Isochrone analysis and assessments of cumulative opportunities are a common way to quantify accessibility. However, different time cut-offs have been used by different researchers, with little investigation into what is the ‘best’ cut-off time. Outstanding questions remain concerning the most effective or predictive cut-off time and the potential implications of choosing one time limit over another. The primary objective of this paper is to explore how different cut-off times affect the calculation of isochrone-based accessibility measurements and their potential to predict travel-mode choice. Fifty dissemination areas (DAs) within the Greater Toronto and Hamilton Area (GTHA) are selected to test the impact of different isochrone cut-off times in 5-minute intervals for public transit, automobile, and walking accessibility. The relative predictive power of 30- and 45-minute isochrones in modeling mode choice is also examined. This paper finds that different cut-off times do impact the interpretability of accessibility measurements in the isochrone approach, but a defined cut-off time for general use cannot be determined based on the analysis.
A buffer of ½ mi (805 m) is commonly used to define the service area of a subway (metro) station. This buffer is based on an approximation of the distance people are willing to walk to access the subway. This research compared the ½-mi pedestrian catchment area with the service areas reported in the Transportation Tomorrow Survey for access to the Toronto Transit Commission Subway System in Canada. This paper assesses the breakdown of access by mode to the subway and the pedestrian, bus–streetcar, and automobile catchment areas of stations in Toronto. This analysis finds two major drawbacks with the use of the ½-mi pedestrian catchment area. The service areas of buses and streetcars that connect to the subway are critical; they account for more than a third of all riders. Spatially, the size and the shape of the service area predicted by the ½-mi approach do not accurately represent what is observed in Toronto. Pedestrian catchment areas are commonly less than ½ mi in radius, and the bus–streetcar and automobile catchment areas are often many times larger.
Vehicle kilometers traveled (VKT) has been widely used in regional planning as a key sustainability performance indicator. Many regional growth plans for reducing work trip VKT have been proposed, with a focus on land use development in employment centers. Despite the potential impact of urban form on the reduction of VKT, the fundamentals of how this takes place remain unclear. This study analyzes the relationship between urban form, VKT, and mode shares by examining office commuting patterns in the Greater Toronto and Hamilton Area (GTHA) through a structural equation modeling approach. The model supports the substantial impact of urban form on the reduction of VKT; however, it indicates that such an impact is made mostly through shifting modes, rather than directly on reduced travel distances. This model is then used to evaluate critically a regional growth plan for the GTHA, finding that strategies focusing solely on increasing land use densities in employment centers are not likely to reduce regional VKT significantly without also easing commuting auto dependency. Thus, it is recommended that more sustainable travel alternatives for workers in employment centers should be provided to achieve a sufficient reduction in VKT.
Transit smart card records detail travel information of passengers, which provides abundant data for analyzing public travel patterns. Regular travelers’ information extracted from smart card data (SCD) have been extensively analyzed. However, rare studies have been devoted to non-roundtrips, which account for a relatively large portion of the overall transit ridership, especially in metropolises such as Beijing. This study aimed to reveal the non-roundtrip pattern using the passenger travel data obtained from SCD. Weekly non-roundtrip SCD were used to analyze the spatiotemporal distribution patterns of overall and typical non-roundtrips’ origins and destinations (ODs). Also, subway data and bus data were combined and visualized in geographic information system (GIS). The reasons for frequent non-roundtrips generated in the metropolitan city were inferred. The results demonstrate some detected spatiotemporal patterns of non-roundtrips. It is not surprising that a large proportion of non-roundtrips serve as a rail access to intercity, but there are still many trips of this kind showing a commuting pattern. Merging SCD with bus data, the results also reveal that passengers may choose other modes as a substitute return transportation option due to rail fare or overcrowding problem. This study focused on irregular trips normally neglected in the literature and found that the number of these trips is too large to be ignored in a diversified city like Beijing. Meanwhile, the travel patterns of non-roundtrips extracted can be used to direct the operation strategies for both rail and bus. The research framework raised here could be applied in other cities and comparative analysis could be done in the future.
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