Tian, K. orcid.org/0000-0002-1412-7964, Markkula, G. orcid.org/0000-0003-0244-1582, Wei, C. orcid.org/0000-0002-4565-509X et al. (5 more authors) (2024) Deconstructing Pedestrian Crossing Decisions in Interactions With Continuous Traffic: An Anthropomorphic Model. IEEE Transactions on Intelligent Transportation Systems, 25 (3). pp. 2466-2478. ISSN 1524-9050
Abstract
Increasing attention has been drawn to computational pedestrian behavior models aimed at understanding the interaction mechanisms between pedestrians and vehicles. Nevertheless, existing research lacks exploration of the underlying behavioral mechanisms of pedestrian crossing decisions, which leads to unrealistic modeling results. In particular, when dealing with continuous traffic flow scenarios, the concept of waiting time is frequently used to account for all intricate traffic flow effects. Moreover, very few studies considered the time-dynamic nature of crossing decisions. To address these research limitations, this study deconstructs pedestrian crossing decisions at uncontrolled intersections with continuous traffic flow through a cognitive process and proposes an anthropomorphic crossing decision model. Specifically, we propose a novel visual collision cue-based crossing decision-initiation model to characterize time-dynamic crossing decisions. In light of the risk-aversion theory, a traffic gap comparison strategy is put forward to explain and model pedestrian waiting behavior in traffic flow. Two datasets collected from a CAVE-based immersive pedestrian simulator are applied to calibrate and validate the model. The proposed model accurately predicts pedestrian crossing decisions across all traffic scenarios. The modeling performance is significantly enhanced by considering the proposed traffic gap comparison strategy. Moreover, the model accurately captures the timing of crossing decisions. This work concisely demonstrates how pedestrians dynamically adapt their crossings in continuous traffic based on visual collision cues, potentially offering insights into modeling pedestrian-vehicle interactions or serving as a tool to realize anthropomorphic pedestrian crossing decisions in simulators.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Pedestrian-vehicle interaction; road crossing decision; anthropomorphic model; traffic flow |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Safety and Technology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Mar 2024 16:37 |
Last Modified: | 23 May 2024 14:10 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/tits.2023.3323010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:210255 |