Optimizing fare and headway to facilitate timed transfer considering demand elasticity

Fare and service frequency significantly affect transit users’ willingness to ride, as well as the supplier's revenue and operating costs. To stimulate demand and increase productivity, it is desirable to reduce the transfer time from one route to another via efficient service coordination, such as timed transfer. Since demand varies both temporally and spatially, it may not be cost-effective to synchronize vehicle arrivals on all connecting routes at a terminal. In this paper, we develop a schedule coordination model to optimize fare and headway considering demand elasticity. The headway of each route is treated as an integer-multiple of a base common headway. A discounted (reduced) fare is applied as an incentive to encourage ridership and, thus, stimulate public transit usage. The objective of the proposed coordination model is used to maximize the total profit subject to the service constraint. A numerical example is given to demonstrate the applicability of the proposed model. The results show that the optimized fare and headway may be carefully applied to yield the maximum profit. The relationship between the decision variables and model parameters is explored in the sensitivity analysis.     

Optimization Of Headway,Vehicle Size and Route Choice for Minimum Cost Feeder Service

ABSTRACT

Many people use public transportation systems to reach their destination, while others use personal vehicles. Poor transportation systems do not attract ridership. Therefore, the usage of passenger cars increases, and traffic and environmental conditions deteriorate. Efficient public transportation has been recognized as one of the potential ways of mitigating air pollution, reducing energy consumption, improving mobility and alleviating traffic congestion. The objective of this study is to optimize a bus feeder service that provides the shuttle service between a recreation center (e.g. Sandy Hook, NJ) and a major public transportation facility, subject to site-specific constraints such as vehicle schedules, bus availability, service capacity and budget. The decision variables include bus headway, vehicle size and route choice. The solution methodology integrating both analytical and numerical techniques is developed, which optimizes the decision variables. Finally, the proposed solution methodology is applied to a case study. Numerical results, including optimal solutions and sensitivity analyses, are presented while the level of coordination between the feeder service and a major transportation service is discussed.     

Why do people fare evade? A global shift in fare evasion research

ABSTRACT

Fare evasion is a significant concern for most transit authorities. The traditional approach to fare compliance has focussed on modifying the physical control of ticketing or ticket inspection rates. Yet recently the perspective on fare evasion has begun to shift toward profiling the fare evader or understanding the customer motivations to fare evade. This paper uses a literature review method to document the characteristics of these three perspectives on fare evasion: the conventional transit system perspective, the customer profiling perspective and the customer motivations perspective. We find that the conventional transit system perspective, although straightforward to measure and control, has its limits particularly in “open” transit systems. The customer profiling perspective attempts to identify, based on demographics, which customers are more likely to fare evade. However this perspective has little use beyond profiling and is ethically questionable. The customer motivations perspective provides a richer understanding of how customers define fare evasion and what attitudes, social norms and circumstances motivates them to fare evade. Considering that between 20% and 40% of a city’s residents admit to fare evading at some point, understanding these complex motivations can help improve revenue compliance at a time when most governments heavily subsidise their transit systems.     

Transport system management in San Francisco: an assessment

The paper reports the results of a transportation corridor study. The emphasis in the study is in transportation system management (TSM) policies although some capital intensive alternatives are also considered.

The results suggest that currently popular TSM policies in U.S.A., even when augmented with capital intensive changes, have only marginal impacts on modal choices. These currently popular policies, high occupancy vehicle priority lanes, improved bus and express bus service, increased feeder bus service and so forth, appear to confer benefits to well to do suburbanites but do not improve the transportation of urban dwellers.

Another interesting result is that if user costs were increased to cover the full costs of transportation the transit fares for low income people would increase ten percent and the increase for urban dwellers would be about 20 percent. Interestingly, there would be no change in bus fares for either group. However, for high income travellers and suburbanites the increase in transit fares would be in excess of 100 percent. Thus, the current fare structure is inequitable making the low income people and the urban dwellers to pay a much larger share of their transportation cost than the often well to do suburbanites.     

Integrated transit services for minimum cost operation considering heterogeneous demand

Abstract

In large metropolitan areas, public transit is a major mode choice of commuters for their daily travel, which has an important role in relieving congestion on transportation corridors. The purpose of this study is to develop a model which optimizes service patterns (SPs) and frequencies that yield minimum cost transit operation. Considering a general transit route with given stops and origin-destination demand, the proposed model consists of an objective total cost function and a set of constraints to ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is provided to demonstrate the effectiveness of the developed model, in which the demand and facility data of a rail transit route were given. Results show that the proposed model can be applied to optimize integrated SPs and headways that significantly reduce the total cost, while the resulting performance indicators are generated.     

