Planning street transit stops under uncertainties : a fuzzy logic approach

• Main Author: Masood, Hassaan
• Language: English
• Published: University of British Columbia 2017
• Online Access: http://hdl.handle.net/2429/63359

This research concerns with the effect of street transit stop-related factors on transit demand attraction. Key stop-related factors that influence passengers’ perception of the service were identified along with their recommended standards. It was shown that current transit planning manuals and guidelines suffer from the following limitations: (a) they are silent regarding the relative importance of stop-related factors; (b) they exhibit great deal of variability in service planning standards; and (c) they fail to provide specific standards for different city sizes. The number of factors and variability in service planning standards involved in transit stop planning make it almost impossible for transit planners to decide on the location, interspacing, and design of street transit stops based merely on intuition and experience. Further, classical decision-making approaches, while useful, do not adequately consider the site-specific conditions and uncertainties associated with service standards. To address the above issues, this research adopted a twofold approach. First, an expert opinion survey was conducted among a panel of transit experts across Canada to (a) understand the relative importance of various transit stop-related factors with respect to their attractiveness to passengers; and (b) collect best-practices used in the transit industry to select typical standards for those factors. Second, an index-based decision-support tool was developed through the solicitation and synthesis of experts’ opinions using Analytical Hierarchical Process and Fuzzy Synthetic Evaluation. The developed index-based tool provides a simple way to quantitatively evaluate transit stops, based on a single score (or rating index), considering various factors that affect transit ridership. The developed tool is intended to help transit planners make informed decisions regarding the location, interspacing, and design of existing/new street transit stops. The results showed that, among all spatial (i.e. stop location and interspacing) factors, land use is the most important factor that influences demand attraction, while the most important design factor is real-time information provision. Furthermore, the dataset showed that a lower passenger demand is required in small cities to provide a particular amenity (e.g. seat, shelter, or CCTV camera) at the stop compared to the demand required in large cities to provide the same amenity. === Applied Science, Faculty of === Engineering, School of (Okanagan) === Graduate