Limited-stop Service Research Articles

A Model of a Limited-Stop and Local Mixed Bus Service with Increased Fares for the Limited-Stop Service

This study designs a limited-stop and local mixed bus service from the perspectives of both transit agencies and passengers based on a proposed optimization model. Close attention was paid to the increase in fares for the limited-stop service in the proposed model to offset the loss in bus fare. The objective function was to minimize the passenger travel time and bus agency costs; the decision variables were the stops for the limited-stop service and the headways of the limited-stop and local services; the constraints included the range of fare increases for the limited-stop service and other factors. The Lingo software and the genetic algorithm were compared in solving the proposed model from the aspects of solving time and results. Because the solutions for the model within the planning time and the influence of the global optimal solution upon parametric analysis were stable, the Lingo software was more suitable for the proposed model. Evaluations of the total costs for the mixed service and local-only service were carried out for different bus corridor lengths. The ratio of the fares for the limited-stop service to the fares for the local service must be within the appropriate range in order to take advantage of the limited-stop service. When the stop spacing and the bus corridor distance were longer, the mixed service was more competitive and noticeable.

Modeling Limited-Stop Bus Corridor Services with Fare Payment Mode Choice and Trip Purpose Consideration.

This paper proposes a novel model for optimizing limited-stop bus corridor services with consideration of varied payment modes and different trip purposes. In the proposed model, the bus dwell time at a stop is dependent on the fare payment modes and the number of passengers getting off and waiting at the stop while those with the similar trip purpose are grouped into one user class. Given an origin-destination (OD) passenger trip matrix and a set of candidate bus lines serving a corridor, the proposed model is to minimize the total social cost that consists of the cost to the bus operator and the cost to the passengers. In the formulation of the optimization problem, a weighting parameter is adopted to balance the operator cost and the passenger cost. Numerical examples are presented to illustrate the importance of considering passenger flow impacts on bus (and passenger) travel times in the proposed model. We also investigate effects on the optimal limited-stop services (e.g., short-turn, skip-stop, and express) taking into account the choice of fare payment modes (e.g., on-board fare collection including payment by cash, magnetic strip or smart card, off-board fare collection) and different values of travel time due to passenger trip purposes. It is shown that the off-board payment mode would be more efficient in a high-demand corridor, that more passengers prefer to express and skip-stop services rather than normal regular services in the four collection systems, and that different limited-stop service plans should be used for different periods of the day in response to temporal variation in OD passenger travel patterns. The intellectual merit of this paper is not the seemingly obvious conclusions but that the proposed model can handle the problem of limited-stop bus corridor service design with the consideration of fare payment mode choice and trip purposes.

Bus Rapid Transit Plans in New York’s Capital District

The Capital District Transportation Authority (CDTA) is seeking to implement Bus Rapid Transit service in the NY 5 corridor, which runs for 16.5 miles between Albany and Schenectady. The benefits of BRT will be to improve service for current riders, draw new riders to the system, help spur economic revitalization in the corridor, provide key nodes for new development, and improve the image of transit in the Capital District as a whole. When fully in place, the key features of BRT on NY 5 will include limited-stop service, substantial passenger facilities and amenities at each station, real-time passenger information, improved pedestrian environment, park-and-ride opportunities, priority treatment at intersections, queue jumpers at key points, off-vehicle fare collection, and a specific brand image to distinguish BRT from other bus services. The cumulative impact of these types of improvements—in travel time, passenger comfort, passenger information, and image—will lead to an increase in transit ridership in the NY 5 corridor. Based on experience at other North American transit agencies that have implemented BRT, an increase of 22 percent to 29 percent is expected, depending on the ultimate travel time savings that is achieved.

Mixed Scheduling Model for Limited-Stop and Normal Bus Service with Fleet Size Constraint

Limited-stop service is useful to increase operation efficiency where the demand is unbalanced at different stops and unidirectional. A mixed scheduling model for limited-stop buses and normal buses is proposed considering the fleet size constraint. This model can optimize the total cost in terms of waiting time, in-vehicle time and operation cost by simultaneously adjusting the frequencies of limited-stop buses and normal buses. The feasibility and validity of the proposed model is shown by applying it to one bus route in the city of Zhenjiang, China. The results indicate that the mixed scheduling service can reduce the total cost and travel time compared with the single scheduling service in the case of unbalanced passenger flow distribution and fleet constraints. With a larger fleet, the mixed scheduling service is superior. There is an optimal fleet allocation that minimizes the cost for the system, and a significant saving could be attained by the mixed scheduling service. This study contributed to the depth analysis of the relationship among the influencing factors of mixed scheduling, such as fleet size constraint, departure interval and cost.

