A dynamic station strategy to improve the performance of flex-route transit services

As an innovative combination of conventional fixed-route transit and demand responsive service, flex-route transit is currently the most popular type of flexible transit services. This paper proposes a dynamic station strategy to improve the performance of flex-route transit in operating environments with uncertain travel demand. In this strategy, accepted curb-to-curb stops are labeled as temporary stations, which can be utilized by rejected requests for their pick-up and drop-off. The user cost function is defined as the performance measure of transit systems. Analytical models and simulations are constructed to test the feasibility of implementing the dynamic station strategy in flex-route transit services. The study over a real-life flex-route service indicates that the proposed dynamic station strategy could reduce the user cost by up to 30% without any additional operating cost, when an unexpectedly high travel demand surpasses the designed service capacity of deviation services.     

A slack arrival strategy to promote flex-route transit services

Flex-route transit, which combines the advantages of fixed-route transit and demand-responsive transit, is one of the most promising options in low-demand areas. This paper proposes a slack arrival strategy to reduce the number of rejected passengers and idle time at checkpoints resulting from uncertain travel demand. This strategy relaxes the departure time constraints of the checkpoints that do not function as transfer stations. A system cost function that includes the vehicle operation cost and customer cost is defined to measure system performance. Theoretical and simulation models are constructed to test the benefits of implementing the slack arrival strategy in flex-route transit under expected and unexpected demand levels. Experiments over a real-life flex-route transit service show that the proposed slack arrival strategy could improve the system performance by up to 40% with no additional operating cost. The results demonstrate that the proposed strategy can help transit operators provide more cost-efficient flex-route transit services in suburban and rural areas.     

A methodology to derive the critical demand density for designing and operating feeder transit services

Feeder lines are one of the most often used types of flexible transit services connecting a service area to a major transit network through a transfer point. They often switch operations between a demand responsive and a fixed-route policy. In designing and running such systems, the identification of the condition justifying the operating switch is often hard to properly evaluate. In this paper, we propose an analytical model and solution of the problem to assist decision makers and operators in their choice. By employing continuous approximations, we derive handy but powerful closed-form expressions to estimate the critical demand densities, representing the switching point between the competing operating policies. Based on the results of one-vehicle and two-vehicle operations for various scenarios, in comparison to values generated from simulation, we verify the validity of our analytical modeling approach.     

Emissions of demand responsive services as an alternative to conventional transit systems

The environmental performance of public transport plays a key role in improving air quality in urban areas. An important way of improving existing transit services is to use innovative propulsive systems; however, this needs considerable financial resources that are not always available. Here we assess how the organizational form of the transit system may impact the environment relying on a new methodology that permits comparisons in terms of distance traveled between a traditional fixed-route and a demand responsive transit service. We apply an emission model to find the least polluting transit system under a broad range of scenarios with different road networks, service quality levels and demand densities. Results indicate that demand responsive transit services minimize emissions for high quality service level and low demand density scenarios. Furthermore, the possibility of employing smaller vans with lower emission factors guarantees additional substantial benefits in terms of atmospheric pollution for demand responsive transit services, thereby giving them a competitive advantage in virtually every case.     

A methodology for choosing between fixed‐route and flex‐route policies for transit services

Flex‐route transit brings together the low cost operability of fixed‐route transit with the flexibility of demand responsive transit, and in recent years, it has become the most popular type of flexible transit service. In this paper, a methodology is proposed to help planners make better decisions regarding the choice between a conventional fixed‐route and a flex‐route policy for a specific transit system with a varying passenger demand. A service quality function is developed to measure the performance of transit systems, and analytical modeling and simulations are used to reproduce transit operation under the two policies. To be closer to reality, two criteria are proposed depending on the processing of rejected requests in the assessment of the service quality function for flex‐route services. In various scenarios, critical demand densities, which represent the switching points between the two competing policies, are derived in a real‐world transit service according to the two criteria. Copyright © 2014 John Wiley & Sons, Ltd.     

Feeder transit services: Choosing between fixed and demand responsive policy

The Demand Responsive Connector (DRC) connects a residential area to a major transit network through a transfer point and is one of the most often adopted types of flexible transit services. In this paper, analytical and simulation models are developed to assist planners in the decision making process when having to choose between a demand responsive and a fixed-route operating policy and whether and when to switch from one to the other during the day. The best policy is chosen to maximize the service quality, defined as a weighed sum of customer walking time, waiting time and ride time. Based on the results of one-vehicle operations for various scenarios, we have generated critical customer demands, which represent switching points between the competing service policies. Our findings show that the critical demands are in the range from 10 to 50 customers/mile²/h and that a demand responsive policy is more preferred during afternoon peak hours.     

