International Conference on Transportation and Development 2020
Application Evaluation of Self-Explaining Intersections Based on Visual Information
Publication: International Conference on Transportation and Development 2020
ABSTRACT
More than 80% of the traffic information acquired by drivers comes from the visual channel. Therefore, visual information provided by traffic environment has great effects on driving safety. Data of drivers’ driving trajectories, driving velocities, and eye movement characteristics in experimental scenes with different traffic environmental visual information and levels of self-explaining characteristic were collected via a driving simulator and eye tracker experiment. This paper analyzed the effects of visual information on drivers’ behaviors, evaluated the safety of self-explaining roads, and designed the methods to improve the capacity of fault tolerance and safety of the self-explaining intersection.
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Information & Authors
Information
Published In
International Conference on Transportation and Development 2020
Pages: 83 - 94
Editor: Guohui Zhang, Ph.D., University of Hawaii
ISBN (Online): 978-0-7844-8314-5
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Aug 31, 2020
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