed by changing the model parameters. |
| first_indexed | 2024-03-09T13:45:50Z |
| format | Article |
| id | doaj.art-0d89deafc1254bfc8fd979535abfe8e1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T13:45:50Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0d89deafc1254bfc8fd979535abfe8e12023-11-30T21:00:27ZengMDPI AGApplied Sciences2076-34172023-01-0113271610.3390/app13020716A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving SystemsKunhee Cho0Changwoo Park1Hyeongcheol Lee2Department of Electrical Engineering, Hanyang University, Seoul 04763, Republic of KoreaDepartment of Electrical Engineering, Hanyang University, Seoul 04763, Republic of KoreaDepartment of Electrical and Biomedical Engineering, Hanyang University, Seoul 04763, Republic of KoreaThis paper proposes a test scenario design method that reflects the longitudinal characteristics of reality for effective verification of advanced driver assistance systems (ADAS) and autonomous driving systems (ADS). Since the target systems interact with the external environment differently from the existing vehicle control system, realistic and various verification scenarios are required for verification. The proposed method consists of a vehicle model for simulating the vehicle behavior and a driver model to actively respond to the driving environment. In particular, the driver model used a model predictive control (MPC) algorithm to reflect the characteristic of human drivers. The longitudinal driving characteristics of human drivers were derived through a large-scale driving database analysis and considered in the driver model. The proposed method was compared with an existing car-following model using computer simulations. It was confirmed that its longitudinal driving behavior is similar to that of human drivers and that various scenarios can be designed by changing the model parameters.https://www.mdpi.com/2076-3417/13/2/716advanced driver assistance systems (ADAS)autonomous driving systems (ADS)model predictive control (MPC)scenario designdriver modelnaturalistic driving database |
| spellingShingle | Kunhee Cho Changwoo Park Hyeongcheol Lee A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems Applied Sciences advanced driver assistance systems (ADAS) autonomous driving systems (ADS) model predictive control (MPC) scenario design driver model naturalistic driving database |
| title | A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems |
| title_full | A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems |
| title_fullStr | A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems |
| title_full_unstemmed | A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems |
| title_short | A Study on Longitudinal Motion Scenario Design for Verification of Advanced Driver Assistance Systems and Autonomous Driving Systems |
| title_sort | study on longitudinal motion scenario design for verification of advanced driver assistance systems and autonomous driving systems |
| topic | advanced driver assistance systems (ADAS) autonomous driving systems (ADS) model predictive control (MPC) scenario design driver model naturalistic driving database |
| url | https://www.mdpi.com/2076-3417/13/2/716 |
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