Crossing roads safely: An experimental study of age differences in gap selection by pedestrians

Oxley, Jennifer Anne; Ihsen, Elfriede; Fildes, Brian; Charlton, Judith Lynne; Day, R. H.

doi:10.1016/j.aap.2005.04.017

Cited by 320 publications

(238 citation statements)

References 13 publications

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“…This result is in line with what could be expected in the light of the age-related decrease in walking speed (fastest as well as self-paced) observed in prior work (Carmeli et al, 2000;Lobjois and Cavallo, 2007;Oxley et al, 2005) and indicates that in this simple street-crossing situation (single lane, oneway traffic) older adults were able, to a certain extent, to take their changing sensory and motor abilities into account when making a decision. The efficiency of this compensatory behavior was demonstrated by the similar safety margins and unsafe-decision rates found here for the three populations of pedestrians.…”

Section: Decisionssupporting

confidence: 91%

“…For instance, Oxley et al (1997) showed that older pedestrians adopted less safe road crossing strategies on two-way undivided roads than on one-way roads. In similar vein, older pedestrians were more impaired than younger ones when the speed of approaching vehicles was systematically varied, as they consistently accepted shorter and shorter gaps as speed increased (Lobjois & Cavallo, 2007, 2009Oxley et al 2005). This turned into unsafe crossing decisions at high speeds and missed crossing opportunities when car speeds were low.…”

Section: Introductionmentioning

confidence: 83%

“…Until recently, much of the research examining gap acceptance was based on estimation tasks, either in children (e.g., Connelly et al 1996Connelly et al , 1998Pitcairn and Edlmann, 2000) or elderly pedestrians (e.g., Lobjois and Cavallo, 2007;Oxley et al, 2005). Estimation tasks require participants to give a verbal response or to press a button to indicate whether they would cross the road in front of oncoming traffic.…”

Section: Methodsmentioning

confidence: 99%

“…Past studies have also dealt with the effects on older pedestrians' crossing behavior of exogenous factors such as oncoming vehicles speed (e.g., Lobjois & Cavallo, 2007, 2009Oxley et al, 2005) or crossing complexity (e.g., one way versus two-way roads; Oxley et al, 1997). Little is known about the causes of accidents in elderly pedestrians and more importantly about the environmental factors that affect or improve the behaviour of elderly people in street crossing.…”

Section: Introductionmentioning

confidence: 99%

“…Little is known about the causes of accidents in elderly pedestrians and more importantly about the environmental factors that affect or improve the behaviour of elderly people in street crossing. Research addressing the impact of a traffic stream on crossing behavior of elderly people is still scarce, as most of the research has been conducted with only one or two approaching vehicles Lobjois & Cavallo, 2007, 2009Oxley et al, 2005;te Velde et al, 2005). Thus the goal of this study was to assess the effect of a traffic stream on gap acceptance and crossing decisions of younger and older pedestrians.…”

Section: Introductionmentioning

confidence: 99%

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The effects of age and traffic density on street-crossing behavior

Lobjois¹,

Benguigui

Cavallo³

2013

Accident Analysis & Prevention

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Please cite this article as: Lobjois, R., Benguigui, N., Cavallo, V., The effects of age and traffic density on street-crossing behavior, Accident Analysis and Prevention (2010), doi:10.1016/j.aap.2012 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A c c e p t e d M a n u s c r i p t AbstractPast research has shown that road users accept shorter time gaps when the waiting time/number of vehicles they let pass before attempting to merge into the traffic increases.While elderly pedestrians are known to be an extremely vulnerable group of road users, very few studies dealt with the effect of environmental constraints and crossing complexity on this population's safety. The present study aimed at determining whether or not street-crossing decisions and behavior of younger and older pedestrians were differently affected by a traffic flow. In an interactive street-crossing task, we assessed whether mean time gap and crossing decisions depended on the position of the gap pedestrians selected into the traffic stream.Results revealed that irrespective of their age pedestrians accepted a smaller time gap when they chose the second interval of the traffic compared to the first one. Contrasting with previous hypotheses, this traffic-related behavior was not accompanied by an increase in the decisions risk. The findings also showed that the transition threshold from rejecting to accepting time gaps was shorter when the second interval was selected compared to the first one. This increment in task constraints might help younger and older pedestrians alike to perceive action possibilities more accurately and to be better attuned to traffic conditions by comparing gaps between each other. This opens an interesting perspective in the understanding and the training of the ability of elderly road users to remain accurate in their judgements.

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Section: Decisionssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 83%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effects of age and traffic density on street-crossing behavior

Lobjois¹,

Benguigui

Cavallo³

2013

Accident Analysis & Prevention

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Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles

Crosato,

Tian,

Shum

et al. 2023

Advanced Intelligent Systems

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Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that focuses on the development of autonomous vehicles (AVs) that are capable of interacting safely and efficiently with human road users. This is a challenging task, as it requires the AV to be able to understand and predict the behaviour of human road users. In this literature review, the current state of IAAD research is surveyed. Commencing with an examination of terminology, attention is drawn to challenges and existing models employed for modeling the behaviour of drivers and pedestrians. Next, a comprehensive review is conducted on various techniques proposed for interaction modeling, encompassing cognitive methods, machine‐learning approaches, and game‐theoretic methods. The conclusion is reached through a discussion of potential advantages and risks associated with IAAD, along with the illumination of pivotal research inquiries necessitating future exploration.

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Pedestrian safety in patients with Parkinson's disease: A case‐control study

et al. 2017

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Background Patients with Parkinson’s disease (PD) experience debilitating motor symptoms as well as non-motor symptoms, such as cognitive dysfunction and sleep disorders. This constellation of symptoms has the potential to negatively influence pedestrian safety. Objective Investigate the association of motor symptoms, daytime sleepiness, impaired vigilance, and cognitive dysfunction on pedestrian behavior in patients with PD and healthy older adults. Methods: Fifty PD and 25 control participants were evaluated within a virtual reality pedestrian environment and completed assessments of motor performance, daytime sleepiness (Epworth Sleepiness Scale), vigilance (psychomotor vigilance task), and visual processing speed (Useful Field of View: UFOV®) outside of the virtual reality environment. The primary outcome measure was Time to Contact (TTC), defined as the time remaining until a participant would have been hit by an approaching vehicle while crossing the virtual street. Results The virtual reality pedestrian environment was feasible in all participants. Patients with PD demonstrated riskier pedestrian behavior compared to controls. Among PD participants, walking speed, objective measures of vigilance, and visual processing speed were correlated with pedestrian behavior, with walking speed being the strongest predictor of Time to Contact, explaining 48% of the variance. Vigilance explained an additional 8% of the variance. In controls, vigilance was also important for street-crossing safety, but older age was the most robust predictor of pedestrian safety. Conclusion Walking speed is associated with unsafe pedestrian behavior in patients with PD. In contrast, age was the strongest predictor of pedestrian safety in healthy older adults.

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Crossing roads safely: An experimental study of age differences in gap selection by pedestrians

Cited by 320 publications

References 13 publications

The effects of age and traffic density on street-crossing behavior

The effects of age and traffic density on street-crossing behavior

Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles

Pedestrian safety in patients with Parkinson's disease: A case‐control study

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