Intercepting a moving traffic gap while avoiding collision with lead and trail vehicles: Gap-related and boundary-related influences on drivers’ speed regulations during approach to an intersection

Louveton, Nicolas; Montagne, Gilles; Berthelon, Catherine; Bootsma, Reinoud J.

doi:10.1016/j.humov.2012.07.010

Cited by 13 publications

(36 citation statements)

References 32 publications

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“…This task allows us to study synchronization of self and object movement independent of movement initiation and gap-selection factors (see also Louveton et al, 2012a, 2012b). Our initial study examined how well 10- and 12-year-old children and adults adjust their movement to intercept a moving gap (Chihak et al, 2010).…”

Section: Intercepting Moving Gaps On the Runmentioning

confidence: 99%

“…Do they perceive the gap directly or do they use the temporal and spatial positions of the lead and tail vehicles to construct the gap? Both the gap and vehicles that define the gap boundaries matter for performance in an interception task (Louveton et al, 2012b). However, gap-interception tasks (Chihak et al, 2010, 2014; Louveton et al, 2012a, 2012b) do not tell us what information perceivers use when deciding about opportunities for action that are embedded in a stream of possible opportunities.…”

Section: Timing Is (Almost) Everythingmentioning

confidence: 99%

“…Both the gap and vehicles that define the gap boundaries matter for performance in an interception task (Louveton et al, 2012b). However, gap-interception tasks (Chihak et al, 2010, 2014; Louveton et al, 2012a, 2012b) do not tell us what information perceivers use when deciding about opportunities for action that are embedded in a stream of possible opportunities. Researchers could address this question by examining eye movements to determine how riders modulate their attention as they assess the crossability of approaching gaps.…”

Section: Timing Is (Almost) Everythingmentioning

confidence: 99%

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How Do Children Perceive and Act on Dynamic Affordances in Crossing Traffic‐Filled Roads?

Plumert

Kearney

2014

Child Dev Perspectives

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Successfully perceiving and acting on dynamic affordances is critical for children and adults to function. In our work, we look at how children cross roads as a model for understanding how they learn to perceive and act on dynamic affordances. Ten- to 14-year-old children and adults ride an interactive bicycling simulator through an immersive virtual environment where they cross intersections with continuous cross traffic. We consistently find developmental and individual differences in children’s ability to tightly time their entry into the roadway relative to the lead car in the gap. Given that children do not adjust their gap choices to match their less precise timing abilities, children take more risks when crossing roads than adults. We conclude by discussing possible reasons for these developmental differences in movement timing.

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Section: Intercepting Moving Gaps On the Runmentioning

confidence: 99%

Section: Timing Is (Almost) Everythingmentioning

confidence: 99%

Section: Timing Is (Almost) Everythingmentioning

confidence: 99%

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How Do Children Perceive and Act on Dynamic Affordances in Crossing Traffic‐Filled Roads?

Plumert

Kearney

2014

Child Dev Perspectives

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“…Consider the task of passing through a lane of pedestrian traffic (see Figure 6A), which one might encounter at an intersection in a crowded airport terminal or shopping mall. In previous studies on passing through a lane of traffic, it was common to treat gaps between obstacles as targets to be intercepted (Chihak et al, 2010; Louveton et al, 2012a,b). By characterizing the situation as a target interception task, the BA model can be considered a possible strategy for regulating approach speed to an intersection.…”

Section: Scaling Up To Complex Tasksmentioning

confidence: 99%

Guiding locomotion in complex, dynamic environments

Fajen¹

2013

Front. Behav. Neurosci.