The impact of using a naïve approach in the limited-stop bus service design problem

The proven benefits of limited-stop services have captured the attention of researchers, especially during the last decade. However, to solve the limited-stop service design problem many existing works directly impose a capacity constraint to a total social cost objective function. This “naïve approach” implicitly assumes that passengers behave altruistically, basing their decisions on what is best for the whole system. Although this issue has been identified in earlier works, the magnitude of the error induced by this simplification has not been studied yet. The objective of this work is to measure this error and to understand how it misrepresents passenger flows and bus occupation rates. To measure this error gap, we optimize a set of test scenarios by applying a naïve approach, and then take the resulting design and obtain a benchmark passenger assignment using a simple behavioral model. We propose two main indicators to compare both passenger assignment: the total passenger deviation, and the total capacity deficit. This comparison reveals that the assignment of the naïve approach may indeed be unrealistic, and raises concerns that a network design based on the naïve approach might have severe problems when implemented. Thus, the work highlights the importance of taking the results of the naïve approach with caution and verify them with a passenger assignment model before their implementation.

Cooperatively coevolutionary optimization design of limited-stop services and operating frequencies for transit networks

The objective of the limited-stop service design and frequency setting problem (LSDFSP) is to realize the operation of a transit route with a set of elaborate service patterns and corresponding frequencies that can minimize the total social cost of the users and operators. In practice, these different patterns and frequencies involve a trade-off between the user and operator requirements, and this aspect cannot be fully clarified by a single-objective optimization problem. Therefore, in this study, the LSDFSP is considered at the network level and formulated as a multi-objective optimization problem with competing objectives of minimizing the user and operator costs. The cooperative coevolutionary multi-objective evolutionary algorithm is redesigned to collaboratively optimize the service patterns and frequencies. A prioritization method is proposed to separately incorporate different types of unsatisfied demand as critical indicators, prompting the algorithm to dig deeper into valuable genes and evolve more feasible solutions. The proposed algorithm is tested on a small network and a real intricate network. It is noted that higher frequencies increased the fleet size and decreased the users’ waiting time and in-vehicle time. Furthermore, skipping more stations reduced the fleet size and users’ in-vehicle time, while increasing the users’ waiting time and number of transfers. The computational results indicated that the proposed algorithm can suitably incorporate the trade-offs and generate an accurate set of Pareto-optimal solutions.

Selecting the most relevant variables towards clustering bus priority corridors

This paper proposes a novel framework to identify the most informative variables for clustering bus priority corridors according to their similarities regarding system and operational aspects. Although each bus corridor has its peculiarities, understanding the similarities (e.g., system, physical and operational aspects) between corridors of different regions of the world can help researchers and transit specialists to draw up strategies tailored to improving the traffic in the cities. For that matter, we integrate a novel metric for measuring clustering quality to the omit-one-variable-out-at-a-time selection procedure. The proposed method relies on three steps: (i) collect and preprocess data describing bus corridors; (ii) define the number of clusters to be generated based on a hierarchical approach; and (iii) iteratively group bus corridors, and eliminate less relevant clustering variables. When applied to a dataset comprised of 296 bus priority corridors from 45 countries and described by 44 variables, the proposed framework retained only four variables (i.e., brand and/or logo, station spacing, enhanced stations, and operating speed) responsible for the best stratification of corridors. Four clusters were formed and qualitatively assessed regarding their similarities in terms of system, physical and operational aspects. Corridors were grouped into basic corridors (cluster 1), improved corridors (cluster 2), Bus Rapid Transit (BRT) and Bus with High Level of Service (BHLS) systems (cluster 3), and express, limited-stop services (cluster 4).

Assessing operation and customer perception characteristics of high frequency local and limited-stop bus service in Vancouver, Canada

Public transport agencies implement different strategies aimed at improving the operation of transit service and to increase satisfaction among its riders. One service strategy employed by transit agencies is a limited-stop bus service that runs in parallel to a heavily used route to decrease travel times for existing riders and to reduce pressure on the local route. Using bus operations data obtained from automatic vehicle location (AVL) and automatic passenger counter (APC) systems and customer satisfaction data collected in Vancouver, Canada, the present study evaluates levels of satisfaction among users of a local and limited-stop bus service while controlling for the service characteristics these users have experienced in the past seven days. Our results reveal that after controlling for characteristics related to the conditions of the service experienced by users, namely passenger activity levels, patrons of the express route service were more likely to be satisfied with the transit service compared to users of the local service. This finding indicates that the operational characteristics of a limited-stop service, including in-vehicle time savings and higher route frequency, are highly valued by its users. Results of this study demonstrate how operations data can provide a greater context for customer satisfaction analyses. Finally, this study provides transit planners and policy makers with a better understanding of how customers perceive local and limited-stop service.

