An application of logit models in analysing the behaviour of pedestrians and car drivers on pedestrian crossings

Himanen, Veli; Kulmala, Risto

doi:10.1016/0001-4575(88)90003-6

Cited by 103 publications

(52 citation statements)

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“…Driving simulator studies showed the same results (e.g., Alexander, Barham, & Black, 2002). For pedestrians' crossing decisions, only a few studies addressed the issue of vehicle size, and found that larger vehicles went with fewer crossings (Himanen & Kulmala, 1988), or that critical gap size increased with vehicle length (Das, Manski, & Manuszak, 2005).…”

Section: Introductionmentioning

confidence: 79%

Time to Arrival Estimates, (Pedestrian) Gap Acceptance and the Size Arrival Effect

Petzoldt

Ngoc

Bogda

2017

Proceedings of the 9th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design: Dri

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Summary:Various studies have found that road users' acceptance of gaps to cross in front of another vehicle is dependent on the approaching vehicle's size, with smaller accepted gaps in front of smaller vehicles. At the same time, the so called size arrival effect is well known from research on time to collision / time to arrival estimates, where larger objects / vehicles tend to be judged as arriving earlier than smaller objects / vehicles. However, so far there has been no attempt to connect these two approaches in a single experiment to investigate whether the size arrival effect that is prevalent in time to arrival estimates can explain the variations in gap acceptance. In this experiment, twenty-seven participants observed video clips of approaching virtual vehicles of varying size (truck, bus, van, two different cars and a motorcycle) from a pedestrian's perspective, and were either required to indicate a crossing decision, or to estimate time to arrival. While, overall, the effect of vehicle size was clearly visible for both crossing decision and time to arrival estimates, there was also a clear exception in form of the motorcycle, which went with larger accepted gaps than some of the larger vehicles. This exception might be explained by the participants' subjective rating of perceived threat, which was rather high for the motorcycle. As (with the exception of the motorcycle), vehicle size and perceived threat correlated substantially, it is unclear at this stage to what degree these two factors contribute to perceived time to arrival and crossing decisions.

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Section: Introductionmentioning

confidence: 79%

Time to Arrival Estimates, (Pedestrian) Gap Acceptance and the Size Arrival Effect

Petzoldt

Ngoc

Bogda

2017

Proceedings of the 9th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design: Dri

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“…We argue that the acceptance of an alerting system is likely to be relatively high when, and only when, it issues alerts at times when and in situations in which drivers are likely to expect them (Källhammer et al, 2007). It should come as no surprise that these situations are contextually dependent (Himanen & Kumala, 1988;Schmidt & Färber, 2009) and involve violations of the field of safe travel.…”

Section: Discussionmentioning

confidence: 92%

“…The model by Himanen and Kumala (1988), the observations by Schmidt and Färber (2009), and the fact that we did not have knowledge of pedestrian demographics led us to focus this investigation on five factors: (a) the locale (urban, suburban, or rural), (b) pedestrian location, (c) direction of pedestrian motion, (d) the vehicle's path, and (e) the curvature of the road. Our aim was to identify factors that influence driver acceptance of alerts and that, by extension, should influence the alerting criteria used by the active safety system.…”

Section: The Research Agendamentioning

confidence: 99%

Assessing Contextual Factors That Influence Acceptance of Pedestrian Alerts by a Night Vision System

Källhammer

Smith²

2012

Hum Factors

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We investigated five contextual variables that we hypothesized would influence driver acceptance of alerts to pedestrians issued by a night vision active safety system to inform the specification of the system's alerting strategies. Background: Driver acceptance of automotive active safety systems is a key factor to promote their use and implies a need to assess factors influencing driver acceptance. Method: In a field operational test, 10 drivers drove instrumented vehicles equipped with a preproduction night vision system with pedestrian detection software. In a follow-up experiment, the 10 drivers and 25 additional volunteers without experience with the system watched 57 clips with pedestrian encounters gathered during the field operational test. They rated the acceptance of an alert to each pedestrian encounter. Results: Levels of rating concordance were significant between drivers who experienced the encounters and participants who did not. Two contextual variables, pedestrian location and motion, were found to influence ratings. Alerts were more accepted when pedestrians were close to or moving toward the vehicle's path. Conclusion: The study demonstrates the utility of using subjective driver acceptance ratings to inform the design of active safety systems and to leverage expensive field operational test data within the confines of the laboratory. Application: The design of alerting strategies for active safety systems needs to heed the driver's contextual sensitivity to issued alerts.

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“…Persson 11 reviewed on communication between road users, and found that the likelihood of a driver giving precedence increased if information of the pedestrian's intention was increased by way of combination of various forms of signs. Many other factors [12][13][14] were presented to have an influence to the drivers to give way to crossing pedestrians: the type of crossing and lane, distance between oncoming vehicle and pedestrian, orientation of pedestrian, number of pedestrians, pedestrian distance from the curb, etc. Logit models 13,15,16 were employed to analyze and evaluate the behavior of pedestrians and vehicle drivers at crosswalks, and it would be the first step for modeling the vehicle-pedestrian encounter process as well as the accident prediction.…”

Section: Introductionmentioning

confidence: 99%

“…Many other factors [12][13][14] were presented to have an influence to the drivers to give way to crossing pedestrians: the type of crossing and lane, distance between oncoming vehicle and pedestrian, orientation of pedestrian, number of pedestrians, pedestrian distance from the curb, etc. Logit models 13,15,16 were employed to analyze and evaluate the behavior of pedestrians and vehicle drivers at crosswalks, and it would be the first step for modeling the vehicle-pedestrian encounter process as well as the accident prediction. However, in the developing countries, the drivers always scramble for the limited space with pedestrians and deter them from having the right of way.…”

Section: Introductionmentioning

confidence: 99%

Situational Factors of Influencing Drivers to Give Precedence to Jaywalking Pedestrians at Signalized Crosswalk

Jiang¹,

Wang²,

Mao³

et al. 2011

IJCIS

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A large number of fatalities are caused by the vehicle-pedestrian accidents. Under a potential conflict between the vehicle and jaywalking pedestrian, giving precedence to the pedestrian will be a proper decision taken by the driver to avoid collision. Field traffic data has been collected by video recording and image processing at two signalized crosswalks. Vehicle speed performance in the single vehicle-pedestrian encounter and platoon vehicle-pedestrian encounter were analyzed for understanding the driver behavior in the conflict process. Binary logit model was proposed to estimate the drivers' giving precedence influenced by the situational factors and the model was validated to predict the drivers' choices accurately. The vehicle speed, pedestrian speed, pedestrian lateral distance and the vehicle longitudinal distance to the conflict point were proved to affect the drivers' choices in platoon driving. The research results would hopefully be helpful to the design of intelligent vehicles and pedestrian protection systems by the knowledge-based decision making process.

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An application of logit models in analysing the behaviour of pedestrians and car drivers on pedestrian crossings

Cited by 103 publications

References 1 publication

Time to Arrival Estimates, (Pedestrian) Gap Acceptance and the Size Arrival Effect

Time to Arrival Estimates, (Pedestrian) Gap Acceptance and the Size Arrival Effect

Assessing Contextual Factors That Influence Acceptance of Pedestrian Alerts by a Night Vision System

Situational Factors of Influencing Drivers to Give Precedence to Jaywalking Pedestrians at Signalized Crosswalk

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