Development of a Cooperative On-Demand Intersection Assistant
In this paper, we present our recently introduced “assistance on demand (AOD)” concept, which allows the driver to request assistance via speech whenever he or she deems it appropriate. The target scenario we currently investigate is turning left from a subordinate road in dense urban traffic. We fi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Society of Automotive Engineers of Japan, Inc.
2019-04-01
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| Series: | International Journal of Automotive Engineering |
| Online Access: | https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194101/_article/-char/ja |
| _version_ | 1797356806226313216 |
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| author | Martin Heckmann Heiko Wersing Dennis Orth Dorothea Kolossa Nadja Schömig Mark Dunn |
| author_facet | Martin Heckmann Heiko Wersing Dennis Orth Dorothea Kolossa Nadja Schömig Mark Dunn |
| author_sort | Martin Heckmann |
| collection | DOAJ |
| description | In this paper, we present our recently introduced “assistance on demand (AOD)” concept, which allows the driver to request assistance via speech whenever he or she deems it appropriate. The target scenario we currently investigate is turning left from a subordinate road in dense urban traffic. We first compare our system in a driving simulator study to driving without assistance or with visual assistance. The results show that drivers clearly prefer our speech-based AOD approach. Next, we investigate the differences between drivers’ left-turn behaviour in a driving simulator. The results of this investigation show that there are large inter-individual differences. Based on these results, we present another driving simulator study, where participants can compare manual driving to driving with a default and a personalized AOD system. The results of this second study show that the personalization very notably improves the acceptance of the system. Given the choice between driving with any of the AOD variants and manual driving, 87.5% of the participants preferred driving with the AOD. Finally, we present an evaluation of the AOD system in a prototype vehicle in real urban traffic. |
| first_indexed | 2024-03-08T14:32:54Z |
| format | Article |
| id | doaj.art-5bd7b67b101c43e8b45bc73e25f36959 |
| institution | Directory Open Access Journal |
| issn | 2185-0992 |
| language | English |
| last_indexed | 2024-03-08T14:32:54Z |
| publishDate | 2019-04-01 |
| publisher | Society of Automotive Engineers of Japan, Inc. |
| record_format | Article |
| series | International Journal of Automotive Engineering |
| spelling | doaj.art-5bd7b67b101c43e8b45bc73e25f369592024-01-12T07:12:58ZengSociety of Automotive Engineers of Japan, Inc.International Journal of Automotive Engineering2185-09922019-04-0110217518310.20485/jsaeijae.10.2_175Development of a Cooperative On-Demand Intersection AssistantMartin Heckmann0Heiko Wersing1Dennis Orth2Dorothea Kolossa3Nadja Schömig4Mark Dunn5Honda Research Institute Europe GmbHHonda Research Institute Europe GmbHInstitute of Communication Acoustics, Ruhr-Universität Bochum UniversitätsstrInstitute of Communication Acoustics, Ruhr-Universität Bochum UniversitätsstrWuerzburg Institute for Traffic Sciences GmbH (WIVW)Honda Research Institute Europe GmbHIn this paper, we present our recently introduced “assistance on demand (AOD)” concept, which allows the driver to request assistance via speech whenever he or she deems it appropriate. The target scenario we currently investigate is turning left from a subordinate road in dense urban traffic. We first compare our system in a driving simulator study to driving without assistance or with visual assistance. The results show that drivers clearly prefer our speech-based AOD approach. Next, we investigate the differences between drivers’ left-turn behaviour in a driving simulator. The results of this investigation show that there are large inter-individual differences. Based on these results, we present another driving simulator study, where participants can compare manual driving to driving with a default and a personalized AOD system. The results of this second study show that the personalization very notably improves the acceptance of the system. Given the choice between driving with any of the AOD variants and manual driving, 87.5% of the participants preferred driving with the AOD. Finally, we present an evaluation of the AOD system in a prototype vehicle in real urban traffic.https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194101/_article/-char/ja |
| spellingShingle | Martin Heckmann Heiko Wersing Dennis Orth Dorothea Kolossa Nadja Schömig Mark Dunn Development of a Cooperative On-Demand Intersection Assistant International Journal of Automotive Engineering |
| title | Development of a Cooperative On-Demand Intersection Assistant |
| title_full | Development of a Cooperative On-Demand Intersection Assistant |
| title_fullStr | Development of a Cooperative On-Demand Intersection Assistant |
| title_full_unstemmed | Development of a Cooperative On-Demand Intersection Assistant |
| title_short | Development of a Cooperative On-Demand Intersection Assistant |
| title_sort | development of a cooperative on demand intersection assistant |
| url | https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194101/_article/-char/ja |
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