Consequences of service reduction in municipal transit: San Francisco’s muni

Urban transit in the United States is going through a crisis of rising costs, increasing fares, falling patronage, and concomitant service reductions; typical of the pattern is San Francisco’s Municipal Railway, the agency in charge of all the City’s transit. From a basic fare of 15c in 1969, two increases brought the fare to 25c by 1972, and cut sharply into a previously stable patronage. The “Muni”, in an effort to reduce costs and meet its budgeted deficit, attempted to reduce service by ten to fifteen percent. From an analysis of the data which could be obtained, it appears that neither efficiency not equity in the City would have been served by the proposed cutbacks. The analysis draws from a variety of sources and methods in exploring the interactions within the transportation system and within the city budget.     

Does uncertainty make cost-benefit analyses pointless?

Cost-benefit analysis (CBA) is widely used in public decision making on infrastructure investments. However, the demand forecasts, cost estimates, benefit valuations and effect assessments that are conducted as part of CBAs are all subject to various degrees of uncertainty. The question is to what extent CBAs, given such uncertainties, are still useful as a way to prioritize between infrastructure investments, or put differently, how robust the policy conclusions of CBA are with respect to uncertainties. Using simulations based on real data on national infrastructure plans in Sweden and Norway, we study how investment selection and total realized benefits change when decisions are based on CBA assessments subject to several different types of uncertainty. Our results indicate that realized benefits and investment selection are surprisingly insensitive to all studied types of uncertainty, even for high levels of uncertainty. The two types of uncertainty that affect results the most are uncertainties about investment cost and transport demand. Provided that decisions are based on CBA outcomes, reducing uncertainty is still worthwhile, however, because of the huge sums at stake. Even moderate reductions of uncertainties about unit values, investment costs, future demand and project effects may increase the realized benefits infrastructure investment plans by tens or hundreds of million euros. We conclude that, despite the many types of uncertainties, CBA is able to fairly consistently separate the wheat from the chaff and hence contribute to substantially improved infrastructure decisions.     

Cost-saving properties of schedule coordination in a simple trunk-and-feeder transit system

The paper explores how the coordination of vehicle schedules in a public transit system affects generalized costs. We consider an idealized system that delivers its users to a common destination by requiring each to transfer from a feeder- to a trunk-line vehicle. Continuum models are used first to analyze cases in which the trunk-line vehicle schedule is given exogenously. We find that when feeder vehicles are dispatched in coordination with this exogenous trunk-line schedule, the reduction in user cost often outweighs the added cost to the feeder operation. In cases when the frequencies of trunk and feeder services can be established jointly, the models show that coordination can be Pareto improving, meaning that operator and user costs both diminish. Conditions that give rise to these cost savings are specified. Practical implications are discussed.     

User satisfaction with paratransit in competition with motorization in indonesia: anticipation of future implications

The rapid pace of motorization throughout the world has changed travel behavior, which in turn has influenced every aspect of transport operations. This impact has also increasingly challenged the future existence of such road-based urban public transport as paratransit due to its characteristics and problems, especially in developing countries. Since creating satisfied users can help retain paratransit’s existence, this research aims to explore user satisfaction with paratransit service in order to anticipate future implications for its competition with motorization in Bandung, Indonesia. It establishes important factors and attributes to explain user perceptions and priorities regarding the service. Its hypotheses explain how users measure paratransit’s quality of service, inferring that they are likely to continue to use it. Even though users are dissatisfied with several aspects of paratransit, and the impact of competition has been strong, loyal users can still be found. By considering the findings, existing problems of inappropriate-quality service can be addressed to satisfy users’ expectations. The study also suggests some anticipation of winning the competition with motorization.     

Do travel cost models value transportation properly?

This paper examines whether travel cost models value transportation properly. It uses contingent behavior and contingent pricing analyses to explore the valuation of transport costs within the context of recreation demand. The contingent behavior analysis poses hypothetical increases in travel costs––travel distance and access fees––and examines the demand responses. In contrast, the ‘contingent pricing’ analysis asks respondents to state the increase in travel costs that is consistent with certain reductions in recreation demand, in this case, reductions that eliminate demand. By comparing distance-related responses to fee-related responses, the two analyses estimate factors for testing and improving the valuation of transport costs. To achieve these ends, the two analyses also explore the valuation of time costs.     

