Abstract
Understanding pedestrian behaviour and controlling interactions with pedestrians is of critical importance for autonomous vehicles, but remains a complex and challenging problem. This study infers pedestrian intent during possible road-crossing interactions, to assist autonomous vehicle decisions to yield or not yield when approaching them, and tests a simple heuristic model of intent on pedestrian-vehicle trajectory data for the first time. It relies on a heuristic approach based on the observed positions of the agents over time. The method can predict pedestrian crossing intent, crossing or stopping, with 96% accuracy by the time the pedestrian reaches the curbside, on the standard Daimler pedestrian dataset. This result is important in demarcating scenarios which have a clear winner and can be predicted easily with the simple heuristic, from those which may require more complex game-theoretic models to predict and control.
| Original language | English |
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| Title of host publication | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 3708-3713 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538670248 |
| DOIs | |
| Publication status | Published - Oct 2019 |
| Event | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand Duration: 27 Oct 2019 → 30 Oct 2019 |
Publication series
| Name | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
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Conference
| Conference | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
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| Country/Territory | New Zealand |
| City | Auckland |
| Period | 27/10/19 → 30/10/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Agent-Human Interactions
- Autonomous Vehicles
- Pedestrian Intention Crossing Estimation