An approach to imputing destination activities for inclusion in measures of bicycle accessibility

This paper proposes a new method to estimate bicycle accessibility for various trip purposes based on a massive dockless bike-sharing dataset in Shanghai, China. Specifically, a Dirichlet multinomial regression topic model (DMR model) is applied to identify bicycle trajectories' trip purposes, simultaneously considering arrival time and drop-off location. Based on obtained trip purposes, we estimate impedance functions using a negative exponential function. Finally, based on estimated impedance functions, two cases of bicycle accessibility for two different purposes - restaurant and hospital - are presented in Shanghais central area. The results show that almost 90% of bicycle trips are less than 30 min or 5 km. Although the difference between the impedance functions between various trip purposes is not significant, we find that trip purposes of “Work and School” have the highest travel impedance for bicyclists. Cyclists in Shanghai accept longer bicycle travel times for leisure (e.g., shopping) than for commuting (e.g., work or school).     

Measuring the long-distance accessibility of Italian cities

Long-distance accessibility is a crucial element for economic development and for territorial cohesion. To be revealing, however, a measure of accessibility must not only consider the distance or travel time of a single mode, but should include the fares, the frequency and the interchanges of all available modes.The paper aims to address whether and where there is an accessibility problem between Italian regions, through a comprehensive measure of accessibility covering the entire Italian territory. The measure used in the paper is potential accessibility, with an exponential decay impedance function. Different from similar studies, this one gives a more in-depth definition of impedance parameters due to the availability of a transport model that includes the entire Italian long-distance supply (roads, coaches, long-distance rail services, air services, and ferries). The opportunities at destination are proxied by population, and private and public sector employees.The main outputs are detailed maps of accessibility that are significantly more realistic than using simple infrastructure indicators or single-mode measures. In addition, some policy conclusions are drawn in terms of past and future investment policies.     

Measuring housing and transportation affordability: A case study of Melbourne,Australia

Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies.     

Robust accessibility: Measuring accessibility based on travelers' heterogeneous strategies for managing travel time uncertainty

Uncertainties in travel times due to traffic congestion and delay are risks for drivers and public transit users. To avoid undesired consequences such as losing jobs or missing medical appointments, people can manage the risks of missing on-time arrivals to destinations using different strategies, including leaving earlier to create a safety margin and choosing routes that have more reliable rather than fastest travel times. This research develops a general analytical framework for measuring accessibility considering automobile or public transit travelers' heterogeneous strategies for dealing with travel time uncertainty. To represent different safety margin plans, we use effective travel time (expected time + safety margin), given specified on-time arrival probabilities. Heterogeneity in routing strategy is addressed using different Pareto-optimal routes with two main criteria: faster travel time vs. higher reliability. Based on various safety margin and routing strategy combinations, we examine how accessibility changes under varying safety margin plans and routing strategies. Also, we define and measure robust accessibility: geographic regions that are accessible regardless of the safety margin planning and routing strategy. Robust accessibility can provide a conservative and reasonable view of accessibility under travel time uncertainty. To demonstrate the applicability of the methods, we carry out an empirical study on measuring the impacts of new transit service on healthcare accessibility in a deprived neighborhood in Columbus, Ohio, USA.     

A ticket to ride: Evolving landscapes of air travel accessibility in the United States

During the past decade, air passenger service in the United States has been exposed to numerous carrier bankruptcies, antitrust investigations, mergers, labor problems and a massive increase in competition. These internal elements, combined with the rising costs of fuel and the threat of terrorism combine to make a relatively uncertain air travel landscape for both passengers and operators. Moreover, these dynamics have generated significant geographical shifts in airline route structures and airports serviced by commercial carriers. These factors, combined with increasing levels of consumer access to fare and routing information, have altered the landscape of air travel accessibility in the United States. The purpose of this paper is to examine issues of consumer air travel accessibility through an analysis of three critical measures: flight segments, flight time and ticket costs. In addition, a typology of air passenger accessibility is generated for the 156 busiest commercial airports in the United States using these three measures. Results suggest significant local and regional biases in time and cost, relative to distance, for many US markets.     

