Estimating light-rail transit peak-hour boarding based on accessibility at station and route levels in Wuhan,China

Promoting public transit is a well-recognized policy for sustainable urban transport development. Transit demand analysis proves to be a challenging task in fast growing cities, partially due to the lack of reliable data and applicable techniques for rapidly changing urban contexts. This paper presents an effort to meet the challenge by developing a framework to estimate peak-hour boarding at light-rail transit (LRT) stations. The core part of the framework is an accessibility-weighted ridership model that multiplies potential demand by integral LRT accessibility. Potential demand around LRT stations is generated by using a distance-decay function. The integral LRT accessibility is a route-level factor that indicates the degree of attractiveness to LRT travel for stations in an LRT corridor. A case study in Wuhan, China, shows that the proposed method produces results useful for improving transit demand analysis.     

A utility-based travel impedance measure for public transit network accessibility

A utility-based travel impedance measure is developed for public transit modes that is capable of capturing the passengers’ behaviour and their subjective perceptions of impedance when travelling in the transit networks. The proposed measure is time-dependent and it estimates the realisation of the travel impedance by the community of passengers for travelling between an origin–destination (OD) pair.The main advantage of the developed measure, as compared to the existing transit impedance measures, relates to its capability in capturing the diversity benefit that the transit systems may offer the society of travellers with different traveling preferences. To clarify the necessity of such capability, we demonstrate the randomness (subjectivity) of travel impedance perceived by transit passengers, through evidence from the observed path choices made in the transit network of the greater Brisbane metropolitan region in Australia.The proposed impedance measure is basically a nested logit “logsum” composition over a generated set of reasonable path options whose systematic utilities are evaluated based on a discrete choice model previously developed and calibrated for the greater Brisbane transit passengers. As a case study, the proposed impedance measure is calculated for all the origin blocks in the Brisbane area, during the morning commutes to the Central Business District (CBD). The results are presented and discussed, and intuitive and important advantages are demonstrated for the proposed measure.     

The cost of equity: Assessing transit accessibility and social disparity using total travel cost

Social equity is increasingly incorporated as a long-term objective into urban transportation plans. Researchers use accessibility measures to assess equity issues, such as determining the amount of jobs reachable by marginalized groups within a defined travel time threshold and compare these measures across socioeconomic categories. However, allocating public transit resources in an equitable manner is not only related to travel time, but also related to the out-of-pocket cost of transit, which can represent a major barrier to accessibility for many disadvantaged groups. Therefore, this research proposes a set of new accessibility measures that incorporates both travel time and transit fares. It then applies those measures to determine whether people residing in socially disadvantaged neighborhoods in Montreal, Canada experience the same levels of transit accessibility as those living in other neighborhoods. Results are presented in terms of regional accessibility and trends by social indicator decile. Travel time accessibility measures estimate a higher number of jobs that can be reached compared to combined travel time and cost measures. However, the degree and impact of these measures varies across the social deciles. Compared to other groups in the region, residents of socially disadvantaged areas have more equitable accessibility to jobs using transit; this is reflected in smaller decreases in accessibility when fare costs are included. Generating new measures of accessibility combining travel time and transit fares provides more accurate measures that can be easily communicated by transportation planners and engineers to policy makers and the public since it translates accessibility measures to a dollar value.     

Household-level commuting mode choices,car allocation and car ownership level choices of two-worker households: the case of the city of Toronto

The paper presents a comprehensive investigation on household level commuting mode, car allocation and car ownership level choices of two-worker households in the City of Toronto. A joint econometric model and a household travel survey dataset are used for empirical investigations. Empirical models reveal that significant substitution patterns exist between auto driving and all other mode choices in two-worker households. It is revealed that, female commuters do not prefer auto driving, but in case of a one car (and two commuters with driving licenses) household, a female commuter gets more preference for auto driving option than the male commuter. Reverse commuting (commuting in opposite direction of home to central business district) plays a critical role on household level car allocation choices and in defining the stability of commuting behaviour of two-worker households. Two worker households in higher income zones and with longer commuting distances tend to have higher car ownership levels than others. However, higher transit accessibility to jobs reduces household car ownership levels. The study reveals that both increasing two worker households and reverse commuting would increase dependency on private car for commuting.     