Optimal Express Bus Routes Design with Limited-Stop Services for Long-Distance Commuters

This research aimed to propose a route optimization method for long-distance commuter bus service to improve the attraction of public transport as a sustainable travel mode. Taking the express bus services (EBS) in Changping Corridor in Beijing as an example, we put forward an EBS route-planning method for long-distance commuter based on a solving algorithm for vehicle routing problem with pickups and deliveries (VRPPD) to determine the length of routes, number of lines, and stop location. Mobile phone location (MPL) data served as a valid instrument for the origin–destination (OD) estimation, which provided a new perspective to identify the locations of homes and jobs. The OD distribution matrices were specified via geocoded MPL data. The optimization objective of the EBS is to minimize the total distance traveled by the lines, subject to maximum segment capacity constraints. The sensitivity analysis was done to several key factors (e.g., the segment capacity, vehicle capacity, and headway) influencing the number of lines, the length of routes. The results suggest that the scenario with the segment capacity of 4000 passengers/h has a minimum of number and length of lines, but we recommend that the transit agency adopt 3000 passengers/h as the route segment capacity because this scenario results in minimum fleet size and minimum total operation length.

Simulation-based robust optimization of limited-stop bus service with vehicle overtaking and dynamics: A response surface methodology

We propose a robust optimization model for limited-stop bus service with vehicle overtaking and demand dynamics. Time-dependent stochastic travel time is also considered. The objective is to minimize the total cost (user cost and operation cost) at the planning phase given a target reliability imperative. We further propose a simulation-based optimization framework incorporating response surface methodology to solve the problem efficiently. A real-world application result shows that vehicle overtaking and demand dynamics have significant impacts on the performance of limited-stop service and that the stop patterns are quite distinct when overtaking and demand dynamics are considered.

Optimizing limited-stop services with vehicle assignment

This paper studies limited-stop operations for rail transit systems and presents an optimization model, which aims to minimize passengers’ travel times and on-board crowdedness. The model combines the design of service itinerary for each vehicle and the allocation of vehicles of various types among multiple lines. Three methods are proposed including a mixed-integer program and two column generation algorithms. Numerical results on generic scenarios show that the column generation algorithm can provide sub-optimal solutions and is computationally efficient. In a case study on Melbourne’s railway network, its solution significantly improves in the passenger travel time compared to the current practice.

Limited-stop bus service: A strategy to reduce the unused capacity of a transit network

Abstract Flexible adaptation to the heterogeneous distribution of travel demand is a challenging issue in the transit network design and planning. Limited-stop service is a strategy used to deal with this problem. In this paper, a bi-level mathematical model is proposed in which the upper-level model minimizes the total fleet unused capacity of limited-stop services, while the objective function of the lower-level model is to minimize total expected travel time for all passengers. Since this model is operator-oriented, some constraints are embedded in it in order to prevent excessive fall of the passengers' service level. Actually, the upper level is a mixed integer linear programming model; but because of NP-hardness and the lower level model, a heuristic algorithm is developed in order to solve the proposed bi-level model. It's worth mentioning that this heuristic approach is based on iterated local search, simulated annealing, and tabu search metaheuristics. Finally, a vast variety of numerical experiments are carried out that are based on some virtual origin-destination demand matrices generated according to different characteristics. Computational results show that by replacing the local service with the set of limited-stop services, the fleet unused capacity can be reduced by up to 48%.

Design of limited-stop service based on the degree of unbalance of passenger demand.

This paper presents a limited-stop service for a bus fleet to meet the unbalanced demand of passengers on a bus route and to improve the transit service of the bus route. This strategy includes two parts: a degree assessment of unbalanced passenger demand and an optimization of the limited-stop service. The degree assessment of unbalanced passenger demand, which is based on the different passenger demand between stations and the unbalance of passengers within the station, is used to judge whether implementing the limited-stop service is necessary for a bus route. The optimization of limited-stop service considers the influence of stop skipping action and bus capacity on the left-over passengers to determine the proper skipping stations for the bus fleet serving the entire route by minimizing both the waiting time and in-vehicle time of passengers and the running time of vehicles. A solution algorithm based on genetic algorithm is also presented to evaluate the degree of unbalanced passenger demand and optimize the limited-stop scheme. Then, the proper strategy is tested on a bus route in Changchun city of China. The threshold of degree assessment of unbalanced passenger demand can be calibrated and adapted to different passenger demands.