Fare deregulation of transit services: Winners and losers in a competitive market

Currently, the Hong Kong government imposes fare control on buses and taxi while the rail services are immune to such a control. This study examined four scenarios of fare deregulation on transit services by considering three related parties of a transit system – service providers, travelers, and society in general, with their respective objectives represented as – revenue, travel utility, and congestion. Analyzing the resultant impacts on these three parties, we found that a different regulatory environment would favor or hurt a different set of parties. There is no clear win‐win situation for all parties. Deciding a socially acceptable regulatory environment is likely to involve difficult tradeoffs among these parties.     

Traffic dynamics in a bi-modal transportation network with information provision and adaptive transit services

This paper has two major components. The first one is the day-to-day evolution of travelers’ mode and route choices in a bi-modal transportation system where traffic information (predicted travel cost) is available to travelers. The second one is a public transit operator adjusting or adapting its service over time (from period to period) based on observed system conditions. Particularly, we consider that on each day both travelers’ past travel experiences and the predicted travel cost (based on information provision) can affect travelers’ perceptions of different modes and routes, and thus affect their mode choice and/or route choice accordingly. This evolution process from day to day is formulated by a discrete dynamical model. The properties of such a dynamical model are then analyzed, including the existence, uniqueness and stability of the fixed point. Most importantly, we show that the predicted travel cost based on information provision may help stabilize the dynamical system even if it is not fully accurate. Given the day-to-day traffic evolution, we then model an adaptive transit operator who can adjust frequency and fare for public transit from period to period (each period contains a certain number of days). The adaptive frequency and fare in one period are determined from the realized transit demands and transit profits of the previous periods, which is to achieve a (locally) maximum transit profit. The day-to-day and period-to-period models and their properties are also illustrated by numerical experiments.     

Optimal transit fare in a bimodal network under demand uncertainty and bounded rationality

This paper investigates the optimal transit fare in a simple bimodal transportation system that comprises public transport and private car. We consider two new factors: demand uncertainty and bounded rationality. With demand uncertainty, travelers are assumed to consider both the mean travel cost and travel cost variability in their mode choice decision. Under bounded rationality, travelers do not necessarily choose the travel mode of which perceived travel cost is absolutely lower than the one of the other mode. To determine the optimal transit fare, a bi‐level programming is proposed. The upper‐level objective function is to minimize the mean of total travel cost, whereas the lower‐level programming adopts the logit‐based model to describe users' mode choice behaviors. Then a heuristic algorithm based on a sensitivity analysis approach is designed to solve the bi‐level programming. Numerical examples are presented to illustrate the effect of demand uncertainty and bounded rationality on the modal share, optimal transit fare and system performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimizing sustainable feeder bus operation considering realistic networks and heterogeneous demand

A mathematical model is developed to optimize social and fiscal sustainable operation of a feeder bus system considering realistic network and heterogeneous demand. The objective total profit is a nonlinear, mixed integer function, which is maximized by optimizing the number of stops, headway, and fare. The stops are located which maximize the ridership. The demand elasticity for the bus service is dependent on passengers' access distance, wait time, in‐vehicle time, and fare. An optimization algorithm is developed to search for the optimal solution that maximizes the profit. The modeling approach is applied to planning a bus transit system within Woodbridge, New Jersey. Copyright © 2011 John Wiley & Sons, Ltd.     

Identifying the spatial distribution of public transportation trips by node and community characteristics

ABSTRACT

Identifying the spatial distribution of travel activities can help public transportation managers optimize the allocation of resources. In this paper, transit networks are constructed based on traffic flow data rather than network topologies. The PageRank algorithm and community detection method are combined to identify the spatial distribution of public transportation trips. The structural centrality and PageRank values are compared to identify hub stations; the community detection method is applied to reveal the community structures. A case study in Guangzhou, China is presented. It is found that the bus network has a community structure, significant weekday commuting and small-world characteristics. The metro network is tightly connected, highly loaded, and has no obvious community structure. Hub stations show distinct differences in terms of volume and weekend/weekday usage. The results imply that the proposed method can be used to identify the spatial distribution of urban public transportation and provide a new study perspective.     

The taxi's role in urban America: Today and tomorrow

Changes in the economic and demographic characteristics of US cities over the past two decades have modified but have not diminished the need for extensive public transportation service in these areas. The vast bulk of trips to work, to shop, and for most other purposes within large American cities are still made by residents of those cities, a significant portion of whom do not own or have access to an automobile. Expensive and far-ranging programs to enhance surburban commutation to the central city by means of rail rapid transit do little to meet the needs of those who still must rely upon local, extensive service within the city.One form of public transport — the taxicab — offers the quality and flexibility of service which even those of limited means find well worth the price. As a consequence, fleet taxicabs serve almost 40 percent more passengers than all US rapid transit systems and about 60 percent as many passengers as all bus transit systems. Removal of archaic and restrictive regulations governing the number and use of taxicabs in major US cities would promote more effective and widespread use of this, the only form of public transit that still operates — at a profit — without public subsidy.     

