S Xie

Development of a Bidirectional Pedestrian Stream Model with an Oblique Intersecting Angle

AbstractThis paper establishes a mathematical model that can represent the conflicting effects of two pedestrian streams that have an oblique intersecting angle in a large crowd. In a previous paper, a controlled experiment in which two streams of pedestrians were asked to walk in designated directions was used to model the bidirectional pedestrian stream of certain intersecting angles. In this paper, the writers revisit that problem and apply the Bayesian inference method to calibrate an improved model with the controlled experiment data. Pedestrian movement data are also collected from a busy crosswalk by using a video observation approach. The two sets of data are used separately to calibrate the proposed model. With the calibrated model, the relationship between speed, density, and flow is studied in both the reference and conflicting streams, and a prediction is made regarding how these factors affected the interactions of moving pedestrian streams. It is found that the speed of one stream not only d...

A Bayesian inference approach to the development of a multidirectional pedestrian stream model

In this paper, we develop a mathematical model to represent the conflicting effects of multidirectional pedestrian flows in a large crowd. The model is formulated based on Drakes model of traffic flow. Rather than relate the speed of a pedestrian stream solely to the pedestrian density, we introduce the flow ratio and intersecting angle between streams as variables. To calibrate the model, data collection was conducted through the video recording of pedestrian movements on a pedestrian street in Mong Kok, Hong Kong. Bayesian inference was adopted to calibrate the parameters based on the information from a previous experiment. Finally, we study the relationships among the speed, density, flow and intersecting angles of the pedestrian streams and predict how these variables affect the pedestrian movements.

Pedestrian Crossing Behavior at Signalized Crosswalks

AbstractThis study investigated pedestrian jaywalking at signalized crosswalks. Observational surveys were conducted at seven crosswalks in different areas in Hong Kong, after which pedestrian info...

Bayesian approach to model pedestrian crashes at signalized intersections with measurement errors in exposure

This study intended to identify the potential factors contributing to the occurrence of pedestrian crashes at signalized intersections in a densely populated city, based on a comprehensive dataset of 898 pedestrian crashes at 262 signalized intersections during 2010-2012 in Hong Kong. The detailed geometric design, traffic characteristics, signal control, built environment, along with the vehicle and pedestrian volumes were elaborately collected. A Bayesian measurement errors model was introduced as an alternative method to explicitly account for the uncertainties in volume data. To highlight the role played by exposure, models with and without pedestrian volume were estimated and compared. The results indicated that the omission of pedestrian volume in pedestrian crash frequency models would lead to reduced goodness-of-fit, biased parameter estimates, and incorrect inferences. Our empirical analysis demonstrated the existence of moderate uncertainties in pedestrian and vehicle volumes. Six variables were found to have a significant association with the number of pedestrian crashes at signalized intersections. The number of crossing pedestrians, the number of passing vehicles, the presence of curb parking, and the presence of ground-floor shops were positively related with pedestrian crash frequency, whereas the presence of playgrounds near intersections had a negative effect on pedestrian crash occurrences. Specifically, the presence of exclusive pedestrian signals for all crosswalks was found to significantly reduce the risk of pedestrian crashes by 43%. The present study is expected to shed more light on a deeper understanding of the environmental determinants of pedestrian crashes.

Rethinking safety in numbers: are intersections with more crossing pedestrians really safer?

Objective To advance the interpretation of the ‘safety in numbers’ effect by addressing the following three questions. How should the safety of pedestrians be measured, as the safety of individual pedestrians or as the overall safety of road facilities for pedestrians? Would intersections with large numbers of pedestrians exhibit a favourable safety performance? Would encouraging people to walk be a sound safety countermeasure? Methods We selected 288 signalised intersections with 1003 pedestrian crashes in Hong Kong from 2010 to 2012. We developed a Bayesian Poisson-lognormal model to calculate two common indicators related to pedestrian safety: the expected crash rate per million crossing pedestrians and the expected excess crash frequency. The ranking results of these two indicators for the selected intersections were compared. Results We confirmed a significant positive association between pedestrian volumes and pedestrian crashes, with an estimated coefficient of 0.21. Although people who crossed at intersections with higher pedestrian volumes experienced a relatively lower crash risk, these intersections may still have substantial potential for crash reduction. Conclusions Conclusions on the safety in numbers effect based on a cross-sectional analysis should be reached with great caution. The safety of individual pedestrians can be measured based on the crash risk, whereas the safety of road facilities for pedestrians should be determined by the environmental hazards of walking. Intersections prevalent of pedestrians do not always exhibit favourable safety performance. Relative to increasing the number of pedestrians, safety strategies should focus on reducing environmental hazards and removing barriers to walking.