Pedestrian Access to Transit: Identifying Redundancies and Gaps Using a Variable Service Area Analysis

School of Urban Planning, McGill University, H3A 2K6, Québec, Canada
Download full-text


Available from: Ahmed M. El-Geneidy
  • Source
    • "Thus, a discrete demand model assuming a finite set of possible locations for bus stops (given by road intersections and the geometric characteristics of a network) is more useful as a tool to determine the actual (optimal) location of stops (Furth and Rahbee, 2000; Chien and Qin, 2004; Furth et al., 2007). With the increased availability of Geographic Information System (GIS) tools, researchers have been able to identify more precise walking distances to bus stops 1 , which can be embedded in discrete models to optimise bus stop location (Furth et al., 2007; El-Geneidy et al., 2010). "
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper re-considers the problem of choosing the number of bus stops along urban routes, first by estimating the probability of stopping in low demand markets, and second by analysing the interplay between bus stop size, bus running speed, spacing and congestion in high demand markets. A comprehensive review of the theory and practice on the location and spacing of bus stops is presented. Using empirical data from Sydney, Australia, we show that the widely used Poisson model overestimates the probability of stopping in an on-call bus stopping regime, and consequently underestimates the optimal number of bus stops that should be designed. For fixed-stop services, we show that bus running speed, frequency and dwell time are crucial to determining the relationship between bus stop spacing and demand, with bus stop congestion in the form of queuing delays playing a key role. In particular, we find that bus stop spacing should be decreased if demand increases at a constant bus running speed; however, if both bus running speed and the speed of the passenger boarding process increase, then the distance between bus stops should be kept long even at high demand levels, a result that is consistent with the implementation of Bus Rapid Transit (BRT) systems that feature high bus running speeds and long distances between stops relative to conventional bus services.
    Full-text · Article · Jan 2014 · Transportation Research Part A Policy and Practice
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Current research focuses on pedestrian access to transit; however, commuter trains in outlying urban regions serve populations in low-density areas where many people drive rather than walk to transit services. The determinants that influence how far people are willing to drive to train stations and the factors that determine boardings at suburban train stations have not been formally studied. This paper models suburban commuter travel demand by use of the 2003 Montreal, Quebec, Canada, origin-destination survey and onboard survey data from the Agence Métropolitaine de Transport to identify characteristics of individual trips and station characteristics that influence the driving distance to commuter rail and demand at stations. The models show that methods for estimating pedestrian access distance and number of boardings per transit stop can easily be transferred to estimating driving access distance and the number of boardings per station in the park-and-ride context. The model for passenger boardings by station can be used for estimating either demand for a planned station or the effect of service interventions (e.g., parking spots) on boardings at existing stations. The paper also shows that these approaches can be a valuable tool to transit planners interested in increasing passenger demand on commuter rail through a better understanding of service characteristics.
    Full-text · Article · Dec 2011 · Transportation Research Record Journal of the Transportation Research Board
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article develops a rapid response ridership forecast model, based on the combined use of Geographic Information Systems (GIS), distance-decay functions and multiple regression models. The number of passengers boarding at each station in the Madrid Metro network is estimated as a function of the characteristics of the stations (type, number of lines, accessibility within the network, etc.) and of the areas they serve (population and employment characteristics, land-use mix, street density, presence of feeder modes, etc.). The paper considers the need to evaluate the distance threshold used (not the choice of a fixed distance threshold by assimilation from other studies), the distance calculation procedure (network distance versus straight-line distance) and, above all, the use of distance-decay weighted regression (so that the data from the bands nearer the stations have a greater weighting in the model than those farther away). Analyses carried out show that weighting the variables according to the distance-decay functions provides systematically better results. The choice of distance threshold also significantly improves outcomes. When an all-or-nothing function is used, the way the service area is calculated (straight-line or network distances) does not seem to have a decisive influence on the results. However, it seems to be more influential when distance-decay weighting is used.Highlights► The article develops a rapid response ridership forecast model. ► It is based on the use of distance-decay functions and multiple regression models. ► Weighting the predictors according to that functions provides better results.
    No preview · Article · Nov 2011 · Journal of Transport Geography
Show more