Evaluating spatial accessibility to healthcare services under travel time uncertainty: A reliability-based floating catchment area approach

Most existing healthcare accessibility studies ignore the travel time uncertainty that are commonly encountered in road networks. This study aims to examine the impacts of travel time uncertainty on healthcare accessibility. A reliability-based two-step floating catchment area (2SFCA) method is proposed to evaluate healthcare accessibility under travel time uncertainty. The proposed measure generalizes the conventional 2SFCA measure by explicitly considering individuals' reliability constraints when scheduling visits to healthcare facilities in the face of travel time uncertainty. The proposed measure is further used to investigate travel time uncertainty impacts in a comprehensive case study. A big dataset of taxi trajectories is collected in the case study to extract dynamic information on travel time distributions. The results of the case study highlight the significant but heterogeneous impacts of travel time uncertainty on healthcare accessibility for various parts of the city at different times of the day. They also have several methodological implications for the evaluation of healthcare accessibility under travel time uncertainty.     

Individuals' social preferences in joint activity location choice: A negotiation model and empirical evidence

Out-of-home leisure activities are often conducted jointly by individuals implying that location and travel choices made for these activities are the result of a group interaction. Current utility-theoretic approaches assume an aggregated group utility function and hence ignore aspects of the group decision making process. In this study, an empirical model of joint-activity choice is developed that, in contrast, assumes a negotiation process. A social utility function describes how individuals deal with preference differences in the group. The model is estimated based on an experimental activity-travel choice task where group settings are mimicked. A sample (N = 315) from a national panel of individuals participated in the experiment. Estimation results based on a discrete mixture model show that individuals display a preference for locations in which losses are equally distributed in the group even when this comes at the costs of the total group outcome. Results further show that the social utility function is asymmetric: compromise solutions are favored more strongly when consequences relate to costs (travel costs) than when they concern rewards (attractiveness). Furthermore, there is considerable heterogeneity in how people make social trade-offs. It is concluded that the model offers new insights in location preferences for joint activities that should be taken into account in spatial choice models and accessibility analysis.     

Planning for low carbon mobility: Impacts of transport interventions and location on carbon-based accessibility

Accessibility has been conceptualized and applied in different ways, depending on the underlying political objectives. In the context of climate change and ambitious emission reduction targets, environmental concerns have risen high on the political agenda. Existing methods for assessing transport-related environmental impacts typically depend on realized or modeled travel behavior. Many of them do not entail a spatial dimension, ignore the importance of the land use component, lack scenario building capabilities or have limited communication value. Consequently, accessibility analysis and planning could make a valuable contribution towards a low carbon transition, but needs to attune to the specific objective of reducing transport-related greenhouse gas emissions. This paper introduces a novel conceptualization of location-based accessibility, where CO₂ emissions are used as a travel cost in place of time or monetary costs. By identifying and assessing options for interventions in the land use and transport system, carbon-based accessibility instruments might serve a number of potential decision-making purposes related to low carbon mobility planning. Carbon-based accessibility of a business park in the Munich region is analyzed in multiple scenarios to demonstrate the application potential of the method. The experiential application focuses on the effects of changes in vehicle efficiency and occupancy rates of both car and transit, but also compares the resulting carbon-based accessibility levels to alternative sites with the transport system unchanged. Applying carbon-based accessibility instruments to real-world planning issues could enhance strategic decision-making processes in the context of climate change mitigation.     

Measuring accessibility to grocery stores using radiation model and survival analysis

Measuring spatial accessibility to grocery stores and identifying food deserts have been of interest to planners and policy makers. However, measuring and quantifying accessibility in a way that relates to actual travel behaviors and preferences are challenging. This study aims to promote an existing radiation model by incorporating different transportation modes and time use diaries to provide a more realistic estimation of accessibility. We proposed a survival analysis method, such as the Cox proportional hazard model, as a novel approach to develop a cost decay function based on time use diaries. A multinomial logit model was applied to estimate the portion of people walking, traveling by car, and traveling by bus. A case study of grocery stores in Travis County, Texas, is used to illustrate the approach. The results indicate that for walking accessibility to grocery stores, the majority of zip codes fall into the very low, low, and moderate accessibility classes. Moreover, in most western zip codes transit accessibility to grocery stores is found to be very low. However, the spatial accessibility for some of such zip codes has been enhanced because of the presence of cars.     

