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Abstract
Research shows that about half of all motorcycle collisions with other vehicles were caused by the accident opponent, typically a passenger car. This study aimed to assess the effect of simulator training on improving car drivers’ perceptibility of motorcycles and thereby addressing this frequent type of motorcycle accident from the perspective of the initiator. For this purpose, a training program with different methods was conducted and tested in a driving simulator with 80 learner drivers aged between 15 and 27 years, assigned to a control group and three training groups: variable priority, equal priority, and equal priority with warning. The conflict scenarios were determined based on an analysis of motorcycle–car accidents. The variable priority training program resulted in better perceptibility of motorcycles as compared to the equal priority training program and equal priority with warning in two out of four test setups, i.e., urban roads with high contrast between motorcycle and the driving environment and on rural roads with a low contrast. Most participants rated each training method in the driving simulator as useful and would recommend it to other learner drivers. These results are important because they show that simulator training has a positive effect on the motorcycle detection performance of learner drivers. The early perception of motorcycles in car drivers is essential for preventing collisions between cars and motorcycles.
Original language | English |
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Article number | 5283 |
Number of pages | 16 |
Journal | Sustainability |
Volume | 14 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 May 2022 |
Keywords
- driving education
- driving simulator
- human factors
- motorcycle safety
- road safety analysis
- vulnerable road users
ASJC Scopus subject areas
- Automotive Engineering
- Environmental Science (miscellaneous)
- Geography, Planning and Development
- Energy Engineering and Power Technology
- Management, Monitoring, Policy and Law
- Renewable Energy, Sustainability and the Environment
Fields of Expertise
- Mobility & Production
Treatment code (Nähere Zuordnung)
- Experimental
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DVS: Vehicle Dynamics
Koglbauer, I. V., Lex, C., Shao, L., Semmer, M., Rogic, B., Peer, M., Hackl, A., Sternat, A. S., Schabauer, M., Samiee, S., Eichberger, A., Ager, M., Malić, D., Wohlfahrter, H., Scherndl, C., Magosi, Z. F., Orucevic, F., Puščul, D., Arefnezhad, S., Karoshi, P., Schöttel, C. E., Pandurevic, A., Harcevic, A., Wellershaus, C., Li, H., Mihalj, T., Kanuric, T., Gu, Z., Wallner, D., De Cristofaro, F., Soboleva, K., Nalic, D., Bernsteiner, S., Kraus, H., Zhao, Y., Bodner, J., Bui, D. T., Hirschberg, W., Plöckinger, M. & Khoshnood Sarabi, N.
1/01/11 → 31/12/24
Project: Research area
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IMPMOD - Improved Perception of Motorcycle by Driving Simulator based Driving Education
1/10/16 → 1/10/17
Project: Research project