Pedestrian Behavior and Traffic Violations at Signalized Intersections

Chen, Jing; Shi, Jianjun; Li, Xiaoli; Quan, Zhao

doi:10.1061/41186(421)108

Cited by 9 publications

(5 citation statements)

References 3 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%

“…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%

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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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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%

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

Zhang

2020

Journal of Advanced Transportation

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“…Model validation, on the other hand, is the process of establishing that the constructed model provides an appropriate representation of the studied system [43]. In this study, validation was performed by comparing the model's output variables (trafc volume, queue length, and travel time) against the actual Observational study [37][38][39] Left turning and pedestrian conficts Safety, capacity Signalized intersection Cross-sectional study [31,40].…”

Section: Model Calibration and Validationmentioning

confidence: 99%

Illegal Maneuver Effect on Traffic Operations at Signalized Intersections: An Observational Simulation-Based Before-After Study Using Response Surface Methodology

Jahangard

Madarshahian

Sabur

et al. 2023

Journal of Advanced Transportation

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This study investigates three illegal maneuvers at signalized intersections: pedestrians jaywalking at signalized crosswalks (JSC), vehicles stopping near the intersections (SNI), and vehicles occupying the through lane instead of the left-turn lane to make a left turn (OTL). Traffic microsimulation models of four intersections were developed using Aimsun, and data were collected by a drone over a 3-hour period. The car-following model (Gibbs model) implemented in Aimsun was calibrated for each of the intersections and validated at the 95% confidence level. The validated Aimsun models were used to perform 13 experiments designed to investigate the interaction effects of decreasing two or more illegal maneuvers on travel time and fuel consumption. These 13 experiments were identified using the design of experiments D-optimality criterion. To investigate the main and interaction effects of decreasing two or more illegal maneuvers on travel time and fuel consumption, the response surface methodology (RSM) was used. Using RSM, the statistical model that was found to best fit the simulation results was a quadratic form. The results showed that the dependent variables “travel time ratio” and “fuel consumption ratio” are affected not only by a decrease in violations ratio but also by the volume of traffic as the exogenous variable. It was found that decreasing two of the violations, namely, JSC and SNI, improves travel time and fuel consumption but decreasing OTL has the opposite effect, resulting from the inadequate design of left-turning lane length/capacity and/or inadequate signal timing to accommodate left-turning volume.

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“…To fix the required number of intersections for safety model development, existing literature on pedestrian behavior and safety modeling at signalized intersections were reviewed and the outcome inferred that the number of study intersections varies from one to ten (Muraleetharan et al 2005;Abu Sa'a 2007;Zhang et al 2009;Huang, Ma 2010;Chen et al 2011;Ling et al 2012;Nagraj, Vedagiri 2013;Marisamynathan, Vedagiri 2018). To cover the variation in pedestrian, traffic and roadway characteristics, five signalized intersections were selected in this study.…”

Section: Site Selection and Videographic Surveymentioning

confidence: 99%

Pedestrian Safety Evaluation of Signalized Intersections Using Surrogate Safety Measures

Marisamynathan

Vedagiri

2020

Transport

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The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian-vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the crosswalk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

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Pedestrian Behavior and Traffic Violations at Signalized Intersections

Cited by 9 publications

References 3 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

Illegal Maneuver Effect on Traffic Operations at Signalized Intersections: An Observational Simulation-Based Before-After Study Using Response Surface Methodology

Pedestrian Safety Evaluation of Signalized Intersections Using Surrogate Safety Measures

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