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Locomotion in complex, dynamic environments is an integral part of many daily activities, including walking in crowded spaces, driving on busy roadways, and playing sports. Many of the tasks that humans perform in such environments involve interactions with moving objects—that is, they require people to coordinate their own movement with the movements of other objects. A widely adopted framework for research on the detection, avoidance, and interception of moving objects is the bearing angle model, according to which observers move so as to keep the bearing angle of the object constant for interception and varying for obstacle avoidance. The bearing angle model offers a simple, parsimonious account of visual control but has several significant limitations and does not easily scale up to more complex tasks. In this paper, I introduce an alternative account of how humans choose actions and guide locomotion in the presence of moving objects. I show how the new approach addresses the limitations of the bearing angle model and accounts for a variety of behaviors involving moving objects, including (1) choosing whether to pass in front of or behind a moving obstacle, (2) perceiving whether a gap between a pair of moving obstacles is passable, (3) avoiding a collision while passing through single or multiple lanes of traffic, (4) coordinating speed and direction of locomotion during interception, (5) simultaneously intercepting a moving target while avoiding a stationary or moving obstacle, and (6) knowing whether to abandon the chase of a moving target. I also summarize data from recent studies that support the new approach.

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“…Whereas the discrete-response motion-extrapolation paradigm has been used in many studies to better understand the underlying perceptual processes, to our knowledge only a few studies decided to preserve the perceptual-motor dialogue when studying intersectioncrossing behavior. The work of Chihak et al (2010Chihak et al ( , 2014 and that of Louveton et al (2012aLouveton et al ( , 2012b) constitute rather isolated attempts to study intersection-crossing behavior without separating the perceptual-motor mechanisms involved. While the former were interested in the perceptual-motor developmental changes accompanying the intersection-crossing behavior of cyclists, the latter focused on the mechanisms underlying the intersection-crossing behavior of adult drivers.…”

Section: Introductionmentioning

confidence: 99%

Judging arrival times of incoming traffic vehicles is not a prerequisite for safely crossing an intersection: Differential effects of vehicle size and type in passive judgment and active driving tasks

et al. 2017

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Using a fixed-base driving simulator we compared the effects of the size and type of traffic vehicles (i.e., normal-sized or double-sized cars or motorcycles) approaching an intersection in two different tasks. In the perceptual judgment task, passively moving participants estimated when a traffic vehicle would reach the intersection for actual arrival times (ATs) of 1, 2, or 3s. In line with earlier findings, ATs were generally underestimated, the more so the longer the actual AT. Results revealed that vehicle size affected judgments in particular for the larger actual ATs (2 and 3s), with double-sized vehicles then being judged as arriving earlier than normal-sized vehicles. Vehicle type, on the other hand, affected judgments at the smaller actual ATs (1 and 2s), with cars then being judged as arriving earlier than motorcycles. In the behavioral task participants actively drove the simulator to cross the intersection by passing through a gap in a train of traffic. Analyses of the speed variations observed during the active intersection-crossing task revealed that the size and type of vehicles in the traffic train did not affect driving behavior in the same way as in the AT judgment task. First, effects were considerably smaller, affecting driving behavior only marginally. Second, effects were opposite to expectations based on AT judgments: driver approach speeds were smaller (rather than larger) when confronted with double-sized vehicles as compared to their normal-sized counterparts and when confronted with cars as compared to motorcycles. Finally, the temporality of the effects was different on the two tasks: vehicle size affected driver approach speed in the final stages of approach rather than early on, while vehicle type affected driver approach speed early on rather than later. Overall, we conclude that the active control of approach to the intersection is not based on successive judgments of traffic vehicle arrival times. These results thereby question the general belief that arrival time estimates are crucial for safe interaction with traffic.

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Intercepting a moving traffic gap while avoiding collision with lead and trail vehicles: Gap-related and boundary-related influences on drivers’ speed regulations during approach to an intersection

Cited by 13 publications

References 32 publications

How Do Children Perceive and Act on Dynamic Affordances in Crossing Traffic‐Filled Roads?

How Do Children Perceive and Act on Dynamic Affordances in Crossing Traffic‐Filled Roads?

Guiding locomotion in complex, dynamic environments

Judging arrival times of incoming traffic vehicles is not a prerequisite for safely crossing an intersection: Differential effects of vehicle size and type in passive judgment and active driving tasks

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