Analysis of Pedestrian Crossing Speed and Waiting Time at Intersections in Dhaka

Zafri, Niaz Mahmud; Rony, Atikul Islam; Adri, Neelopal

doi:10.3390/infrastructures4030039

Cited by 27 publications

(14 citation statements)

References 34 publications

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“…Concerning company, crossing speeds were slowing down as the size of the company group was growing (Bansal et al, 2019;Kadali and Vedagiri, 2019;Shaaban, 2019). The same effect was noticed when pedestrians were crossing while holding objects, such as bags or luggage (Zafri et al, 2019). To this end, since the crossing duration expresses the exposure to risks, it is of great importance to further investigate it and particularly to focus on distracted pedestrians who are considered as more vulnerable.…”

Section: Literature Reviewmentioning

confidence: 93%

“…Based on literature review, crossing speed is affected by the intersection control type, with the relevant results varying between signalized and unsignalized intersections and crossings through midblocks. More specifically, Hassouna (2020) observed that pedestrians cross the unsignalized intersections faster than the signalized ones, while Zafri et al (2019) noticed slower crossing speeds in corresponding cases. Likewise, crossing was associated with gender, age, company group size, pedestrian flow and volume, the carrying of objects and in some cases with the use of a mobile phone.…”

Section: Literature Reviewmentioning

confidence: 98%

“…In particular, Kadali and Vedagiri (2019) observed that male pedestrians presented more changes of their crossing speed and Zafri et al ( 2019) that female pedestrians crossed the road slower than males. Regarding the age, several studies found out that young people between 16 and 30 years old were more likely to change their crossing speed (Kadali and Vedagiri, 2019), presenting higher crossing speeds (Forde and Daniel, 2020) in comparison to children, elderly and disabled people (Bansal et al, 2019;Zafri et al, 2019), who crossed slower.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Investigation of Distracted Pedestrians' Exposure Duration at Signalized and Unsignalized Pedestrian Crossings: A Bayesian Modeling Approach

Perra

Basbas

Nikiforiadis

et al. 2022

Period. Polytech. Transp. Eng.

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During the last decades, distraction caused by mobile phones has created concerns about pedestrians' safety, especially while crossing a road. The aim of this paper is to investigate the factors that have an effect on the crossing duration of pedestrians, distracted by mobile phone use, at both signalized and unsignalized crossings. Pedestrians with mobile phones were observed during crossing the aforementioned types of crossings in Thessaloniki, Greece, while their crossing duration was further examined via the development of Bayesian regression models, one for unsignalized and one for signalized crossings. For the research purposes, 554 pedestrians were observed at unsignalized crossings and 409 at signalized ones. The most commonly observed type of distraction was talking on the mobile phone, while texting was also found to be very common. The variables, found to be associated with crossing duration, were significantly different between unsignalized and signalized crossings. Crossing duration at unsignalized crossings seemed to be affected by the experience of a potential conflict with a motorized vehicle and the presence of additional distractors, such as the carrying of an object and the presence of company. At signalized crossings, duration tended to be influenced by the age of the pedestrian and the position before crossing. Current research contributes in understanding and modeling distracted pedestrians' behavior when crossing streets.

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Section: Literature Reviewmentioning

confidence: 93%

Section: Literature Reviewmentioning

confidence: 98%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Investigation of Distracted Pedestrians' Exposure Duration at Signalized and Unsignalized Pedestrian Crossings: A Bayesian Modeling Approach

Perra

Basbas

Nikiforiadis

et al. 2022

Period. Polytech. Transp. Eng.

View full text Add to dashboard Cite

show abstract

“…The results highlighted the impact of intersection clearing time on violations and percentage of unsafe crossings that occur. Gender and age are often regarded key factors; crossing time [2] and the waiting time [4] of the pedestrians varied with age and gender. Females waited almost twice the amount of time as males at the crossings [5], and older pedestrians have longer waiting time [6].…”

Section: Introductionmentioning

confidence: 99%

Contributing Factors in Pedestrians Waiting Time at Signalized Intersections Using Survival Analysis

Hashemi¹,

Bargegol²,

Hamedi³

2022

CRPASE

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Recognizing elements that determine pedestrian waiting time is important when designing intersection implications in order to reduce violations and their repercussions. The goal of this study is to investigate these influencing elements. To achieve this purpose, data from 1116 pedestrians was collected at three signalized intersections with various signal types and land uses. The T-test is performed to see if there are any significant differences between sets of variables. The value of factors and the decision-making process of pedestrians are determined using Survival Analysis. Pedestrians' waiting time is affected by the type of median, arrival time, land use, and gender (according to survival analysis model). An effective median design, based on field observations and findings, could have a considerable impact on pedestrians' willingness to wait for a safe crossing during the red phase. The findings of this study will aid in improving the safety of intersections by providing a better understanding of the most vulnerable road users' behavior.

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“…Research into collecting and measuring reliable microscopic traffic data is a fundamental aspect in road network planning scientific literature. Several applications can be implemented by using the acquired dataset in terms of traffic safety, road capacity, and level of service analysis [1][2][3][4]. However, as the traffic conditions get more complex, the level of detail and the quality of the collected information is getting higher.…”

Section: Introduction 1microscopic Traffic Data Acquirementmentioning

confidence: 99%

Utilizing UAVs Technology on Microscopic Traffic Naturalistic Data Acquirement

Anagnostopoulos

Kehagia

2021

Infrastructures

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Research into collecting and measuring reliable, accurate, and naturalistic microscopic traffic data is a fundamental aspect in road network planning scientific literature. The vehicle trajectory is one of the main variables in traffic flow theory that allows to extract information regarding microscopic traffic flow characteristics. Several methods and techniques have been applied regarding the acquisition of vehicle trajectory. The forthcoming applications of intelligent transport systems on vehicles and infrastructure require sufficient and innovative tools to calibrate existing models on more complex situations. Unmanned aerial vehicles (UAVs) are one of the most emerging technologies being used recently in the transportation field to monitor and analyze the traffic flow. The aim of this paper is to examine the use of UAVs as a tool for microscopic traffic data collection and analysis. A comprehensive guiding framework for accurate and cost-effective naturalistic traffic surveys and analysis using UAVs is proposed and presented in detail. Field experiments of acquiring vehicle trajectories on two multilane roundabouts were carried out following the proposed framework. Results of the experiment indicate the usefulness of the UAVs technology on various traffic analysis studies. The results of this study provide a practical guide regarding vehicle trajectory acquirement using UAVs.

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Analysis of Pedestrian Crossing Speed and Waiting Time at Intersections in Dhaka

Cited by 27 publications

References 34 publications

Investigation of Distracted Pedestrians' Exposure Duration at Signalized and Unsignalized Pedestrian Crossings: A Bayesian Modeling Approach

Investigation of Distracted Pedestrians' Exposure Duration at Signalized and Unsignalized Pedestrian Crossings: A Bayesian Modeling Approach

Contributing Factors in Pedestrians Waiting Time at Signalized Intersections Using Survival Analysis

Utilizing UAVs Technology on Microscopic Traffic Naturalistic Data Acquirement

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