Exploring built environment impacts on transit use – an updated meta-analysis

ABSTRACT

The built environment (BE) is widely accepted to influence transit use (TU). Evidence to date suggests the relationship is dependent on many factors which can be difficult to account for in quantitative studies. This creates barriers to transferring research into practice. Considering many studies together can be useful for accounting for more of the factors impacting transit use. Yet, meta-analysis of research measuring these influences was last undertaken in 2010 based on 18 studies. Since then 90 new quantitative studies have been published. These recent studies use improved methodologies and are conducted in more diverse geographies. This paper reports an improved and updated meta-analysis of built environment impacts on transit use. It compares elasticity estimates from research published pre-and post-2010 and explores the impact of new methods and a more diverse geographical representation on findings. Updated meta-elasticities range from <0.01 to 0.26; a similar range to the 2010 study. However, at the individual indicator levels, more recent results are different. Elasticities for urban density, including population, employment and commercial density, have increased significantly in studies published since 2010, as did that of land use mix. However, measures of local access, design and jobs-housing balance decreased in post-2010 studies. These results confirm the small but imprecise relationship between the BE and TU. Results also suggest that while the range of elasticity impacts is relatively consistent, new study methodologies, notably those that control for regional accessibility and self-selection, and the increasing geographical diversity in study applications, is acting to change BE-TU findings at the indicator level. Research setting and context are important to consider when using empirical results to design BE strategies to promote transit use.     

Accessibility: an evaluation using consumer welfare

This study explores the worth consumers place on mode-destination accessibility for the AM journey to work trip. To accomplish this, a multinomial mode-destination choice model is estimated and the denominator of the specified logit model is used as an estimate of mode-destination accessibility. To improve the interpretability of this measure, compensating variation is then applied to convert the mode-destination accessibility to units of dollars per AM journey to work trip. The model is estimated using travel survey data from the Puget Sound Region in Washington state. It is reasonable to assume, for example, that the worth placed on mode-destination accessibility varies by mode, by destination, and by market segment (e.g., low income, high income). Less intuitive, however, are the magnitude and direction of these variations. This paper presents a methodological approach, followed by an empirical evaluation, for examining the worth of journey to work mode- destination accessibility. The results have important policy implications and also provide a mechanism for incorporating a monetary value for accessibility in future cost-benefit analyses.     

New technology and the modeling of risk-taking behavior in congested road networks

Intelligent transport systems provide various means to improve traffic congestion in road networks. Evaluation of the benefits of these improvements requires consideration of commuters’ response to reliability and/or uncertainty of travel time under various circumstances. Various disruptions cause recurrent or non-recurrent congestion on road networks, which make road travel times intrinsically fluctuating and unpredictable. Confronted with such uncertain traffic conditions, commuters are known to develop some simple decision-making process to adjust their travel choices. This paper represents the decision-making process involved in departure-time and route choices as risk-taking behavior under uncertainty. An expected travel disutility function associated with commuters’ departure-time and route choices is formulated with taking into account the travel delay (due the recurrent congestion), the uncertainty of travel times (due to incident-induced congestion) and the consequent early or late arrival penalty. Commuters are assumed to make decision on the departure-time and route choices on the basis of the minimal expected travel disutility. Thus the network will achieve a simultaneous route and departure-time user equilibrium, in which no commuter can decrease his or her expected disutility by unilaterally changing the route or departure-time. The equilibrium is further formulated as an equivalent nonlinear complementarity problem and is then converted into an unconstrained minimization problem with the use of a gap function suggested recently. Two algorithms based on the Nelder–Mead multidimensional simplex method and the heuristic route/time-swapping approach, are adapted to solve the problem. Finally, numerical example is given to illustrate the application of the proposed model and algorithms.     

Planning transport for social inclusion: An accessibility-activity participation approach

Social equity is increasingly becoming an important objective in transport planning and project evaluation. This paper provides a framework and an empirical investigation in the Greater Toronto and Hamilton Area (GTHA) examining the links between public transit accessibility and the risks of social exclusion, simply understood as the suppressed ability to conduct daily activities at normal levels. Specifically, we use a large-sample travel survey to present a new transport-geography concept termed participation deserts, neighbourhood-level clusters of lower than expected activity participation. We then use multivariate models to estimate where, and for whom, improvements in transit accessibility will effectively increase activity participation and reduce risks of transport-related social exclusion. Our results show that neighbourhoods with high concentrations of low-income and zero-car households located outside of major transit corridors are the most sensitive to having improvements in accessibility increase daily activity participation rates. We contend that transit investments providing better connections to these neighbourhoods would have the greatest benefit in terms of alleviating existing inequalities and reducing the risks of social exclusion. The ability for transport investments to liberate suppressed activity participation is not currently being predicted or valued in existing transport evaluation methodologies, but there is great potential in doing so in order to capture the social equity benefits associated with increasing transit accessibility.     

