A simulation‐based reliability assessment approach for congested transit network

This paper is an attempt to develop a generic simulation‐based approach to assess transit service reliability, taking into account interaction between network performance and passengers' route choice behaviour. Three types of reliability, say, system wide travel time reliability, schedule reliability and direct boarding waiting‐time reliability are defined from perspectives of the community or transit administration, the operator and passengers. A Monte Carlo simulation approach with a stochastic user equilibrium transit assignment model embedded is proposed to quantify these three reliability measures of transit service. A simple transit network with a bus rapid transit (BRT) corridor is analysed as a case study where the impacts of BRT components on transit service reliability are evaluated preliminarily.     

Reducing the cost of peak hour transit service through contracting out service

Transit service contracting has responded to fiscal and financial woes of public transit agencies as the most uniquely attractive cost‐saving strategy at present. Most transit service contracting, however, has been in the traditional provision of entire fixed route bus service or commuter express bus service, and exclusive demand responsive service for the general public or for special disadvantaged population groups such as the elderly and/or the handicapped. This paper presents a new module in transit service contracting whereby the public and private operators jointly provide the peak service on the same route and at the same time. While the public agency provides the base demand of the service, the private provider provides the excess demand, both following the same schedules and similar service arrangements. In this paper, proposed service arrangements, costing and contracting procedures are discussed. It is also reported that substantial cost savings ranging from 32 to 57% with an average savings of 48% can be achieved if the excess peak hour bus transit service on highly peaked routes in public transit agencies is contracted to competing private operator(s).     

Modeling a rail transit alignment considering different objectives

An optimization model for station locations for an on-ground rail transit line is developed using different objective functions of demand and cost as both influence the planning of a rail transit alignment. A microscopic analysis is performed to develop a rail transit alignment in a given corridor considering a many-to-one travel demand pattern. A variable demand case is considered as it replicates a realistic scenario for planning a rail transit line. A Genetic Algorithm (GA) based on a Geographical Information System (GIS) database is developed to optimize the station locations for a rail transit alignment. The first objective is to minimize the total system cost per person, which is a function of user cost, operator cost, and location cost. The second objective is to maximize the ridership or the service coverage of the rail transit alignment. The user cost per person is minimized separately as the third objective because the user cost is one of the most important decision-making factors for planning a transit system from the users’ perspective. A transit planner can make an informed decision between various alternatives based on the results obtained using different objective functions. The model is applied in a case study in the Washington, DC area. The optimal locations and sequence of stations obtained using the three objective functions are presented and a comparative study between the results obtained is shown in the paper. In future works we will develop a combinatorial optimization problem using the aforementioned objectives for the rail transit alignment planning and design problem.     

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.     

Modeling transit vehicle repair duration and active service time

Abstract

The need for dependable and flexible models of transit vehicle maintenance has been well established in the literature as a means for improving daily operations, capital planning and service quality. Stemming from the practical need to predict the duration of maintenance activities and active service time for buses, this paper uses the principles of duration modeling to address two important questions: what is the duration of vehicle maintenance activities and, given that a bus is in active service, how long will it take? We extend previous work by including exogenous factors directly affecting maintenance duration and active service time in fully parametric duration models and examine such activities for the transit system in Athens (Greece). Results indicate that vehicle age, kilometers travelled and repair type are amongst the most important determinants of maintenance duration.     

Extraboard team sizing: An analysis of short unscheduled absences among regular transit drivers

Several factors contribute to short-duration unscheduled absences of bus transit drivers. This article aims to understand these factors at the aggregate level and to anticipate future total absence that will need to be filled for a large-size transit operator. The aggregate level is defined as the total number of regular driver absences per garage, day of week and time period that need to be covered by the extraboards. This study analyzes absenteeism data obtained from OC Transpo, the transit provider of the city of Ottawa, Canada. A multilevel regression model is generated to investigate regular drivers’ absences. The short-unscheduled absence is estimated in relation to temporal factors, drivers’ personal characteristics, aspects of assigned work, and service delivery characteristics. Furthermore, using the model’s coefficients, sensitivity analyses are conducted to demonstrate the advantages of this technique over traditional ones adopted by various transit agencies. This study provides transit planners and policy makers with a practical methodology that can be used to support extraboard planning practice and help reduce the incidence of missed trips due to absences while having the appropriate size of extraboard drivers.     