Transit competitiveness in polycentric metropolitan regions

This paper analyzes the potential to, and impacts of, increasing transit modal split in a polycentric metropolitan area – the Philadelphia, Pennsylvania region. Potential transit riders are preselected as those travelers whose trips begin and end in areas with transit-supportive land uses, defined as “activity centers,” areas of high-density employment and trip attraction. A multimodal traffic assignment model is developed and solved to quantify the generalized cost of travel by transit services and private automobile under (user) equilibrium conditions. The model predicts transit modal split by identifying the origin–destination pairs for which transit offers lower generalized cost. For those origin–destination pairs for which transit does not offer the lowest generalized cost, I compute a transit competitiveness measure, the ratio of transit generalized cost to auto generalized cost. The model is first formulated and solved for existing transit service and regional pricing schemes. Next, various transit incentives (travel time or fare reductions, increased service) and auto disincentives (higher out of pocket expenses) are proposed and their impacts on individual travel choices and system performance are quantified. The results suggest that a coordinated policy of improved transit service and some auto disincentives is necessary to achieve greater modal split and improved system efficiency in the region. Further, the research finds that two levels of coordinated transit service, between and within activity centers, are necessary to realize the greatest improvements in system performance.     

A general corridor model for designing plug-in electric vehicle charging infrastructure to support intercity travel

This paper proposes to optimally configure plug-in electric vehicle (PEV) charging infrastructure for supporting long-distance intercity travel using a general corridor model that aims to minimize a total system cost inclusive of infrastructure investment, battery cost and user cost. Compared to the previous work, the proposed model not only allows realistic patterns of origin–destination demands, but also considers flow-dependent charging delay induced by congestion at charging stations. With these extensions, the model is better suited to performing a sketchy design of charging infrastructure along highway corridors. The proposed model is formulated as a mixed integer program with nonlinear constraints and solved by a specialized metaheuristic algorithm based on Simulated Annealing. Our numerical experiments show that the metaheuristic produces satisfactory solutions in comparison with benchmark solutions obtained by a mainstream commercial solver, but is more computationally tractable for larger problems. Noteworthy findings from numerical results are: (1) ignoring queuing delay inducted by charging congestion could lead to suboptimal configuration of charging infrastructure, and its effect is expected to be more significant when the market share of PEVs rises; (2) in the absence of the battery cost, it is important to consider the trade-off between the costs of charging delay and the infrastructure; and (3) building long-range PEVs with the current generation of battery technology may not be cost effective from the societal point of view.     

Pricing local emission exposure of road traffic: An agent-based approach

This paper proposes a new approach to iteratively calculate local air pollution exposure tolls in large-scale urban settings by taking the exposure times and locations of individuals into consideration. It explicitly avoids detailed air pollution concentration calculations and is therefore characterized by little data requirements, reasonable computation times for iterative calculations, and open-source compatibility. In a first step, the paper shows how to derive time-dependent vehicle-specific exposure tolls in an agent-based model. It closes the circle from the polluting entity, to the receiving entity, to damage costs, to tolls, and back to the behavioral change of the polluting entity. In a second step, the approach is applied to a large-scale real-world scenario of the Munich metropolitan area in Germany. Changes in emission levels, exposure costs, and user benefits are calculated. These figures are compared to a flat emission toll, and to a regulatory measure (a speed reduction in the inner city), respectively. The results indicate that the flat emission toll reduces overall emissions more significantly than the exposure toll, but its exposure cost reductions are rather small. For the exposure toll, overall emissions increase for freight traffic which implies a potential conflict between pricing schemes to optimize local emission exposure and others to abate climate change. Regarding the mitigation of exposure costs caused by urban travelers, the regulatory measure is found to be an effective strategy, but it implies losses in user benefits.     

Substance precedes methodology: on cost–benefit analysis and equity

While distributive aspects have been a topic of discussion in relation to cost–benefit analysis (CBA), little systematic thought has been given in the CBA literature to the focus of such an equity analysis in evaluating transport projects. The goal of the paper is to provide an overview of the various directions an equity analysis, carried out within the context of a social cost–benefit analysis, could take. The paper starts from the widely-shared definition of distributive justice: the morally proper distribution of goods and bads over members of society. Following this definition, carrying out an equity analysis requires that decisions are made about: (1) the benefits and costs that are distributed through a transport project; (2) the members of society between whom benefits and costs are distributed; and (3) the distributive principle that determines whether a particular distribution is fair. Much of the discussions about cost–benefit analysis and equity do not address these questions in any systematic way. The paper aims to provide a framework. Three sets of benefits and costs are identified as a possible focus of an equity analysis: (1) net benefits; (2) mobility-enhancing benefits; and (3) individual benefits and costs. For each set, a discussion follows regarding the way in which members of societies could be divided into meaningful groups, as well as the possible yardstick for judging whether a certain distribution is fair. While the paper acknowledges that the choice between the three sets is ultimately a political decision, it ends with a set of arguments that suggest that the equity analysis of transport projects should focus first and foremost on the mobility-enhancing benefits generated by such projects.     