Public transit service operation strategy under indifference thresholds‐based bi‐modal equilibrium

This paper investigates public transit service (fare and frequency) operation strategies in a bi‐modal network with assumption of indifference thresholds‐based travelers' mode choice behavior. Under such behavior, users would switch to a new mode only if its utility is larger than the utility of current mode plus a threshold. The concept of indifference thresholds‐based bi‐modal equilibrium (ITBE) and the properties of the ITBE solution are explicitly proposed. Considering transit operator's different economic objectives (profit‐maximizing, no‐deficit and total system cost‐minimizing), the effect of indifference thresholds on transit fare and frequency schemes is studied. Some numerical experiments are accompanied to verify the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

Monopoly,Subsidies and the Mohring Effect: A Synthesis

Abstract

This paper provides a unifying framework to analyze whether a monopoly transit provider will under or over-supply frequency. To this end we couch the problem in term of Spence [(1975). Monopoly, quality and regulation. The Bell Journal of Economics, 6, 417–429] who analyzed the incentives to provide quality by a monopolist. We show that all of the results of a recent academic exchange discussing this topic are special cases of Spence [(1975). Monopoly, quality and regulation. The Bell Journal of Economics, 6, 417–429], albeit with an adjustment in order to take into account the cost structure of frequency provision in the case of public transport. In theory then, there are cases when a monopolist may offer optimal or above optimal levels of frequency without requiring subsidies. However, public transport is rarely provided by an unregulated monopolist. Rather, these services are usually provided either by an exclusive operator under regulated fares or by a group of competing operators, with or without fare regulation. We show that in the first case frequency will always be below the social optimal level.     

Assessing social equity in distance based transit fares using a model of travel behavior

The goal of this study is to develop and apply a new method for assessing social equity impacts of distance-based public transit fares. Shifting to a distance-based fare structure can disproportionately favor or penalize different subgroups of a population based on variations in settlement patterns, travel needs, and most importantly, transit use. According to federal law, such disparities must be evaluated by the transit agency, but the area-based techniques identified by the Federal Transit Authority for assessing discrimination fail to account for disparities in distances travelled by transit users. This means that transit agencies currently lack guidelines for assessing the social equity impacts of replacing flat fare with distance-based fare structures. Our solution is to incorporate a joint ordinal/continuous model of trip generation and distance travelled into a GIS Decision Support System. The system enables a transit planner to visualize and compare distance travelled and transit-cost maps for different population profiles and fare structures. We apply the method to a case study in the Wasatch Front, Utah, where the Utah Transit Authority is exploring a switch to a distance-based fare structure. The analysis reveals that overall distance-based fares benefit low-income, elderly, and non-white populations. However, the effect is geographically uneven, and may be negative for members of these groups living on the urban fringe.     

Policy analysis of third party electronic coupons for public transit fares

Mobile technologies are generating new business models for urban transport systems, as is evident from recent startups cropping up from the private sector. Public transport systems can make more use of mobile technologies than just for measuring system performance, improving boarding times, or for analyzing travel patterns. A new transaction model is proposed for public transport systems where travelers are allowed to pre-book their fares and trade that demand information to private firms. In this public-private partnership model, fare revenue management is outsourced to third party private firms such as big box retail or large planned events (such as sports stadiums and theme parks), who can issue electronic coupons to travelers to subsidize their fares. This e-coupon pricing model is analyzed using marginal cost theory for the transit service and shown to be quite effective for monopolistic coupon rights, particularly for demand responsive transit systems that feature high cost fares, non-commute travel purposes, and a closed access system with existing pre-booking requirements. However, oligopolistic scenarios analyzed using game theory and network economics suggest that public transport agencies need to take extreme care in planning and implementing such a policy. Otherwise, they risk pushing an equivalent tax on private firms or disrupting the urban economy and real estate values while increasing ridership.     

Nature and/or nurture? Analyzing the determinants of transit ridership across US urbanized areas