On joint railway and housing development strategy

Transit Oriented Development (TOD) with railway service is recognized as a sustainable mode of development for highly dense megacities. In addition to providing safe and efficient transit services, reducing auto dependence and therefore less need for highway expansions, the improved accessibility of TOD influences commuters’ residential location choices and the resultant housing value. Traditionally, statistical approaches have been used to estimate the relationship between railway development and housing value for individual sites. To some degree, TOD has also been studied with integrated land-use transport models. While useful, they lack an analytical framework to study the region-wide impacts of TOD on residential location and travel choices and the resultant land value changes. In this study, the joint railway and housing development strategy is modeled based on a combined equilibrium formulation with the bid-rent process. The problem is formulated as a mathematical program with equilibrium constraints, in which the upper level optimizes the objective for the joint development strategy by deciding on the combination of housing supplies and railway service levels. Analytical results are obtained for a single corridor in a multi-modal transport network, which are further illustrated by sensitivity analyses. A numerical example is constructed to demonstrate the approach and compare with other separate development strategies. The results generally confirm the synergy between railway and housing developments.     

Adaptive traffic signal control with equilibrium constraints under stochastic demand

This study develops a methodology to model transportation network design with signal settings in the presence of demand uncertainty. It is assumed that the total travel demand consists of commuters and infrequent travellers. The commuter travel demand is deterministic, whereas the demand of infrequent travellers is stochastic. Variations in demand contribute to travel time uncertainty and affect commuters’ route choice behaviour. In this paper, we first introduce an equilibrium flow model that takes account of uncertain demand. A two-stage stochastic program is then proposed to formulate the network signal design under demand uncertainty. The optimal control policy derived under the two-stage stochastic program is able to (1) optimize the steady-state network performance in the long run, and (2) respond to short-term demand variations. In the first stage, a base signal control plan with a buffer against variability is introduced to control the equilibrium flow pattern and the resulting steady-state performance. In the second stage, after realizations of the random demand, recourse decisions of adaptive signal settings are determined to address the occasional demand overflows, so as to avoid transient congestion. The overall objective is to minimize the expected total travel time. To solve the two-stage stochastic program, a concept of service reliability associated with the control buffer is introduced. A reliability-based gradient projection algorithm is then developed. Numerical examples are performed to illustrate the properties of the proposed control method as well as its capability of optimizing steady-state performance while adaptively responding to changing traffic flows. Comparison results show that the proposed method exhibits advantages over the traditional mean-value approach in improving network expected total travel times.     

Identifying transit deserts for low-income commuters in Wuhan Metropolitan Area,China

The rapid expansion of many Chinese cities has put increasing pressure on existing urban transportation systems. Using Baidu users’ location data, this research analyzes the spatial patterns of the transit systems and commuter flows in Wuhan Metropolitan Area, China, and identifies transit deserts affecting low-income commuters. The results show that, first, most transit demand are generated by trips between neighboring communities, while large transit supply tends to occur between distant communities in the region. Second, about 11.21% of low-income commuters are affected by transit deserts in Wuhan Metropolitan Area. In detail, 61.30% of them commute within the city centers and 36.06% of them commute within the suburbs. Only about 2.64% of them actually travel between city centers and suburbs. Third, for low-income suburban commuters, transit deserts occur when they are surrounded by low-density transit infrastructure and low-frequency transit services, which makes it very difficult for them to connect to rest of the region. However, for low-income commuters residing in the city centers, transit deserts are mainly caused by the large numbers of transit-dependent people competing for limited transit supply in the areas. This research explores the relationship between transit systems and commuting demand in a major Chinese metropolitan area. The findings could help guide future transit system planning in China and beyond.     

Effects of built environment on walking at the neighbourhood scale. A new role for street networks by modelling their configurational accessibility?