Using GIS to visualise and evaluate student travel behaviour

Using GIS to evaluate travel behaviour is an important technique to increase our understanding of the relationship between accessibility and transport demand. In this paper, the activity space concept was used to identify the nature of participation in activities (or lack of it) amongst a group of students using a 2 day travel-activity diary. Three different indicators such as the number of unique locations visited, average daily distance travelled, and average daily activity duration were used to measure the size of activity spaces. These indicators reflect levels of accessibility, personal mobility, and the extent of participation, respectively. Multiple regression analyses were used to assess the impacts of students socio-economic status and the spatial characteristics of home location. Although no differences were found in the levels of accessibility and the extent of participation measures, home location with respect to a demand responsive transport (DRT) service was found to be the most important determinant of their mobility patterns. Despite being able to travel longer distances, students who live outside of the DRT service area were found to be temporally excluded from some opportunities. Student activity spaces were also visualised within a GIS environment and a spatial analysis was conducted to underpin the evaluation of the performance of the DRT. This approach was also used to identify the activity spaces of individuals that are geographically excluded from the service. Evaluation of these results indicated that although the service currently covers areas of high demand, 90% of the activity spaces remained un-served by the DRT service. Using this data six new routes were designed to meet the coverage goal of public transport based on a measure of network impedance based on inverse activity density. Following assessment of public transport service coverage, the study was extended using a spatial multi criteria evaluation (SMCE) technique to assess the effect of service provision on patronage.     

Impacts of high speed rail on railroad network accessibility in China

High speed rail (HSR) is changing the overall travel accessibility of cities in China. There have been a number of studies of high speed rail in China. However, detailed spatiotemporal accessibility pattern of cities affected by the operation of high speed rail in China has not been reported. This study takes a timetable-based accessibility evaluation approach to analyze the changes in travel time, travel cost, and distance accessibility for each of the four main stages of HSR development in China: no HSR service in Stage 1 before August 2008, several HSR lines in Stage 2 between August 2008 and July 2011, reduced operating speed of HSR trains in Stage 3 between August 2011 and November 2012, and addition of new HSR lines and reduction of ticket fares in Stage 4 between December 2012 and January 2013. In addition to the “corridor effect” and the “center-diffusion” pattern, this paper investigates the impacts of HSR on changes in in-vehicle travel time and out-of-vehicle travel time with respect to the policy changes that reduced the operating speed of HSR trains, rearranged the train timetable, and lowered the ticket fare on HSR trains. The analysis results indicate the spatiotemporal pattern of Chinese cities affected by these policy changes. This study is useful for assessing HSR impacts on the accessibility of various cities across China as well as serving as a decision-making support to policies related to adjustments of HSR operation and planning of future HSR routes by considering the existing HSR and non-HSR railway lines.     

Measuring the effect of transportation infrastructure on retail firm co-location patterns

This paper studies the effects of transportation infrastructure on the location behavior of competing retail firms. First, in a game theoretic framework that describes the location choices made by retailers with respect to each other, the connection between relative firm location and transportation demand is outlined. Second, a multivariate point pattern statistic based on this theoretical framework is applied to location patterns of fast food outlets to measure the effects that major road infrastructure has on firm location behavior in this sector.The results suggest that transportation infrastructure affects the location behavior of firms with respect to their location in relation to their competitors. Access to important transportation infrastructure induces competing outlets to locate next to each other—a tendency not necessarily observed among outlets without such access. Theoretically, this does not only affect economic outcomes, but also travel demand and consumer accessibility. The findings from this study stress the importance of accounting for how transportation infrastructure changes the location behavior of firms in travel demand frameworks.     