Public subsidy of transit services has increased dramatically in recent years, with little effect on overall ridership. Quite obviously, a clear understanding of the factors influencing transit ridership is central to decisions on investments in and the pricing and deployment of transit services. Yet the literature about the causes of transit use is quite spotty; most previous aggregate analyses of transit ridership have examined just one or a few systems, have not included many of the external, control variables thought to influence transit use, and have not addressed the simultaneous relationship between transit service supply and consumption. This study addresses each of these shortcomings by (1) conducting a cross-sectional analysis of transit use in 265 US urbanized areas, (2) testing dozens of variables measuring regional geography, metropolitan economy, population characteristics, auto/highway system characteristics, and transit system characteristics, and (3) constructing two-stage simultaneous equation regression models to account for simultaneity between transit service supply and consumption. We find that most of the variation in transit ridership among urbanized areas – in both absolute and relative terms – can be explained by factors outside of the control of public transit systems: (1) regional geography (specifically, area of urbanization, population, population density, and regional location in the US), (2) metropolitan economy (specifically, personal/household income), (3) population characteristics (specifically, the percent college students, recent immigrants, and Democratic voters in the population), and (4) auto/highway system characteristics (specifically, the percent carless households and non-transit/non-SOV trips, including commuting via carpools, walking, biking, etc.). While these external factors clearly go a long way toward determining the overall level of transit use in an urbanized area, we find that transit policies do make a significant difference. The observed range in both fares and service frequency in our sample could account for at least a doubling (or halving) of transit use in a given urbanized area. Controlling for the fact that public transit use is strongly correlated with urbanized area size, about 26% of the observed variance in per capita transit patronage across US urbanized areas is explained in the models presented here by service frequency and fare levels. The observed influence of these two factors is consistent with both the literature and intuition: frequent service draws passengers, and high fares drive them away.     

Normative framework for transit fare policy-making

This paper presents a normative model for transit fare policy-making. Key elements of the model are: establishing service policy and ridership objectives, developing an overall financial philosophy, making fare level decisions, making structural pricing decisions, and designing implementation strategies. In general, the overall objectives of a transit agency regarding service quality and ridership levels should be the main impetus behind any fare program. Identifying where transit lies on the continuum of being a public versus a private service should frame the overall financial philosophy of a transit agency. From this the specification of farebox recovery targets should follow. Deciding upon structural aspects of a fare program perhaps represents one of the most important and most frequently overlooked steps of the process. Specific cost-based and value-based fare strategies should be considered. Implementation involves making the adopted fare strategy work. Key implementation issues are: fare payment and collection techniques, necessary service changes, marketing and promotional programs, and consensus-building. The model presented calls for feedback among these steps to allow an iterative, yet comprehensive, approach to fare policy-setting.     

Illuminating the unseen in transit use: A framework for examining the effect of attitudes and perceptions on travel behavior

This study develops the Perception–Intention–Adaptation (PIA) framework to examine the role of attitudes, perceptions, and norms in public transportation ridership. The PIA framework is then applied to understand the relative importance of socio-demographic, built environment, transit service, and socio-psychological factors on public transit use for 279 residents of south Los Angeles, California, a predominately low-income, non-white neighborhood. Confirmatory factor analysis based on 21 survey items resulted in six transit-relevant socio-psychological factors which were used in regression models of two measures of transit use: the probability of using transit at least once in the 7-day observation period, and the mean number of daily transit trips. Our analysis indicates that two PIA constructs, attitudes toward public transportation and concerns about personal safety, significantly improved the model fit and were robust predictors of transit use, independent of built environment factors such as near-residence street network connectivity and transit service level. Results indicate the need for combined policy approaches to increasing transit use that not only enhance transit access, but also target attitudes about transit service and perceptions of crime on transit.     

Drivers of transit service loyalty considering heterogeneity between user segments

Users’ loyalty to public transit service is fundamental to promote its popularity in the transportation market. A four-step analytical framework is advanced to investigate the importance of service attributes that heterogeneous transit user segments place on their public transit service loyalty, measured in terms of overall satisfaction and re-use intention. Critical service attributes perceived by transit users that are relevant for loyalty enhancement are explicitly determined, which vary between user segments. It is suggested that the design of strategies aimed to promote the use of public transit by increasing user loyalty towards transit service be targeted at specific attributes that contribute most to loyalty and specific user segments whose original loyalty level is significantly different to others.     

Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data

Transit fares are an effective tool for demand management. Transit agencies can raise revenue or relieve overcrowding via fare increases, but they are always confronted with the possibility of heavy ridership losses. Therefore, the outcome of fare changes should be evaluated before implementation. In this work, a methodology was formulated based on elasticity and exhaustive transit card data, and a network approach was proposed to assess the influence of distance-based fare increases on ridership and revenue. The approach was applied to a fare change plan for Beijing Metro. The price elasticities of demand for Beijing Metro at various fare levels and trip distances were tabulated from a stated preference survey. Trip data recorded by an automatic fare collection system was used alongside the topology of the Beijing Metro system to calculate the shortest path lengths between all station pairs, the origin–destination matrix, and trip lengths. Finally, three fare increase alternatives (high, medium, and low) were evaluated in terms of their impact on ridership and revenue. The results demonstrated that smart card data have great potential with regard to fare change evaluation. According to smart card data for a large transit network, the statistical frequency of trip lengths is more highly concentrated than that of the shortest path length. Moreover, the majority of the total trips have a length of around 15 km, and these are the most sensitive to fare increases. Specific attention should be paid to this characteristic when developing fare change plans to manage demand or raise revenue.