A structured flexible transit system for low demand areas

Public transit structure is traditionally designed to contain fixed bus routes and predetermined bus stations. This paper presents an alternative flexible-route transit system, in which each bus is allowed to travel across a predetermined area to serve passengers, while these bus service areas collectively form a hybrid “grand” structure that resembles hub-and-spoke and grid networks. We analyze the agency and user cost components of this proposed system in idealized square cities and seek the optimum network layout, service area of each bus, and bus headway, to minimize the total system cost. We compare the performance of the proposed transit system with those of comparable systems (e.g., fixed-route transit network and taxi service), and show how each system is advantageous under certain passenger demand levels. It is found out that under low-to-moderate demand levels, the proposed flexible-route system tends to have the lowest system cost.     

Switching service types for multi-region bus systems

Conventional fixed-route bus services are generally preferred to flexible-route services at high demand densities, and vice versa. This paper formulates the problem of integrating conventional and flexible services that connect a main terminal to multiple local regions over multiple time periods. The system’s vehicle size, route spacing (for conventional services), service area (for flexible services), headways and fleet sizes are jointly optimized to minimize the sum of supplier costs and user costs. The route spacing for conventional bus services and service area for flexible bus services are also optimized for each region. The proposed solution method, which uses a genetic algorithm and analytic optimization, finds good solutions quickly. Numerical examples and sensitivity analyses confirm that the single fleet variable-type bus service may outperform either the single fleet conventional bus service or the single fleet flexible bus service when demand densities vary substantially among regions and time periods.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

Effects of contracting on cost efficiency in US fixed-route bus transit service

Contracted service comprises a significant proportion of total operating expenses in the provision of fixed-route bus transit service in the US. Despite its importance, the literature on the economic effects of transit service contracting has been limited to only a few studies since the mid-1990s, and is inconclusive due to problems with the nature and methodology of the past studies.This paper examines how the cost efficiency of providing fixed-route bus transit service varies by the degree of contracting. I make several improvements to previous studies and conduct a regression analysis that: (1) addresses the endogeneity problem between the contracting decision and cost efficiency, (2) differentiates between agencies that contract out only a portion of service from those that contract out all service, (3) takes into account the moderating effects of several factors on the effect of contracting on cost efficiency, and (4) uses a relatively larger set of cross-sectional time-series data constructed from the National Transit Database from 1992 to 2000.The analysis results show that the combined effects of contracting lower operating costs by $4.09 and $2.89 per vehicle hour for partial and full-contracting agencies, respectively, in the average case. These average cost savings translate into 7.8% and 5.5%, using the average operating cost per vehicle hour of $53.06. However, this improvement is not universal, because the effects of contracting on cost efficiency vary by factors such as peak-to-base ratio, agency size, the wage gap between bus operators in the public and private sectors, and agency type.     

Two-phase stochastic program for transit network design under demand uncertainty

This paper develops a reliability-based formulation for rapid transit network design under demand uncertainty. We use the notion of service reliability to confine the stochastic demand into a bounded uncertainty set that the rapid transit network is designed to cover. To evaluate the outcome of the service reliability chosen, flexible services are introduced to carry the demand overflow that exceeds the capacity of the rapid transit network such designed. A two-phase stochastic program is formulated, in which the transit line alignments and frequencies are determined in phase 1 for a specified level of service reliability; whereas in phase 2, flexible services are determined depending on the demand realization to capture the cost of demand overflow. Then the service reliability is optimized to minimize the combined rapid transit network cost obtained in phase 1, and the flexible services cost and passenger cost obtained in phase 2. The transit line alignments and passenger flows are studied under the principles of system optimal (SO) and user equilibrium (UE). We then develop a two-phase solution algorithm that combines the gradient method and neighborhood search and apply it to a series of networks. The results demonstrate the advantages of utilizing the two-phase formulation to determine the service reliability as compared with the traditional robust formulation that pre-specifies a robustness level.     