Extending public transit accessibility models to recognise transfer location

A longstanding issue for public transit agencies has been how to assess the performance of transit service including spatial service coverage to meet the transport needs of the community. The conventional approach quantifies accessibility using door-to-door travel time in such a way that accessibility declines as the travel time to the opportunity increases. A new approach to modelling transit accessibility is proposed by incorporating the potential effect of transfer location. It builds on the premise that transit users may have a preference for a transfer location best located relative to the trip origin and destination points. The model is tested in Brisbane's bus network which has a radial form, where inner-city suburbs have relatively higher accessibility than outer-city suburbs, if only travel time is counted. Incorporating the transfer location refines the accessibility modelling so that some outer-city suburbs located along the major bus corridors have a relatively higher accessibility level. The new model also suggests that inner-city suburbs do not necessarily have better accessibility. Suburbs close to the city centre may have shorter transit travel time to reach other suburbs, but they do not have a well-connected transit network to other suburbs through service transfers.     

Firm heterogeneity and the accessibility of manufacturing firms to labour markets

In this paper, we propose a measure of geographic accessibility of firms to labour markets. This measure is computed from the microeconomic perspective, avoiding ex ante imposition of administrative boundaries and including the individual characteristics of firms and workers along with the geographical environment and the urban structure of territories through the estimation of particular impedance functions. Computation is done using microdata on more than 60,000 Spanish manufacturing firms and over a million workers' commutes across the full road transport infrastructure network (urban and intercity). We estimate impedance functions that incorporate the specific characteristics of firms and workers. Results show notable accessibility differences across firms due not just to their geographic location but also to their intrinsic industry characteristics and the strategies that they follow.     

Network industries in collision: aviation infrastructure capacity,financing and the exposure to traffic declines

This paper discusses how various aviation infrastructure service providers have dealt with the fall off in airline traffic following the terrorist attacks in the US on September 11th. It shows that these organizations have relatively high fixed costs and low incremental costs for providing services. As such, small changes in traffic have large impacts on revenue because revenues are generally proportional to activity. However, because of the high component of common and fixed costs, airport and ATS provider costs do not change in proportion to activity. When traffic declines, revenue shortfalls can arise because most airport and ATC systems operate on a simple cost recovery basis. The responses to the events of September 11th have also caused substantial increases in security costs. To the extent these costs are passed forward to system users, they will increase the price of travel and impact patronage further. Airlines also have substantial fixed capacity costs. The declines in traffic are often felt as an erosion of yields and fares as carriers seek to maintain traffic loads for the capacity they are going to operate. In general, the ability to pass along cost increases from providers to airlines or from airlines to passengers depends on relative supply and demand elasticities. Because infrastructure provision is often a monopoly, and the demand for airline services is price elastic, we suggest that most of the cost increases will be borne by the airlines. We also suggest that short-haul flights will be most severely impacted because the fees and taxes are a larger proportion of the fare for these flights. We also examine the extent to which additional infrastructure costs imposed on operators may exacerbate the downturn in their traffic.     

Dynamic accessibility: Incorporating day-to-day travel time reliability into accessibility measurement

Travel times and hence accessibility in urban areas are susceptible to traffic disruption caused by events such as congestion, roadworks and traffic accidents. Being highly valued by travellers, travel time reliability affects their participation in activities and thus, plays a decisive role in accessibility. The aim of the study was to develop an approach to integrate travel time reliability into the measurement of accessibility. To achieve this, we extended a commonly-used accessibility indicator to include day-to-day variability in travel times. In a case study of the accessibility to the newly-built Queen Elizabeth University Hospital (QEUH) in Glasgow, we used real-time travel times with high temporal resolution collected over a long period of time to demonstrate the applicability and the utility value of this approach compared to the standard accessibility measurement. Our results revealed that travel time reliability varied both temporally and spatially, and zones experienced relatively high levels of accessibility loss due to higher travel time variability. The proposed approach provides a more realistic representation of actual network performance, allows for assessing the effect of travel time reliability on accessibility throughout the day and will help transport planners to trace equity impacts on accessibility due to travel time unreliability.     

Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data

Accessibility metrics are gaining momentum in public transportation planning and policy-making. However, critical user experience issues such as crowding discomfort and travel time unreliability are still not considered in those accessibility indicators. This paper aims to apply a methodology to build spatiotemporal crowding data and estimate travel time variability in a congested public transport network to improve accessibility calculations. It relies on using multiple big data sources available in most transit systems such as smart card and automatic vehicle location (AVL) data. São Paulo, Brazil, is used as a case study to show the impact of crowding and travel time variability on accessibility to jobs. Our results evidence a population-weighted average reduction of 56.8% in accessibility to jobs in a regular workday morning peak due to crowding discomfort, as well as reductions of 6.2% due to travel time unreliability and 59.2% when both are combined. The findings of this study can be of invaluable help to public transport planners and policymakers, as they show the importance of including both aspects in accessibility indicators for better decision making. Despite some limitations due to data quality and consistency throughout the study period, the proposed approach offers a new way to leverage big data in public transport to enhance policy decisions.     

Public transit accessibility approach to understand the equity for public healthcare services: A case study of Greater Mumbai

Urban public health is one of the most critical yet neglected aspects of urban planning in developing countries such as India. Inequity in access to government healthcare facilities affects the overall urban population and can substantially negatively impact the vulnerable population, who mostly rely on government healthcare services. In this paper, the accessibility measure for healthcare services by public transport is developed using travel time and the number of transit stops (accounting for transit connectivity) for Greater Mumbai. We also identified socially vulnerable wards (administrative units) using a Social Vulnerability Index (SVI), developed based on 16 indicators using Principal Component Analysis (PCA). Developed regression models showed that the proposed accessibility measure explains the coverage and usage of healthcare services better than the traditional accessibility measure, which is based on only aggregate level travel time impedances. South Mumbai has relatively better accessibility for public hospitals and dispensaries, whereas, lower level of accessibility is observed in the eastern part for public healthcare services. Assessment for the spatial inequity based on the Gini index, bivariate Moran's I, and mean access value reveals a higher degree of spatial inequity for accessing government hospitals for the slum population. The study developed a decision framework to suggest effective policy measures, which can be prioritised based on SVI to reduce the disparity in the spatial distribution of accessibility to government healthcare systems for vulnerable groups. Our findings can aid transportation and urban planners, health researchers, and policymakers to improve accessibility in under-served areas and give special attention to the needs of the vulnerable population.     

Accessibility impacts of China’s high-speed rail network

The large-scale implementation of High-Speed Rail (HSR) network in China not only offers a new option for travelers’ mode choice, but also may influence, or even generate, the redistribution of demographic and economic activities. As has been observed over the past several years in other countries, the impact of HSR spans a wide range. However, few quantitative studies have been conducted to measure this impact. As a new attempt, this study uses accessibility analysis for quantifying the impact of China’s HSR network. Weighted average travel times and travel costs, contour measures, and potential accessibility are employed as indicators of accessibility at the macro or national level. Forty-nine major cities in the HSR network are used in the accessibility analysis. Accessibility quantification and spatial distribution analysis for the study cities are performed on a Geographical Information System (GIS) platform. Accessibilities associated with varying availabilities of HSR, conventional rail, and airline are estimated and compared. The selected indicators and computational methods are found effective in evaluating the accessibility impacts of HSR from different conceptualization strategies and perspectives. They also offer complementary information on accessibility capacity of the study cities created by the HSR network.     

Can information promote transportation-friendly location decisions? A simulation experiment

Where people live, work, shop, and recreate fundamentally determines their local travel options. Yet, information problems such as the cost of conducting comprehensive searches and cognitive load have been shown to limit decision-making. In the context of residential decision-making, information problems are likely to influence which locations get chosen. This study examines whether providing people seeking a rental home with map-based information about the transit and pedestrian accessibility of the available units might influence their residential location choices. More specifically, would some people make use of this information to select more accessible residences than they would have otherwise chosen?This proposition was tested through an experimental research design in a laboratory setting. Graduate student participants were asked to select their top choices of where to live after reviewing a database of residential properties custom-designed for this study. In order to assess the influence of accessibility information, we divided participants randomly into control and experimental groups, with the former receiving baseline information currently available and the latter receiving map-based supplemental property information on multi-modal accessibility to desirable destinations.The study results suggest that providing multi-modal accessibility information to people who are relocating will enhance the attractiveness of locations that support multiple travel modes. If this is true for broader populations, then planners and policy makers may be able to increase use of non-auto modes by providing multi-modal transportation information to people at the time when they are looking for a new residence.