Rail Infrastructure: Challenges for Cost–Benefit Analysis and Other ex ante Evaluations

Abstract

Cost–benefit analysis (CBA) plays a major role in the ex ante evaluation of rail projects in many western countries. At first sight carrying out a CBA for rail projects seems straightforward, since cost estimates are almost always available, and the most dominant benefits are generally known, being the travel time saved and the increase in consumer surplus due to induced demand. However, the practice is much more complex: the quality of current estimates for costs and benefits is often poor and several benefits-related aspects are ignored. This article gives an overview of the challenges in improving the quality of CBAs for rail projects.     

Comparative analysis of three user equilibrium models under stochastic demand

Recent empirical studies on the value of time and reliability reveal that travel time variability plays an important role on travelers' route choice decision process. It can be considered as a risk to travelers making a trip. Therefore, travelers are not only interested in saving their travel time but also in reducing their risk. Typically, risk can be represented by two different aspects: acceptable risk and unacceptable risk. Acceptable risk refers to the reliability aspect of acceptable travel time, which is defined as the average travel time plus the acceptable additional time (or buffer time) needed to ensure more frequent on‐time arrivals, while unacceptable risk refers to the unreliability aspect of unacceptable late arrivals (though infrequent) that have a travel time excessively higher than the acceptable travel time. Most research in the network equilibrium based approach to modeling travel time variability ignores the unreliability aspect of unacceptable late arrivals. This paper examines the effects of both reliability and unreliability aspects in a network equilibrium framework. Specifically, the traditional user equilibrium model, the demand driven travel time reliability‐based user equilibrium model, and the α‐reliable mean‐excess travel time user equilibrium model are considered in the investigation under an uncertain environment due to stochastic travel demand. Numerical results are presented to examine how these models handle risk under travel time variability.     

Assessment of profit,cost and emissions by varying speed as a function of sea conditions and freight market

This paper assesses shipping profits, costs and emissions by speed and as a function of sea and freight market conditions. Traditionally, seagoing vessels have been designed to operate at standardized, maximum economic speeds based on hydrodynamic considerations. High fuel costs and increased environmental concerns have challenged this practice. While speed reductions may reduce costs and emissions, most studies are based on still water conditions despite these being the exceptions. In addition, shipping lines operate in a commercial market with the objective of making profit and not solely on cost reductions. Our results show that significant cost and emissions reductions can be achieved and that the maximum economic speeds based on hydrodynamic considerations even in a good freight market are lower than the design speeds.     

Optimal design and benefits of a short turning strategy for a bus corridor

We develop a short turning model using demand information from station to station within a single bus line-single period setting, aimed at increasing the service frequency on the more loaded sections to deal with spatial concentration of demand considering both operators’ and users’ costs. We find analytical expressions for optimal values of the design variables, namely frequencies (inside and outside the short cycle), capacity of vehicles and the position of the short turn limit stations. These expressions are used to analyze the influence of different parameters in the final solution. The design variables and the corresponding cost components for operators and users (waiting and in-vehicle times) are compared against an optimized normal operation scheme (single frequency). Applications on actual transit corridors exhibiting different demand profiles are conducted, calculating the optimal values for the design variables and the resulting benefits for each case. Results show the typical demand configurations that are better served using a short turn strategy.     

Travel time variability and airport accessibility

We analyze the cost of access travel time variability for air travelers. Reliable access to airports is important since the cost of missing a flight is likely to be high. First, the determinants of the preferred arrival times at airports are analyzed. Second, the willingness to pay (WTP) for reductions in access travel time, early and late arrival time at the airport, and the probability to miss a flight are estimated, using a stated choice experiment. The results indicate that the WTPs are relatively high. Third, a model is developed to calculate the cost of variable travel times for representative air travelers going by car, taking into account travel time cost, scheduling cost and the cost of missing a flight using empirical travel time data. In this model, the value of reliability for air travelers is derived taking “anticipating departure time choice” into account, meaning that travelers determine their departure time from home optimally. Results of the numerical exercise show that the cost of access travel time variability for business travelers are between 0% and 30% of total access travel cost, and for non-business travelers between 0% and 25%. These numbers depend strongly on the time of the day.     