Robust transit network design with stochastic demand considering development density

This paper analyzes the influence of urban development density on transit network design with stochastic demand by considering two types of services, rapid transit services, such as rail, and flexible services, such as dial-a-ride shuttles. Rapid transit services operate on fixed routes and dedicated lanes, and with fixed schedules, whereas dial-a-ride services can make use of the existing road network, hence are much more economical to implement. It is obvious that the urban development densities to financially sustain these two service types are different. This study integrates these two service networks into one multi-modal network and then determines the optimal combination of these two service types under user equilibrium (UE) flows for a given urban density. Then we investigate the minimum or critical urban density required to financially sustain the rapid transit line(s). The approach of robust optimization is used to address the stochastic demands as captured in a polyhedral uncertainty set, which is then reformulated by its dual problem and incorporated accordingly. The UE principle is represented by a set of variational inequality (VI) constraints. Eventually, the whole problem is linearized and formulated as a mixed-integer linear program. A cutting constraint algorithm is adopted to address the computational difficulty arising from the VI constraints. The paper studies the implications of three different population distribution patterns, two CBD locations, and produces the resultant sequences of adding more rapid transit services as the population density increases.     

The theory of second best in urban mass transit: Management in the public sector as a proforma exercise

This paper focuses on four issues. The first is the case of one-sided investments in mass transit in metropolitan areas of developing countries. It is pointed out that in many cases in which the conditions for optimum investment policies (Pareto's Optimum) are not maintained, excessive investments on mass transit, including large annual operating subsidies, usually lead to substantial sub-optimizations and waste of scarce financial resources. This problem is then reviewed under the light of the “Theory of Second Best” as articulated for all investment options within Welfare Economic Theory. The second issue examined is the matter of recently discovered important diseconomies of scale of large metro transit systems in developing and developed countries, and the need to retain production of transport services within small-scale production units that are well coordinated and controlled. The third issue discussed is the problem of mismanagement of most public sector transit companies and agencies. The notion that most such systems are simply administered, not managed, is being brought up and the requirements for proper management are amplified. Finally, the case of public vs. private ownership of mass transit is being discussed with a distinction between public policies of providing mass transit services and the actual production process of these services. Provision of services represents a public responsibility that belongs to the public sector. However, production of service is a techno-economic process that requires different talents and circumstances. The paper concludes with a strong suggestion for major reorientation of urban mass transit in the metro areas of developing countries towards more efficiency and higher productivity.     

An analysis of public bus transit performance in Indian cities

Maintaining and enhancing public transit service in Indian cities is important, to meet rapidly growing mass mobility needs, and curb personal motor vehicle activity and its impacts at low cost. Indian cities rely predominantly on buses for public transport, and are likely to continue to do so for years. However, the public bus transit service is inadequate, and unaffordable for the urban poor. The paper explores the factors that contribute to and affect efforts to improve this situation, based on an analysis of the financial and operational performance of the public bus transit service in the four metropolitan centres and four secondary cities during the 1990s. Overall, there were persistent losses, owing to increasing input costs and declining productivity. The losses occurred despite rapidly increasing fares, and ridership declined. The situation, and the ability to address it, is worse in the secondary cities than the metropolitan centres. We suggest a disaggregated approach based on the needs and motivations of different groups in relation to public transit, along with improved operating conditions and policies to internalize costs of personal motor vehicle use, to address the challenge of providing financially viable and affordable public bus transit service.     

The analysis of travel and emission impacts of travel demand management strategies using activity-based models

This paper demonstrates, tests and shows the value of activity-based travel demand models and household sample enumeration forecasting techniques in evaluating the transportation and air quality impacts of travel demand management strategies. Using data from the Portland, Oregon metropolitan area, three transportation policies were evaluated both individually and in combination: transit improvements, pricing, and telecommunications. The activity-based models used in this testing represents a significant improvement to today's "four-step" sequential model systems by providing a deeper insight into the individual decision making process in response to transportation policies. A wider range of impacts is predicted, and indirect effects as well as synergistic effects of such policies are taken into consideration. These models are capable of providing the information needed to improve the linkage of transportation models with emissions and air quality analysis methodologies by improving the prediction of variables that are important to accurately estimating emissions and air quality impacts of transportation actions.     

