Author: | Zhu, Manman |
Title: | A comprehensive analysis of walking behaviour and safety of pedestrians in urban environment |
Advisors: | Sze, Nang-ngai Tony (CEE) |
Degree: | Ph.D. |
Year: | 2025 |
Department: | Department of Civil and Environmental Engineering |
Pages: | xiii, 153 pages : color illustrations |
Language: | English |
Abstract: | Walking is the primary mean of access to essential urban goods and services. Like many metropolitan cities around the world, Hong Kong has been promoting walkability in its urban design and planning policy. Quality of urban walking environment is one of the crucial factors that affect the viability of a city. It can reshape the activity and mobility pattern of the citizens. However, pedestrians are also vulnerable to fatal and severe road injuries. Hence, it is necessary to identify the factors that affect walking behaviour and safety of pedestrians. Then, effective remedial measures can be developed to improve the walking environment and mitigate pedestrian injury risk. In this study, pedestrian walking behaviour and safety in urban environment will be evaluated at different levels. First, relationship between environment, traffic, safety perception and walking behaviour of individual pedestrian is investigated. Second, effects of street design, urban street tree, and traffic characteristics on pedestrian crash risk at the microscopic level are evaluated. Third, association between built environment, road network configuration, transport facilities, population socio-demographics and pedestrian crash risk at the macroscopic level is measured. At the individual level, effects of walking environment, transport facilities, and personal characteristics on the walking path choice are evaluated using an attitudinal survey. In this part, the stated preference method is adopted to predict the preferred walking path of pedestrians, accessing to the urban rail transit stations. In particular, factors like mixture of indoor and outdoor environment, accessible design, sky and green view, road geometry, socio-demographics and travel habit are considered. Then, the integrated choice and latent variable model is adopted, accounting for the effect of unobserved heterogeneity. On the other hand, effects of weather and traffic conditions on pedestrian safety perception and crossing behaviour are explored using the immersive Cave Automatic Virtual Environment (CAVE) experiment. For example, relationship between adverse weather conditions like rain and fog, vehicle speed, and pedestrian safety perception is examined. Furthermore, the casual inference approach, with inverse probability of treatment weight, is adopted to account for the possible confounding factors. At the microscopic level, effects of road geometric design, transport facilities, and urban street trees on the pedestrian crash risk of individual streets are evaluated. For example, data on tree density and tree canopy cover is used. In addition, comprehensive pedestrian count data is also available for the estimation of pedestrian crash exposure. Furthermore, the multivariate Bayesian spatial approach is applied, accounting for the effects of spatial dependency and multivariate correlation. At the macroscopic level, the roles of footbridges and underpasses in pedestrian safety at the zonal level are explored. With the three-dimensional digital map of pedestrian network, it is possible to estimate the connectivity of pedestrian network and accessibility of crossing facilities like footbridges and underpasses. Then, the Poisson lognormal approach is adopted, accounting for the effect of overdispersion. Furthermore, data on land use, road network, street environment, traffic characteristics, pedestrian crash, and population socio-demographics are usually aggregated at different spatial scales. To this end, the multiple membership multilevel modeling approach is adopted, accounting for the effects of hierarchical data structure and spatial correlation on the association measure of pedestrian crash risk at both microscopic and macroscopic levels. To sum up, findings of perceptional survey, immersive CAVE experiment, and micro- and macroscopic level pedestrian crash model should shed light on the effective urban design and planning policy that can improve the walking environment and promote walking as the sustainable transportation mode in Hong Kong. Therefore, overall quality of living can be enhanced. |
Rights: | All rights reserved |
Access: | open access |
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