The hypothesis of this paper is that some features of the built environment, particularly those concerned with the accessibility of the street network, could be associated with the proportion of pedestrians on all trips (modal split) found in different parts of a city. Quantitative analysis (bi-variate correlation and a multiple regression model) was used to establish the association between variables. The study area covered a substantial part of the metropolitan area in Madrid, Spain. Results showed a consistent influence of five particular indexes in the multi-variate model. Not surprisingly for this kind of research, four of them described density and mix of land uses. But perhaps more interestingly, the first one was a measure of the accessibility of the public space network, a less prominent variable in literature to date. This variable is called herein configurational accessibility, calculated using Space Syntax, an urban morphology theory. The relevance of configurational accessibility is probably related to its surprising ability to synthesize global and perceived properties of street networks at the same time. The findings introduce the idea that the configuration of the urban grid can influence the proportion of pedestrians (as a part of total trips in any transport mode) who choose to walk on single-journey trips. The discussion links with the current debate about walkability indexes and the need of empirical support for the chosen variables and also with transport planning. Because the relevance of the street network’s role is not so easy to grasp, inputs from configurational theory and the pedestrian potential underlying this fact are also discussed at the end of the paper.     

A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership model. Such feedback allows switching class membership in response to the changes in choice contexts. The model is used for an empirical investigation of commuting mode and departure time choices in the Greater Toronto and Hamilton Area (GTHA) by using a large sample household travel survey dataset. The empirical model reveals that overall 38% of the commuters in the GTHA are more likely to switch modes than departure times and 62% of them are more likely to do the reverse. The empirical model also reveals that the average Subjective Value of Travel Time Savings (SVTTS) of the commuters in the GTHA can be as low as 3 dollars if a single choice pattern of departure time choices nested within mode choices is considered. It can also be as high as 67 dollars if the opposite nesting structure is assumed. However, the LCM estimates the average SVTTS to be around 27 dollars in the GTHA. An empirical scenario analysis by using the estimated model indicates that a 50% increase in morning peak period car travel time does not sway more than 4% of commuters from the morning peak period.

     

Flow-based accessibility measurement: The Place Rank approach

In this paper, we empirically test the viability of a flow-based approach as an alternative to transport accessibility measurement. To track where commuters travel from and to (but not commute times), we use transactional smartcard data from residents in Singapore to construct the (daily) spatial network of trips generated. We use the Place Rank method to demonstrate the viability of the flow-based approach to study accessibility. We compute the Place Rank of each of 44 planning areas in Singapore. Interestingly, even though the spatial network is constructed using only origin–destination information, we find that the travel time of the trips out of each planning area generally decreases as the area’s Place Rank increases. The same is also the case for in-vehicle time, number of transfers in the network and transfer time. This shows that a flow-based approach can be used to measure the notion of accessibility, which is traditionally assessed using travel time information in the system. We also compare Place Rank with other indicators, namely, bus stop density, eigenvector centrality, clustering coefficient and typographical coefficient to evaluate an area’s accessibility. The results show that these indicators are not as effective as the Place Rank method.     

Transportation serviceability analysis for metropolitan commuting corridors based on modal choice modeling

Major commuting corridors in metropolitan areas generally comprise multiple transportation modes for commuters, such as transit (subways or buses), private vehicles, or park-and-ride combinations. During the morning peak hour, the commuters would choose one of the available transportation modes to travel through the corridors from rural/suburban living areas to urban working areas. This paper introduces a concept of transportation serviceability to evaluate a transportation mode’s service status in a specific link, route, road, or network during a certain period. The serviceability can be measured by the possibility that travelers choose a specific type of transportation service at a certain travel cost. The commuters’ modal-choice possibilities are calculated using a stochastic equilibrium model based on general travel cost. The modeling results illustrate how transportation serviceability is influenced by background traffic flow in a corridor, value of comfort for railway mode, and parking fee distribution.     

Workers wanted: Changing employee accessibility with industrial development ─ Evidence from Foxconn

In response to the trends of manufacturing revitalization and workforce shortage in the U.S., this study investigates how Foxconn changes accessibility to industrial employees by automobile and by transit in Southeast Wisconsin. Results suggest that there is a mismatch between the Foxconn site and the areas with high accessibility to industrial employees. With a great demand for labor, Foxconn reduces employee accessibility by automobile throughout the region, while its impact on employee accessibility by transit is more localized. The results inform industrial firm locations, workforce housing development, and transportation service provisions. The analysis framework shifts the angle of accessibility research to focusing on the perspective of employers, and it can be applied to investigate future large-scale economic development projects.     