Maximizing net benefits for conventional and flexible bus services

Transit ridership is usually sensitive to fares, travel times, waiting times, and access times, among other factors. Therefore, the elasticities of demand with respect to such factors should be considered in modeling bus transit services and must be considered when maximizing net benefits (i.e. “system welfare” = consumer surplus + producer surplus) rather just minimizing costs. In this paper welfare is maximized with elastic demand relations for both conventional (fixed route) and flexible-route services in systems with multiple dissimilar regions and periods. As maximum welfare formulations are usually too complex for exact solutions, they have only been used in a few studies focused on conventional transit services. This limitation is overcome here for both conventional and flexible transit services by using a Real Coded Genetic Algorithm to solve such mixed integer nonlinear welfare maximization problems with constraints on capacities and subsidies. The optimized variables include service type, zone sizes, headways and fares. We also determine the maximum welfare threshold between optimized conventional and flexible services) and explore the effects of subsidies. The proposed planning models should be useful in selecting the service type and optimizing other service characteristics based on local geographic characteristics and financial constraints.     

Public transport provision in sparsely populated arid areas

Arid areas are characterized by dispersed patterns of population and economic activities in a hot and dry environment. Although basic human needs are identical everywhere, patterns of travel behaviour in arid lands are different from the patterns in more humid areas. The different behavioural patterns imply somewhat different demand patterns for transport services in general and transit services in particular. Good access to the scattered small communities and more so to the remote urban centres is of prime concern in the sparsely populated arid areas. And the demand patterns themselves raise the need to develop unusual types of service based on local conditions. This article presents the effects of the arid spatial and climatic conditions on transit demand and supply. After examining the service standards required in the sparselands and using the Israeli Negev region as an example, guidelines for developing regional transit systems in these arid areas are put forward.     

Planning hierarchical urban transit systems for reductions in greenhouse gas emissions

Public transit systems with high occupancy can reduce greenhouse gas (GHG) emissions relative to low-occupancy transportation modes, but current transit systems have not been designed to reduce environmental impacts. This motivates the study of the benefits of design and operational approaches for reducing the environmental impacts of transit systems. For example, transit agencies may replace level-of-service (LOS) by vehicle miles traveled (VMT) as a criterion in evaluating design and operational changes. In previous work, we explored the unintended consequences of lowering transit LOS on emissions in a single-technology transit system. Herein, we extend the analysis to account for a more realistic case: a transit system with a hierarchical structure (trunk and feeder lines) providing service to a city where demand is elastic. By considering the interactions between the trunk and the feeder systems, we provide a quantitative basis for designing and operating integrated urban transit systems that can reduce GHG emissions and societal costs. We find that highly elastic transit demand may cancel emission reduction potentials resulting from lowering LOS, due to demand shifts to lower occupancy vehicles. However, for mass transit modes, these potentials are still significant. Transit networks with buses, bus rapid transit or light rail as trunk modes should be designed and operated near the cost-optimal point when the demand is highly elastic, while this is not required for metro. We find that the potential for unintended consequences increases with the size of the city. Our results are robust to uncertainties in the costs and emissions parameters.     

Evaluating Flexible Transport Solutions

Abstract

Flexible transport services (FTS) have been of increasing interest in developing countries as a bridge between the use of personal car travel and fixed route transit services. This paper reports on findings from a recent study in Queensland Australia, which identified lessons from an international review and implications for Australia. Potential strategic directions, including a vision, mission, key result areas, strategies, and identified means of measuring performance are described. Evaluation criteria for assessing flexible transport proposals were developed, and approaches to identifying and assessing needs and demands outlined. The use of emerging technologies is also a key element of successful flexible transport services.     

Flexible feeder transit route design to enhance service accessibility in urban area

To improve the accessibility of transit system in urban areas, this paper presents a flexible feeder transit routing model that can serve irregular‐shaped networks. By integrating the cost efficiency of fixed‐route transit system and the flexibility of demand responsive transit system, the proposed model is capable of letting operating feeder busses temporarily deviate from their current route so as to serve the reported demand locations. With an objective of minimizing total bus travel time, a new operational mode is then proposed to allow busses to serve passengers on both street sides. In addition, when multiple feeder busses are operating in the target service area, the proposed model can provide an optimal plan to locate the nearest one to response to the demands. A three‐stage solution algorithm is also developed to yield meta‐optimal solutions to the problem in a reasonable amount of time by transforming the problem into a traveling salesman problem. Numerical studies have demonstrated the effectiveness of the proposed model as well as the heuristic solution approach. Copyright © 2015 John Wiley & Sons, Ltd.