Modeling and optimizing urban bus transit considering headway variation for cost and service reliability analysis

Due to the stochastic nature of traffic conditions and demand fluctuations, it is a challenging task for operators to maintain reliable services, and passengers often suffer from longer travel times. A failure to consider this issue while planning bus services may lead to undesirable results, such as higher costs and a deterioration in level of service. Considering headway variation at route stops, this paper develops a mathematical model to optimize bus stops and dispatching headways that minimize total cost, consisting of both user and operator costs. A Genetic Algorithm is applied to search for a cost-effective solution in a real-world case study of a bus transit system, which improves service reliability in terms of a reduced coefficient of variation of headway.     

Characterizing,measuring, and managing transit service quality

Recent studies to evaluate the quality of transit service are generating a good amount of renewed interest in an old idea, the passenger's perspective; this new interest stems from recognizing that transit service quality should be characterised, measured, and managed by parameters capturing both passenger and transit operator perspectives. However, although the selected parameters are user‐oriented in their input, the output may not be as user‐oriented as considered, and the number or the percentage of passengers is often neglected. As a result, the findings are often misleading because the perspectives of transit operators dominate. Therefore, academics and practitioners must rethink their strategies of quality analysis of public transportation by stressing more on the role of passengers. These challenges are addressed in this paper with a practical, simple, and holistic framework, for Transit Quality (TRANSQUAL). This framework provides for the involvement of all stakeholders in the characterisation, measurement, and management of the stages of quality monitoring, which is jointly analyzed at different planning levels. In the characterization stage, the framework supports the selection of parameters to be monitored. The measurement stage sets and measures four quality areas in terms of percentage of passengers who expect a predefined level of service, for whom the service is designed, who receive the planned service, and who perceive the service as delivered. The management stage computes the differences between these percentages, points out criticalities, and recommends corrective actions. These stages are investigated in‐depth, integrated, and discussed in a real‐life case study. Copyright © 2016 John Wiley & Sons, Ltd.     

Bus Transit Service Reliability and Improvement Strategies: Integrating the Perspectives of Passengers and Transit Agencies in North America

Abstract

Transit agencies are consistently trying to improve service reliability and attract new passengers by employing various strategies. Previous literature reviews have focused on either passengers' or transit agencies' perspectives on service reliability. However, none of the earlier reviews have simultaneously addressed these differing perspectives on service reliability in an integrated manner. In response to this gap in the literature, this paper first reviews previous work on passengers' perspectives of transit service reliability and their response to service adjustments made by different agencies. Second, it analyzes transit agencies' plans and reports regarding their reliability goals and used strategies in order to improve service reliability, while looking at the impacts of these strategies on service. Reviewing these two parts together provides a needed contribution to the literature from a practical viewpoint since it allows for the identification of gaps in the public transit planning and operations field in the area of reliability and provides transit planners and decision makers with effective and valuable policy-relevant information.     

Statistical and machine learning approach for planning dial-a-ride systems

Door-to-door transportation service for elderly and persons with disabilities is often called dial-a-ride (DAR), and is usually provided by transit agencies through private contractors. Growth in DAR ridership is reported across the United States and this tendency will likely continue due to aging population. Such trends encourage development of models that can provide decision support in planning new DAR systems or expanding existing ones. Several statistical models were previously developed to predict the required DAR system capacity, given various characteristics of the service region, level-of-service requirements and operator constraints. Our work contributes to this line of research by proposing statistical and machine learning approaches that provide more accurate predictions over a wider range of scenarios. This is accomplished through transformation of variables and application of generalized linear model and support vector regression. Proposed models are built into an online tool that can help transit planners and policy makers: (a) estimate the capacity and operating cost of a DAR system needed to provide the desired level of service, (b) explore tradeoffs between system costs and levels of service, and (c) compare the cost of providing DAR service with other transportation alternatives (e.g., taxi, conventional transit).     

An activity-based approach for scheduling multimodal transit services

This paper proposes a new activity-based transit assignment model for investigating the scheduling (or timetabling) problem of transit services in multi-modal transit networks. The proposed model can be used to generate the short-term and long-term timetables of multimodal transit lines for transit operations and service planning purposes. The interaction between transit timetables and passenger activity-travel scheduling behaviors is captured by the proposed model, as the activity and travel choices of transit passengers are considered explicitly in terms of departure time choice, activity/trip chain choices, activity duration choice, transit line and mode choices. A heuristic solution algorithm which combines the Hooke–Jeeves method and an iterative supply–demand equilibrium approach is developed to solve the proposed model. Two numerical examples are presented to illustrate the differences between the activity-based approach and the traditional trip-based method, together with comparison on the effects of optimal timetables with even and uneven headways. It is shown that the passenger travel scheduling pattern derived from the activity-based approach is significantly different from that obtained by the trip-based method, and that a demand-sensitive (with uneven headway) timetable is more efficient than an even-headway timetable.     

