Pedestrian compliance and cross walking speed adaptation due to countdown timer installations: A self report study

Paschalidis, Evangelos; Politis, Ioannis; Basbas, Socrates; Lambrianidou, Polixeni

doi:10.1016/j.trf.2015.07.010

Cited by 36 publications

(21 citation statements)

References 20 publications

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“…In addition, culture is considered as another important factor impacting di erences in crossing behaviors [5]. Psychological factors such as comfort perception, willingness to bypass, conformity, carelessness, anxiety, and personal preference are also analyzed in previous studies [2,[8][9][10]. A few studies take alcohol use into account to analyze risk of pedestrian-motor vehicle collisions [6,7].…”

Section: Factors a Ecting Crossing Behavior Of Pedestrianmentioning

confidence: 99%

“…Data from video-based observation is used to analyze characteristics of crossings, including crossing speed, crossing pattern, etc., and quantify some factors of pedestrian attributes, tra c conditions and road conditions [1,[17][18][19][20]. Data from questionnaire surveys are mainly used to obtain pedestrian psychological factors, behavioral reasons, preferences and so on [2,8]. Applications of data are mainly divided into three categories: data of video recording used alone, data of questionnaire survey used alone, and the combination of them.…”

Section: Data Collectionmentioning

confidence: 99%

“…In this paper, data from questionnaire survey in which the scenes of pedestrians crossing the streets were augmented by respondents recalling their recent crossing experiences were mainly used to model pedestrian illegal crossings considering factors of pedestrian attributes, tra c conditions and road conditions. Additional data from video recordings were only [2], crowd size [3], clothing [3], luggage [4], cultural backgrounds [5], alcohol use [6,7], social psychology [2,[8][9][10], etc.…”

Section: Data Collectionmentioning

confidence: 99%

See 2 more Smart Citations

Analysis on Illegal Crossing Behavior of Pedestrians at Signalized Intersections Based on Bayesian Network

Zhang

2020

Journal of Advanced Transportation

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Pedestrians do not always comply with the crossing rules of when and/or where to cross the road at signalized intersections. This risky behavior tends to undermine greatly the effectiveness of safety countermeasures at such locations. Thus, it is very important to understand illegal behavior to develop more effective and targeting measures. In order to address the problem, this paper aimed to analyze characteristics of illegal crossings and their impact on behavior choice. Firstly, illegal crossing behaviors at signalized intersections were classified into two categories, including “crossing at a red light” and “crossing outside of a crosswalk.” Secondly, two sets of data were collected to understand the behaviors. One set of data was collected from video-based observation conducted at 3 signalized intersections in Guangzhou, China, capturing 3334 valid illegal crossing cases in total. Another set of data, from a questionnaire survey conducted online, resulted in 275 valid responses. Finally, presentational characteristics of illegal crossings at signalized intersection were analyzed and two Bayesian network-based behavior models were developed to investigate the characteristics and their impacts on the two types of illegal crossing behaviors, “crossing at a red light” and “crossing outside of a crosswalk,” respectively. Findings reveal that, (i) illegal crossings occur at various types of signalized intersections, with a higher probability for “crossing outside of a crosswalk” compared to “crossing at a red light;” (ii) Arc routing crossing has the highest probability to occur at signalized intersections compared to other types of out-side-crosswalk crossings. (iii) The location of origin and destination of a pedestrian has a significant effect on crossing outside of a crosswalk, the location of origin and destination of “one is inside of a crosswalk and another is outside of a crosswalk” has a highest proportion. These findings provide better understanding of illegal crossings and their impact factors so that the effectiveness of management and control of pedestrians at signalized intersections can be improved.

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Section: Factors a Ecting Crossing Behavior Of Pedestrianmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

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Analysis on Illegal Crossing Behavior of Pedestrians at Signalized Intersections Based on Bayesian Network

Zhang

2020

Journal of Advanced Transportation

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“…Walking speed studies are usually conducted in traffic engineering studies such as simulation of pedestrian movement in a corridor, sidewalk, or crosswalk [21], [22], [23], [24]. Sharifi et al [21] investigated the walking behavior of individuals with disabilities through controlled video tracking.…”

Section: B Walking Speed Studiesmentioning

confidence: 99%

“…Bosina and Weidmann [23] compared many walking speed studies and determined the variables that influence the walking speed. Paschalidis et al [24] studied the behavior of pedestrians when crossing an intersection and examined parameters affecting the walking speed adaptation. However, the behavior of pedestrian movement during a non-disaster conditions would be different from an evacuation condition.…”

Section: B Walking Speed Studiesmentioning

confidence: 99%

Identification of Factors Influencing the Evacuation Walking Speed in Padang, Indonesia

Yosritzal¹,

Putra²,

Kemal³

et al. 2020

Proceedings of the 2nd International Symposium on Transportation Studies in Developing Countries (ISTSDC 2019)

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This paper aims to identify factors influencing the walking speed of evacuees by conducting an evacuation drill in Padang, West Sumatera, Indonesia. A number of 18 volunteers and 6 observers, were gathered in an evacuation experiment on 3 routes with 5 segments each. The chosen routes are almost equal in terms of distance, but different in terms of the number of turning points. The experiment comprises of three cases in terms of the complexity of the route. These cases represent a simple, a medium and a complex route based on the number of turning points. The volunteers were asked to move, as if in an evacuation, to a particular place which was assumed to be a shelter. The observers were placed at some particular waypoints to record the time when an evacuee passes their location. The distance between the observers was measured using a manual distance meter. This study found that the average walking speed during the evacuation was 1.69 m/s. In addition, walking speed varied by age, gender, and walking distance. This finding significantly has an effect on the estimations of the coverage area of tsunami shelters. The data collection method is one of the novelties of this research. In this study, the walking speed was observed through an evacuation drill from a location to a shelter of 1.5 km away, whilst most of the previous studies estimate the walking speed based on an observation of a group of pedestrians crossing a road.

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An Analysis on Drivers’ Self-reported Questionnaire Responses, Regarding Aggressive Driving, Attitude Toward Cyclists and Personal Values

Andronis

Mavridis

Oikonomou

et al. 2018

Data Analytics: Paving the Way to Sustainable Urban Mobility

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Pedestrian compliance and cross walking speed adaptation due to countdown timer installations: A self report study

Cited by 36 publications

References 20 publications

Analysis on Illegal Crossing Behavior of Pedestrians at Signalized Intersections Based on Bayesian Network

Analysis on Illegal Crossing Behavior of Pedestrians at Signalized Intersections Based on Bayesian Network

Identification of Factors Influencing the Evacuation Walking Speed in Padang, Indonesia

An Analysis on Drivers’ Self-reported Questionnaire Responses, Regarding Aggressive Driving, Attitude Toward Cyclists and Personal Values

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