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Investigation of microscopic pedestrian walking behavior

University of British Columbia

In sustainable urban planning, non-motorized active modes of travel such as walking are identified as a leading driver for a healthy, liveable, and resource-efficient environment. Walking is also an integral component of most trips. However, walking receives less attention in transportation engineering and planning compared to motorized modes. As the global society is becoming more aware of the benefits of active transportation, there is an increasing demand for designing and shaping the transportation system to put more emphasis on pedestrians. As such, standards and guidelines need to be developed in order to provide practitioners with the tools required to objectively evaluate pedestrian oriented facilities. However, the tools and methods developed and used for modeling pedestrian movement have not yet been developed to a level that can reliably measure pedestrian activity and behavior. To encourage walking, there is a need for a solid understanding of pedestrian walking behavior. This understanding is central to the evaluation of measures of walking conditions such as comfortability and efficiency. The aim of this thesis work is to gain an in-depth understanding of pedestrian walking behavior through the investigation of walking speed and the spatiotemporal gait parameters (step length and step frequency). This microscopic-level analysis provides insight into the pedestrian walking mechanisms and the effect of various attributes such as gender and age. The analysis relies on automated video-based data collection using computer vision techniques. This thesis makes several contributions which include: i) demonstrating the feasibility of using computer vision to capture pedestrian movement, ii) investigation of pedestrian speed variations with respect to design changes to intersection crossings, iii) investigation of the ability of individual pedestrians to change their walking speed as a response to pedestrian signal indications, iv) investigation of pedestrian gait parameters for various pedestrian and design attributes, and v) development of a methodology for classification of pedestrian age and gender using spatiotemporal gait parameters.  

Text

2012-07-20

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/42788

Civil Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/