Importance of user perception in evaluating level of service for bus transit for a developing country like India: a review

Assessment of service quality in bus transit planning has received due attention in recent years from the viewpoint of optimal service allocation. The concept of level of service (LOS) has emerged as an effective tool to measure quality of services. Service-quality assessment provides operators with knowledge on users' satisfaction with existing services and their expected LOSs. The importance of user perception towards assessment of LOS has been acknowledged by researchers. While LOS standards for public transportation have been established by the Transportation Research Board in the USA, researchers have questioned the applicability of these standards in the context of different geographic regions. Since the service delivery environment differs between developed and developing nations, the user perception of service quality varies between these economic regions. Substantial research has been carried out in the context of both developed and developing nations, to identify the bus transit service parameters that affect users' perceived service quality; however, little research exists that establishes LOS thresholds for bus transit, based on user perception. This paper reviews the concept of LOS, describes the importance of user perception in assessment of service quality and identifies the need to establish LOS thresholds for bus transit from user perception for developing countries.     

The Downs–Thomson paradox with imperfect mode substitutes and alternative transit administration regimes

The Downs–Thomson paradox (D–T paradox) occurs when expansion of a congested and untolled highway undermines scale economies of a competing transit service, leaving users of both modes worse off. The standard analysis of the D–T paradox is based on several stringent assumptions: fixed total travel demand, perfect substitutability between automobile and transit trips, and no transit crowding. This paper re-examines the paradox when these assumptions are relaxed while retaining the usual assumption that there is no congestion interaction between the modes. It also broadens consideration to alternative transit administration regimes. In the standard treatment the transit operator is obliged to cover its costs. In this paper we also study two other regimes: transit profit maximization, and system-wide welfare maximization with no financing constraint. We examine how the transit system operator responds to highway capacity expansion in each regime, and how this affects welfare for drivers and transit users. We show that in all regimes the full price of transit declines only if the full price of driving falls as well. Thus, drivers are more likely to benefit from highway expansion than transit riders. The D–T paradox cannot occur in the profit maximization or unconstrained welfare maximization regimes. In the traditional self-financing regime transit service deteriorates, but the D–T paradox is not inevitable. Numerical analysis suggests that it can occur only when automobile and transit trips are nearly perfect substitutes.     

Investigating the impact of stochastic vehicle arrivals to optimal stop spacing and headway for a feeder bus route

Stop spacing and service frequency (i.e., the inverse of headway) are key elements in transit service planning. The trade‐offs between increasing accessibility and reducing travel time, which affect transit system performance, need to be carefully evaluated. The objective of this study is to optimize stop spacing and headway for a feeder bus route, considering the relationship between the variance of inter‐arrival time (VIAT), which yields the minimum total cost (including user and operator costs). A solution algorithm, called successive substitution, is adapted to efficiently search for the optimal solutions. In a numerical example, the developed model is applied to planning a feeder bus route in Newark, New Jersey. The results indicate that the optimal stop spacing should be longer that those suggested by previous studies where the impact of VIAT was ignored. Reducing VIAT via certain operational control strategies (i.e., holding/stop‐skipping, transit signal priority) may shorten stop spacing and improve accessibility. Copyright © 2014 John Wiley & Sons, Ltd.     

A survey on planning semi-flexible transit systems: Methodological issues and a unifying framework

When demand for transportation is low or sparse, traditional transit cannot provide efficient and good-quality service, due to its fixed structure. New transportation alternatives are therefore increasingly proposed, combining on-demand service adjustment capabilities to the regular route and schedule characteristics of traditional transit. Such so-called semi-flexible systems require careful planning, but no formalization of the corresponding decisions problems, nor any comprehensive methodology has been proposed yet. This paper aims at contributing to fill this gap by presenting a comprehensive literature review, and a general and unifying modeling framework for representing and planning semi-flexible systems. The latter takes the form of the Demand Adaptive Systems, which generalizes the semi-flexible systems described in the literature, and also offers a number of advanced features, the scheduling mechanism, in particular. The paper then provides a classification of planning decisions, which is used to structure a comprehensive and comparative literature review of the field of semi-flexible systems, including methodological contributions as well as a number of particularly significant practical experiences.     

