Pedestrian movement, although ubiquitous and well-studied, is still not that well under-stood due to the complicating nature of the embedded social dynamics. Interest among researchers in simulating the nature of pedestrian movement and interactions has grown significantly in part due to increased computational and visualization capabilities afforded by high power computing. Different approaches have been adopted to simulate pedestrian movement under various circumstances and interactions. In the present work, bi-directional crowd movement is simulated where equal numbers of individuals try to reach the opposite sides of an environment. Two pedestrian movement modeling methods are considered. The reasonableness of these two models in producing better results is com-pared without increasing the computational complexity. First a Least Effort Model (LEM) is investigated, where agents try to take an optimal path with minimal changes from their intended path as possible. Following this, a modified form of Ant Colony Op-timization (ACO) is developed, where individuals are guided by a goal of reaching the other side in a least effort mode as well as being influenced by a pheromone trail left by predecessors. The objective is to increase agent interaction, thereby more closely reflect-ing a real world scenario. The methodology utilizes Graphics Processing Units (GPUs) for general purpose computing using the CUDA platform. Because of the inherent parallel properties associated with pedestrian movement, such as similar interactions of indi-viduals on a 2D grid, GPUs are a well suited computing platform. The main feature of the implementation undertaken here is the data driven parallelism model. The data driven implementation leads to a speedup up to 18x compared to its sequential counterpart run-ning on a single threaded CPU. The number of pedestrians considered in the model ranged from 2K to 100K, representing numbers typical of mass gathering events. A de-tailed analysis is also provided on the throughput of pedestrians across the environment. Compared to LEM model, there is an overall increment of 39.6% in the throughput of agents using the ACO model with a marginal increment of 11% in the computational time. A detailed discussion addresses implementation challenges faced and avoided.

This research is an empirical analysis of pedestrian safety in San Jose, Costa Rica. The purpose of this research is to evaluate pedestrian accommodation and analyze pedestrian safety performance at signalized intersections. Pedestrian accommodation is defined by the documented and applied practices for designing and operating pedestrian facilities at signalized intersections. Pedestrian safety performance is defined by pedestrian compliance and conflicts. This research: (1) reviews and compares documented practices in Costa Rica regarding pedestrian accommodation at signalized intersections with best practices from North America; (2) develops and applies a data collection program for evaluating pedestrian accommodation and safety at 20 signalized intersections on an urban-arterial study corridor; (3) evaluates the study corridor’s physical and operational site conditions; and (4) analyzes pedestrian compliance and conflicts on the study corridor. Transport policy revisions and engineering measures to improve pedestrian accommodation and safety at signalized intersections in Costa Rica are recommended.

Thesis (M.A.)--University of Hong Kong, 2002. / Includes bibliographical references.

Thesis (M. Sc.)--University of Hong Kong, 2002. / Includes bibliographical references.

Thesis (M.A.)--University of Hong Kong, 2002. / Includes bibliographical references. Also available in print.

Thesis (M.U.D.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 143-147) Also available in print.

Thesis (M.U.D.)--University of Hong Kong, 2002. / Includes bibliographical references. Also available in print.