A discrete dynamical system of formulating traffic assignment: Revisiting Smith’s model

Through relaxing the behavior assumption adopted in Smith’s model (Smith, 1984), we propose a discrete dynamical system to formulate the day-to-day evolution process of traffic flows from a non-equilibrium state to an equilibrium state. Depending on certain preconditions, the equilibrium state can be equivalent to a Wardrop user equilibrium (UE), Logit-based stochastic user equilibrium (SUE), or boundedly rational user equilibrium (BRUE). These equivalence properties indicate that, to make day-to-day flows evolve to equilibrium flows, it is not necessary for travelers to choose their routes based on actual travel costs of the previous day. Day-to-day flows can still evolve to equilibrium flows provided that travelers choose their routes based on estimated travel costs which satisfy these preconditions. We also show that, under a more general assumption than the monotonicity of route cost function, the trajectory of the dynamical system converges to a set of equilibrium flows by reasonably setting these parameters in the dynamical system. Finally, numerical examples are presented to demonstrate the application and properties of the dynamical system. The study is helpful for understanding various processes of forming traffic jam and designing an algorithm for calculating equilibrium flows.     

Modeling the cost sensitivity of intermodal inland waterway terminals: A scenario based approach

Cost characteristics of differently sized inland waterway terminals (IWTs) have not received much scientific attention. This observation is remarkable given the importance of costs in transportation decision-making. Classification of differently sized IWTs and their cost structure will lead to more insight into the container cost per terminal. Therefore, the goal of our research was to determine both the characteristics of the cost structure associated with different inland waterway (IWW) container terminal types and the sensitivity of the system to cost/TEU changes in input and operational conditions. We show that terminals with a higher container throughput encounter fewer costs, and can therefore charge a lower price. Assumed delays of 2 h per day on the waterside cause a 4.7–6.6% cost increase per container, mainly caused by extra labor costs. It is also assumed that the changing climate will influence terminal operations and results in extreme water levels (lasting two weeks occurring four times a year) causing a cost increase of 1.0–3.4%. Subsidies can cause cost reductions of 0.3–10.4% depending on the exact form, with the smaller terminals benefiting more because their investment costs are higher relative to operational costs. A subsidy can lower costs by up to 10.4%, but it is questionable whether small and medium terminals will have a lower cost price than the market price, showing that it is important for small and medium terminals to quickly grow in size.     

Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

Activity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true assessment of the impact of different Travel Demand Management measures. However, qualitative approaches in data collection are believed to be able to capture aspects of individuals’ travel behavior that cannot be obtained using quantitative studies, such as detailed decision making process information. Therefore, qualitative methods may deepen the insight into human’s travel behavior from an agent-based perspective. This paper reports on the application of a qualitative semi-structured interview method, namely the Causal Network Elicitation Technique (CNET), for eliciting individuals’ thoughts regarding fun-shopping related travel decisions, i.e. timing, shopping location and transport mode choices. The CNET protocol encourages participants to think aloud about their considerations when making decisions. These different elicited aspects are linked with causal relationships and thus, individuals’ mental representations of the task at hand are recorded. This protocol is tested in the city centre of Hasselt in Belgium, using 26 young adults as respondents. Response data are used to apply the Association Rules, a fairly common technique in machine learning. Results highlight different interrelated contexts, instruments and values considered when planning a trip. These findings can give feedback to current AB models to raise their behavioral realism and to improve modeling accuracy.     

Automation of paratransit reservation,routing, and scheduling

Santa Clara County, California experienced a sharp growth in demand‐responsive paratransit ridership for individuals with disabilities, as a result of the passage of the 1990 Americans With Disabilities Act (ADA). This paper describes an automated paratransit system for the ADA‐type paratransit operation implemented in Santa Clara County. It automated paratransit reservation, scheduling, and routing functions. The key components of this system were a digital geographic database (DGD) and an automated trip scheduling system (ATSS). Empirical evidence after one year of operation indicates numerous benefits of this automation. There were significant reductions in the paratransit operating costs and an increase in the percent shared rides. The savings in operating costs far exceeded the annualized capital cost of automation. A user survey indicates that these improvements were achieved without degradation to service quality such as vehicle on‐time performance, invehicle travel times, vehicle response to open return, and ride comfort.     

Economic costs and environmental impacts of alternative fuel vehicle fleets in local government: An interim assessment of a voluntary ten-year fleet conversion plan

Vehicle fleets are widely viewed by policy makers as attractive first markets for introduction of alternative fuel technologies. Although, it is essential to understand the environmental benefits and economic challenges involved in fleet conversion, the literature provides little understanding of the implementation issues associated with alternative fuel vehicles. This paper examines the cost effectiveness and environmental impact of the conversion of a 180 plus vehicle fleet to alternative fuel vehicle technologies by a public organization at the mid-point of the project implementation. Using multi-year micro data on fuel usage, operational and capital expenditures, mileage and emissions, the paper examines conversion costs and infrastructure investments required, extent of user adoption, and emissions reductions achieved. Results are discussed in terms of their implications for managerial practice in local government fleet agencies and for future research.