Driver-Pedestrian Perceptual Models Demonstrate Coupling: Implications for Vehicle Automation-Reference-Cited by-同舟云学术

Driver-Pedestrian Perceptual Models Demonstrate Coupling: Implications for Vehicle Automation

Published:2022-08 Issue:4 Volume:52 Page:557-566
ISSN:2168-2291
Container-title:IEEE Transactions on Human-Machine Systems
language:
Short-container-title:IEEE Trans. Human-Mach. Syst.

Author:

Domeyer Joshua E.¹^ORCID,Lee John D.²^ORCID,Toyoda Heishiro¹,Mehler Bruce³^ORCID,Reimer Bryan³^ORCID

Affiliation:

1. Toyota Collaborative Safety Research Center, Toyota Motor North America, Ann Arbor, MI, USA

2. Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA

3. MIT Center for Transportation and Logistics, Cambridge, MA, USA

Funder

Toyota Collaborative Safety Research Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Signal Processing,Control and Systems Engineering,Human Factors and Ergonomics

Link

http://xplorestaging.ieee.org/ielx7/6221037/9829905/09745572.pdf?arnumber=9745572

Reference74 articles.

1. TITAN: Future Forecast Using Action Priors

2. Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction

3. PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction

4. Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior

5. Computational modeling of driver pre-crash brake response, with and without off-road glances: Parameterization using real-world crashes and near-crashes

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