Effects of Marking Automated Vehicles on Human Drivers on Highways
Due to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as car...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/11/6/286 |
| _version_ | 1797566793978478592 |
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| author | Tanja Fuest Alexander Feierle Elisabeth Schmidt Klaus Bengler |
| author_facet | Tanja Fuest Alexander Feierle Elisabeth Schmidt Klaus Bengler |
| author_sort | Tanja Fuest |
| collection | DOAJ |
| description | Due to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as carefully as human learners do. In the same way that driving-school vehicles tend to be marked in Germany, markings for automated vehicles could also prove advantageous. To this end, a simulation study with 40 participants was conducted. All participants experienced three different highway scenarios, each with and without a marked automated vehicle. One scenario was based around some roadworks, the next scenario was a traffic jam, and the last scenario involved a lane change. Common to all scenarios was that the automated vehicles strictly adhered to German highway regulations, and therefore moved in road traffic somewhat differently to human drivers. After each trial, we asked participants to rate how appropriate and disturbing the automated vehicle’s driving behavior was. We also measured objective data, such as the time of a lane change and the time headway. The results show no differences for the subjective and objective data regarding the marking of an automated vehicle. Reasons for this might be that the driving behavior itself is sufficiently informative for humans to recognize an automated vehicle. In addition, participants experienced the automated vehicle’s driving behavior for the first time, and it is reasonable to assume that an adjustment of the humans’ driving behavior would take place in the event of repeated encounters. |
| first_indexed | 2024-03-10T19:32:32Z |
| format | Article |
| id | doaj.art-3e8c6931c50c4746bd843824794cb276 |
| institution | Directory Open Access Journal |
| issn | 2078-2489 |
| language | English |
| last_indexed | 2024-03-10T19:32:32Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj.art-3e8c6931c50c4746bd843824794cb2762023-11-20T02:00:08ZengMDPI AGInformation2078-24892020-05-0111628610.3390/info11060286Effects of Marking Automated Vehicles on Human Drivers on HighwaysTanja Fuest0Alexander Feierle1Elisabeth Schmidt2Klaus Bengler3Chair of Ergonomics, Technical University of Munich, 85748 Garching, GermanyChair of Ergonomics, Technical University of Munich, 85748 Garching, GermanyBMW Group, New Technologies, 85748 Garching, GermanyChair of Ergonomics, Technical University of Munich, 85748 Garching, GermanyDue to the short range of the sensor technology used in automated vehicles, we assume that the implemented driving strategies may initially differ from those of human drivers. Nevertheless, automated vehicles must be able to move safely through manual road traffic. Initially, they will behave as carefully as human learners do. In the same way that driving-school vehicles tend to be marked in Germany, markings for automated vehicles could also prove advantageous. To this end, a simulation study with 40 participants was conducted. All participants experienced three different highway scenarios, each with and without a marked automated vehicle. One scenario was based around some roadworks, the next scenario was a traffic jam, and the last scenario involved a lane change. Common to all scenarios was that the automated vehicles strictly adhered to German highway regulations, and therefore moved in road traffic somewhat differently to human drivers. After each trial, we asked participants to rate how appropriate and disturbing the automated vehicle’s driving behavior was. We also measured objective data, such as the time of a lane change and the time headway. The results show no differences for the subjective and objective data regarding the marking of an automated vehicle. Reasons for this might be that the driving behavior itself is sufficiently informative for humans to recognize an automated vehicle. In addition, participants experienced the automated vehicle’s driving behavior for the first time, and it is reasonable to assume that an adjustment of the humans’ driving behavior would take place in the event of repeated encounters.https://www.mdpi.com/2078-2489/11/6/286marking automated vehiclesautomated vehicles―human drivers interactionmixed trafficexplicit communicationexternal human-machine interface |
| spellingShingle | Tanja Fuest Alexander Feierle Elisabeth Schmidt Klaus Bengler Effects of Marking Automated Vehicles on Human Drivers on Highways Information marking automated vehicles automated vehicles―human drivers interaction mixed traffic explicit communication external human-machine interface |
| title | Effects of Marking Automated Vehicles on Human Drivers on Highways |
| title_full | Effects of Marking Automated Vehicles on Human Drivers on Highways |
| title_fullStr | Effects of Marking Automated Vehicles on Human Drivers on Highways |
| title_full_unstemmed | Effects of Marking Automated Vehicles on Human Drivers on Highways |
| title_short | Effects of Marking Automated Vehicles on Human Drivers on Highways |
| title_sort | effects of marking automated vehicles on human drivers on highways |
| topic | marking automated vehicles automated vehicles―human drivers interaction mixed traffic explicit communication external human-machine interface |
| url | https://www.mdpi.com/2078-2489/11/6/286 |
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