Underestimation tendencies of vehicle speed by pedestrians when crossing unmarked roadway-Reference-Cited by-同舟云学术

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Underestimation tendencies of vehicle speed by pedestrians when crossing unmarked roadway

Published:2020-08 Issue: Volume:143 Page:105586
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Papić Zoran,Jović Andrijana,Simeunović Milan,Saulić Nenad,Lazarević Milan

Funder

Ministry of Education, Science and Technological Development of the Republic of Serbia

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference35 articles.

1. Exploration of pedestrian gap-acceptance behavior at selected locations;Brewer;Transp. Res. Rec.,2006

2. Bright cars and outsiders: evidence of asymmetric estimates in vehicular speeds;Cherry;J. Appl. Social Psychol.,2001

3. Statistical Power Analysis for the Behavioral Sciences;Cohen,1988

4. Estimating the speed of vehicles: the influence of stereotypes;Davies;Psychol. Crime Law,2009

5. The influence of car and driver stereotypes on attributions of vehicle speed, position on the road and culpability in a road accident scenario;Davies;Legal Criminol. Psychol.,2005

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2. Analyzing the Effects of Healthy Older Adults’ Optimism and Executive Function on Hazardous Road-Crossing Using a Bayesian Generalized Linear Mixed Model;Transportation Research Record: Journal of the Transportation Research Board;2024-08-02

3. Impacts of brightness contrast, road environment complexity, travel direction and judgement type on speed perception errors among older adult pedestrians' road‐crossing decision‐making;Australasian Journal on Ageing;2024-07-22

4. Application of immersive virtual reality for assessing chronic neglect in individuals with stroke: the immersive virtual road-crossing task;Journal of Clinical and Experimental Neuropsychology;2024-03-15

5. Prediction of jaywalker-vehicle conflicts based on encoder-decoder framework utilizing multi-source data;Accident Analysis & Prevention;2024-02

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