Economic impact of a supply change in mass transit in urban areas: A Canadian example

This paper aims at estimating the economic impact of a supply change in the bus transit service in a Canadian city of medium size. By using a quasi-experiment approach and a difference-in-differences (DID) estimator, it evaluates the impact of the introduction of a rapid bus transit (RBT) in Quebec City (Canada) through a spatio-temporal analysis of house price variations. The hedonic price model shows that the new service generates an increase in house price ranging from 6.9% to 2.9%, for those properties located close to the service corridor where the population is quite dense and where the service was offered initially. Using sales transaction data and municipal assessment records from 1997, the effect on price is translated into an economic impact for the whole region. The paper shows that the improvement in public transit supply generates, for Quebec City, a significant fiscal impact estimated to $6 M and a plus-value for properties owners close to $35 M over 12 years. Finally, the implications of this kind of analysis for urban planning and development are discussed.     

Demi-flexible operating policies to promote the performance of public transit in low-demand areas

The efforts of providing attractive transport service to residents in sparse communities have previously focused on operating flexible transit services. This paper identifies a new category of transit policies, called demi-flexible operating policies, to fill the gap between flexible transit services and conventional fixed-route systems. The passenger cost function is defined as the performance measure of transit systems and the analytic work is performed based on a real-world flag-stop transit service, in which we compare its system performance with another two comparable systems, the fixed-route and flex-route services, at expected and unexpected demand levels in order to be closer to reality. In addition, the dynamic-station policy is introduced to assist the flex-route service to better deal with unexpectedly high demand. Experiments demonstrate the unique advantages of demi-flexible operating policies in providing affordable, efficient, and reliable transport service in low-demand operating environments and this work is helpful to optimize the unifying framework for designing public transit in suburban and rural areas.     

Non-commitment bias in public opinion on transit usage

Estimation of ridership on a new transit system in an area where no comparable service existed before is a difficult task of transit planning. Traditional modal split models cannot be used in these cases, because no data or basis for developing a new model or adjusting a “borrowed” model are available. One of the techniques which can be used in this type of situation, is to perform a “concept test” based on public opinion. This approach, however, is plagued with the phenomenon of non-commitment bias of interviewees, and tends to overestimate the ridership. A new fixed route and fixed schedule transit service in Johnson City in Tennessee provided a rare opportunity to perform an investigation on the non-commitment bias through “before” and “after” surveys. The analysis of the non-commitment and actual responses of a sample of residents revealed substantial bias. Overall, the non-commitment ridership estimate was about twice (100% greater than) the actual ridership.:It was also observed that the bias was higher for persons owning automobiles, and for work and shopping trips.     

Transportation service procurement problem with transit time

In this work, we investigate transit time in transportation service procurement, which is conducted by shippers using auctions to purchase transportation service from carriers in the planning stage. Besides cost, we find that many shippers are most concerned with transit time in practice; shorter transit time indicates better transportation service. To minimize both the total cost and transit time, the problem faced by shippers is the biobjective transportation service procurement problem with transit time. To solve the problem, we introduce a biobjective integer programming model that can also accommodate some important business constraints. A biobjective branch-and-bound algorithm that finds all extreme supported nondominated solutions is developed. To speed up the algorithm, two fast feasibility checks, a network flow model for particular subproblems, and lower bounds from relaxation are proposed. In addition, a sophisticated heuristic is introduced to meet shipper’s requirements in some situations. Computational experiments on evaluating the performance of the algorithms are conducted on a set of test instances that are generated from practical data.     

Traditional neighborhoods and commuting in the San Francisco Bay area

Neo-traditional designs, proponents argue, reduce dependency on the automobile and provide attractive environments for walking, bicycling, and transit riding. This paper explores the extent to which this proposition holds for seven traditional neighborhoods in the San Francisco Bay Area that evolved around early streetcar services. Matched-pair comparisons of modal shares and trip generation rates for work trips are made between these neighborhoods and newer auto-oriented suburbs, controlling for the effects of income and, to a lesser extent, existing bus service levels. Pedestrian/bicycle modal shares and trip rates tended to be considerably higher, in some cases five time as high, in transit-oriented than in the paired auto-oriented neighborhood. Transit neighborhoods also averaged around 70 more daily transit work trips per 1,000 households than auto-oriented neighborhoods, though trip rates varied considerably among neighborhood pairs. Higher residential densities were also found to have a proportionately greater impact on transit commuting in transit-oriented than in auto-oriented neighborhoods. The paper concludes that in order to yield significant transportation benefits, neo-traditional development must be coordinated with larger regional planning efforts and public policy initiatives to reduce automobile dependency.