Orientador: Carlos Alberto Bandeira Guimarães / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-18T20:55:06Z (GMT). No. of bitstreams: 1 Amancio_MarceloAugusto_D.pdf: 2206122 bytes, checksum: 3893647f371e670bcba9295c4489a867 (MD5) Previous issue date: 2011 / Resumo: O objetivo principal desta pesquisa e propor uma concepção inicial para um modelo de opção modal de viagens a pé a shopping centers urbanos. Foi realizado, inicialmente um levantamento bibliográfico sobre o tema shopping center e as características do meio físico urbano que influenciam na opção pelo modo a pé. Dentre as metodologias disponíveis para avaliar a opção modal, foi selecionado um modelo de escolha discreta do tipo logit. A pesquisa foi realizada na cidade de Campinas (SP), em shoppings dentro da área urbana (Shopping Jaraguá Conceição e Campinas Shopping). Os dados relacionados as características do meio físico urbano, as características das viagens (comprimento, modo de transporte utilizado) e as características dos indivíduos (renda, numero de automóveis no domicilio e numero de moradores do domicilio) serão obtidas em órgãos competentes e por entrevistas com usuários dos shopping centers através da técnica de preferência revelada e implementados com o auxilio de um Sistema de Informações Geográficas (TransCAD®). Já o software utilizado para estimar os parâmetros do modelo proposto foi o BIOGEME® (Bierlaire Optimization Toolbox for GEv Model Estimation). Dois modelos foram calibrados, um considerando apenas as variáveis relacionadas as viagens e ao individuo e ou considerando alem destas as variáveis que caracterizam o meio físico urbano. Os resultados apontam uma melhora significativa na calibração do modelo quando se consideram as características do meio físico urbano, confirmando a importância destas variáveis no processo de opção modal, principalmente na opção pelo modo a pé / Abstract: The main objective of this research is to propose an initial conception for a model that allows to estimate walk on foot trips to shopping malls. Initially it was carried out a literature review related to shopping malls and the urban physical environment characteristics that influence the choice of walk on foot. Among the available methods to evaluate the modal choice, was selected a logit discrete modal choice model. The survey was conducted in the city of Campinas, Brazil, in malls within the urban area (Shopping Jaraguá Conceição and Campinas Shopping). The data related to the urban physical environment characteristics, the trips characteristics (length, mode of transport) and individual characteristics (income, number of cars in the domicile and number of people in the household) will be obtained from government officials and interviews with users of the mall through the revealed preference technique and implemented with the assistance of a Geographic Information System (TransCAD). To estimate the model parameters was used the software BIOGEME (Bierlaire Optimization Toolbox for GEv Estimation Model). Two models were calibrated, one considering only the variables related to travel and to the individual and other considering in addition to these variables the urban physical environment characteristics. The results show a significant improvement in the model calibration when considering the urban physical environment characteristics, confirming the importance of these variables in the modal choice process, especially in the option by the walk on foot / Doutorado / Transportes / Doutor em Engenharia Civil

Active models of travel, particularly walking, are an integral part of the multi-modal transportation system in urban areas. Walking provides numerous benefits at the individual and community levels (e.g., health benefits, reducing traffic congestion, emissions, and energy consumption). Nevertheless, safety concerns represent a major roadblock to the optimal utilization of walking as a key mode of travel. Pedestrians are among the most Vulnerable Road Users (VRUs) who are at a higher risk of being killed or severely injured as a result of road collisions. Previous research shows that many pedestrian behaviours could increase the risk of collisions significantly. Pedestrian violations, either temporal or spatial, stand as one of the riskiest behaviours that impact pedestrian safety. However, investigating such behaviour and quantifying its impact on safety are scarce in the literature. Accordingly, this research aims at developing a comprehensive framework to analyze pedestrian violations and understand when and where they can lead to collisions. To address these goals, the research utilized historical records of collisions that involve pedestrian violations. State-of-the-art statistical models (Copula models, Bayesian Structural Equation Modelling), Machine Learning techniques (Latent Class Analysis clustering), and Deep Learning methods (Self-Organizing Map) were applied to understand the factors contributing to such collisions on the micro-level (intersection and mid-blocks) and macro-levels (traffic analysis zones) and understand the characteristics of locations that experience a high frequency of those collisions. Additionally, a novel approach (dynamic R-vine copula-based time series model) was proposed to analyze the efficiency of pedestrian safety treatments that are implemented as part of vision zero programs. This approach enables the accurate assessment of the treatments, identifying the most effective combination of treatments, and investigating the association between area characteristics and treatment combination performance. Overall, this dissertation provides a solid understanding of pedestrian violations and safety for decision-makers, safety practitioners, and academia. / Thesis / Doctor of Philosophy (PhD)

Chen, Liang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 199-218). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.