Crossing at a red light: Behaviour of individuals and groups

Rosenbloom, Tova

doi:10.1016/j.trf.2009.05.002

Cited by 231 publications

(145 citation statements)

References 20 publications

Supporting

Mentioning

125

Contrasting

Unclassified

Order By: Relevance

“…Concerning pedestrian behavior when they are alone or in a group, Rosenbloom (2009) showed that the number of males who cross the street during red light is higher than the number of females, but hypothesis about the higher probability of pedestrian crossing the street during red light if others are already crossing the street, compared to the probability that a pedestrian will start crossing the street when other pedestrians are waiting for the green light, was not confirmed.…”

Section: Introductionmentioning

confidence: 92%

Pedestrian Risk at the Signalized Pedestrian Crossing Equipped With Countdown Display

Vujanic¹,

Pešić²,

Antić³

et al. 2014

IJTTE

View full text Add to dashboard Cite

Abstract:In this paper we proposed method for assessing pedestrian risk at the signalized pedestrian crossing equipped with counter. Results showed that 17.5% of pedestrians were at high risk and male pedestrians are more often in dangerous situation (20.4%) than female pedestrians (14.4%). About 3% of all examined pedestrians created conflict situations, more frequently in first 5 seconds and last 5 seconds of red light phase (79.7% of all offenders), but the risk that pedestrians will create a conflict situation were higher in other time of red light phase. Analysis of pedestrians' behavior at pedestrian crossings equipped with countdown display could point to potentially safety problems for pedestrians and those analysis could give direction for proposing and implementing adequate countermeasures. Also, numerically defined pedestrian accident risk could assess road safety level for pedestrians and show accident occurrence probability.

show abstract

Section: Introductionmentioning

confidence: 92%

Pedestrian Risk at the Signalized Pedestrian Crossing Equipped With Countdown Display

Vujanic¹,

Pešić²,

Antić³

et al. 2014

IJTTE

View full text Add to dashboard Cite

show abstract

“…As identified in a wide range of literature, and in this research, the analysis on the VE index and the CT index drew upon different age groups, with a special focus on children and aged pedestrians, people with special needs [42], gender [43], the presence of traffic signals [35,44], traffic conditions such as traffic volumes and widths [45,46], and a group effect [43]. These factors have been used as explanatory variables in analysing the two indices.…”

Section: Data Collectionmentioning

confidence: 99%

Pedestrian Crossing Environments in an Emerging Chinese City: Vehicle Encountering, Seamless Walking, and Sensory Perception Perspectives

Kim¹,

Mateo-Babiano²

2018

Sustainability

View full text Add to dashboard Cite

Abstract:While pedestrian crossings play a vital role in providing seamless mobility for pedestrians, they have also continually been spaces of negotiation, contestation, and conflicts between and among different users. Several evidences have shown that such conflict has always been costly, risky, and even fatal to pedestrians. This research aims to assess the pedestrian crossing from an operational perspective in one emerging Chinese city, Suzhou. To evaluate, this research has developed three indices associated with vehicle encountering (VE index), crossing time (CT index) and H-index which refers to audio-sensory perception or a count on the number of horns. This research used video and audio recordings on sample pedestrian crossings. Pedestrians encountered 1.16 vehicles on average when crossing at the sample roads. The average CT index was 1.19 signifying that pedestrians waited for 19% more than their seamless walking when there was no pedestrian crossing. The H index was 5.8 on average at peak time, meaning that there were 5.8 horns (Hs) from vehicles every one minute or approximately one H per every 10 s at a pedestrian crossing. The analysis of these three indices was strengthened by multilevel regression and multi-variable regression analyses. The paper concludes with insights on how the level of safety of inferior walking environments associated with ambiguous traffic rules, vehicle-prioritised traffic behaviours and passive roles of traffic police officers can be improved.

show abstract

“…It often changes according to the surroundings. Nevertheless, pedestrians naturally adapt to their surroundings [16]. The mean accepted gap for pedestrian to make a cross is estimated to be 8 seconds [17].…”

Section: Literature Overviewmentioning

confidence: 99%

Crossing Behaviour of Pedestrians Along Urban Streets in Malaysia

et al. 2017

View full text Add to dashboard Cite

Abstract. Road crossings are considered as an unavoidable part of walking in which the desirable route of pedestrians interacts with vehicles. These interactions may expose the pedestrians to risks or delays. In Malaysia, road accident statistics show that pedestrian casualties are fairly high. Inappropriate gap acceptance when pedestrians cross roads is a main contributing element to this situation. In this context, the purpose of this study was to develop realistic models for pedestrian road crossing behaviour using the regression technique for mid-block street crossing. A choice model was produced to capture the decision making process of pedestrians whereas rejected or accepted vehicular gaps was based on the discrete choice theory. Gap acceptance data under real mix traffic conditions was collected using video camera on a typical unsignalised two lane one way urban street section in the city center of Kuala Lumpur, Malaysia. The lognormal regression model developed for the crossing behaviour model shows that traffic speed, pedestrian waiting time, gender, crossing distance, age group, frequency of attempts and pedestrian number are the significant factors which are able to predict 77.0% of variance or changes in accepted gap size at 0.05 significance level. Higher traffic speed, lower waiting time, being a male, wider crossing distance, older age group, lower frequency of attempts and higher number of pedestrian were found to influence pedestrians to accept a bigger gap size. The binary logistic regression developed for the crossing choice model was found to be influenced by traffic speed, driver yield, pedestrian number and age group. Furthermore, lower traffic speed, willingness of drivers to slow down, more pedestrian crossings at the same time and a younger age group lead to a higher chance or probability of crossing roads. The model was validated again using 100 isolated samples and an accuracy of 98% was obtained compared to the calibrated model which yielded an accuracy of 98.9%.

show abstract

Crossing at a red light: Behaviour of individuals and groups

Cited by 231 publications

References 20 publications

Pedestrian Risk at the Signalized Pedestrian Crossing Equipped With Countdown Display

Pedestrian Risk at the Signalized Pedestrian Crossing Equipped With Countdown Display

Pedestrian Crossing Environments in an Emerging Chinese City: Vehicle Encountering, Seamless Walking, and Sensory Perception Perspectives

Crossing Behaviour of Pedestrians Along Urban Streets in Malaysia

Contact Info

Product

Resources

About