A GIS-based planning approach to locating urban rail terminals

This paper develops a flexible GIS-based methodology for evaluating the potential locations of terminal park-and-ride facilities along urban rail lines. The methodology differs from political-based approaches and traditional travel demand modeling in its use of an objective measure of accessibility to gage the suitability of a site. The methodology begins by constructing an index of derived demand for rail usage based on the local demographics. Principal component analysis (PCA) is used as a means of constructing an index of derived demand consistent with other passenger surveys. Next, trade areas or commutersheds are calculated for each candidate park-and-ride location based on realistic measures of accessibility and network based drive times, taking into account competition among candidates for riders. Following the analysis, the candidate locations and their commutersheds are delineated and visualized in the GIS environment. In summary, application of this method produces a site-specific suitability index that may be used to rank and compare potential park-and-ride locations. We illustrate how our approach fits within the context of the larger-scale corridor study as a complimentary means of refining the location of urban rail stations. The analysis uses the proposed rail system for Columbus Ohio as a case study. This revised version was published online in June 2006 with corrections to the Cover Date.     

Making do: The effects of a mass transit strike on travel behavior

A brief transit strike in early December 1976 disrupted bus services to the city of Pittsburgh and surrounding Allegheny County. That strike provided an opportunity for testing a variety of approaches to increase ride-sharing and to reduce traffic congestion, and for examining the effect of the strike on traffic congestion and on individual travel behavior. Even though over 60% of the commuters to the CBD use transit, the effects of the strike were relatively mild. There was some increase in traffic flow into the CBD and some spreading of the peak period. The largest proportion of the transit commuters who made trips to the CBD during the strike were dropped off by a non-commuter, increasing highway traffic. The most severe impact was felt by those transit commuters who had no cars in the household; 25% of these commuters (only 3% of the total CBD commuters) stayed home from work on the first day of the strike. Most attempts to mitigate the impact of the strike had little effect, largely because most commuters were able to manage adequately during the short strike. The anticipated parking problem, on which much of the contingency planning was focused, did not emerge, largely because of the use of carpooling and drop-off mode by many of the transit users.     

Optimization of bus stop placement for routes on uneven topography

The improvement and expansion of public transport is an increasingly important solution to the high congestion costs and worsening environmental impacts of the car dominated transport systems seen in many cities today. The intelligent design of stop locations is one way to improve the quality of PT and thereby improve its ridership. Stop placement is a relatively complex task as it involves a trade-off between two competing goals; accessibility and operation; however this trade-off can be made explicit using an appropriate mathematical model. Many such models have been developed in the literature, however none consider the effects of uneven topography. Topography is an important but often neglected factor in the design of public transportation systems, with the potential to have a significant impact on the accessibility, operation and planning of a transit service. In this work a mathematical modelling approach to bus stop placement is developed which includes considerations of uneven topography in three ways; (1) Its effect on walking speed; (2) Its impact on the attractiveness of an access path to a transit service; and (3) Its effect on acceleration rates at stops. Because of the complexity of the model developed, a heuristic evolutionary algorithm’ is employed to approximate an optimal solution to the model. Finally, the model and solution method are applied to a case study in the Auckland CBD area in New Zealand.     

The impact of transit station areas on the travel behaviors of workers in Denver,Colorado

Transit development is one planning strategy that seeks to partially overcome limitations of low-density single use car oriented development styles. While many studies focus on how residential proximity to transit influences the travel behaviors of individuals, the effect of workplace proximity to transit is less understood. This paper asks, does working near a light rail transit station influence the travel behaviors of workers differently than workers living near a station? We begin by examining workers’ commute mode based on their residential and workplace proximity to transit station areas. Next, we analyze the ways in which personal travel behaviors differ between those who drive to work and those who do not. The data came from a 2009 travel behavior survey in the Denver, Colorado metropolitan area, which contains 8000 households, 16,000 individuals, and nearly 80,000 trips. We measure sustainable travel behaviors as reduced mileage, reduced number of trips, and increased use of non-car transportation. The results of this study indicate that living near a transit station area by itself does not increase the likelihood of using non-car modes for work commutes. But if the destination (work) is near a transit station area, persons are less likely to drive a car to work. People who both live and work in a transit station area are less likely to use a car and more likely to take non-car modes for both work and non-work (personal) trips. Especially for persons who work near a transit station area, the measures of personal trips and distances show a higher level of mobility for non-car commuters than car commuters – that is, more trips and more distant trips. The use of non-car modes for personal trips is most likely to occur by non-car commuters, regardless of their transit station area relationship.