Optimising the design of a limited-stop bus service for a branching network

This paper presents an optimisation model for designing limited-stop lines for a branching bus network composed of several feeder lines and a trunk line. On the basis of the different demand patterns in the feeder lines and the trunk line, passenger assignment in the bus route is considered. The optimisation model is used to calculate the total cost of a transit system in which limited-stop services are implemented on bus routes. The total cost includes the cost of passenger waiting time and in-vehicle time, as well as the operator cost for each bus route. With better service planning of limited-stop lines, based on the demand behaviour in high-demand corridors, the total cost can be reduced (compared with the normal service costs of stopping all buses at all stops). A genetic algorithm is adopted to ascertain the optimal model. This algorithm can determine continuous and discrete optimisation variables: the optimal bus frequencies and the best pattern of limited-stop use for each bus route. Finally, a numerical example is optimised. The results show that a limited-stop service for branching corridors can reduce the total cost of the transit system.

A new solution framework for the limited-stop bus service design problem

Limited-stop services are a key element to the successful operation of bus rapid transit corridors. In this study, we present a framework for addressing the limited-stop service design problem over a corridor, and formally introduce a family of subproblems involved in its solution. Using a bi-level optimization approach, we introduce a method of designing these services while considering bus capacity, transfers, and two behavioral models for passengers: deterministic and stochastic. The algorithm and its variants were tested on nine scenarios with up to 80 stops. Working with deterministic passenger assignment, our model solved the problem in a small fraction of the time required by a benchmark algorithm. We use this algorithm to show that neglecting transfers can lead to suboptimal solutions. We finally show that although it makes the problem much harder, working with stochastic assignment leads to more realistic and robust solutions.

Designing Limited-Stop Transit Service with Fixed Fleet Size in Peak Hours by Exploiting Transit Data

Efficiently designed limited-stop transit service is an attractive way to respond to high commuter travel demand in which trips concentrate on a few origin–destination pairs during peak hours. Such service is redesigned in many metropolises in China. Some research has dealt with this situation; bus fleet size was assumed to be unlimited, and the research was concerned with the average daily passenger flow rather than the specific average peak hour travel demand. In contrast to previous work, this paper presents an approach to design limited-stop transit service with the existing available fleet size from current normal service and focuses only on peak hour travel demand extracted through exploitation of transit data. First, a model for limited-stop service was proposed to minimize user costs through existing fixed fleet size. A heuristic algorithm was developed to search the transit line structure for limited-stop service instead of selecting lines from the predefined set. Next, a case in Chengdu, China, was tested. The results indicate that up to 9.32% of total travel time can be saved with the fixed fleet size when limited-stop transit service is applied. Finally, different proportions of commuter flow and different travel behaviors are discussed to illustrate the performance of limited-stop service for different scenarios.

When and where are limited-stop bus services justified?

ABSTRACTAlthough limited-stop bus services around the world have proven to benefit users and operators alike, there are few published studies on design methodologies for such services and little clarity on when or where they are best applied to a given bus corridor. This article reports on an experiment in which a design algorithm for limited-stop services in a corridor was used to optimise almost 1000 scenarios. A regression model was then calibrated to estimate the benefits of operating limited-stop bus services as a function of various attributes of the corridor. The benefits from limited-stop services increase with higher dwell times, number of trips, concentration of trips in few origin–destination pairs and critical arc load, and with lower wait time values and vehicle capacity. The analytic expression derived from the regression model provides an unprecedented tool to forecast the benefits of implementing limited-stop services.

Methodology for Evaluating Potential for Limited-Stop Bus Service along Existing Local Bus Corridors

Limited-stop bus service is a service configuration implemented by many large transit agencies along high-demand bus corridors. Limited-stop service is advantageous because it produces faster running times along the route or corridor than those of local service and it increases efficiency in terms of the number of trips a vehicle can make along the route or corridor in a given time span. However, for many transit agencies it is not necessarily apparent whether the implementation of a limited-stop service configuration along specific routes and corridors will provide a net benefit to passengers, especially under a resource-neutral implementation strategy in which local bus trips are replaced with limited-stop trips. Although a resource-neutral implementation strategy offers the greatest potential for cost savings, increases in wait, access, and egress time for passengers along a corridor can easily offset the intended benefits of reduced onboard time and cause a reduction in the quality of service to passengers. This study developed a methodology for transit agencies to evaluate the potential for limited-stop bus service along existing local routes. The methodology was designed to identify existing routes where the net benefits of onboard travel time savings outweighed the net burdens of increased wait, access, and egress times should limited-stop service be implemented. A set of six metrics was used for the evaluation: existing service frequency, concentration of passenger demand, distribution of stops with high passenger demand, passenger trip length, roadway geometry, and traffic congestion. The methodology was applied to identify candidates for limited-stop service within the Massachusetts Bay Transportation Authority bus network.

A simulation of transit bus emissions along an urban corridor: Evaluating changes under various service improvement strategies

This study investigates the impacts of transit improvement strategies on bus emissions along a busy corridor in Montreal, Canada. The local transit provider, Société de Transport de Montréal, has implemented a number of strategies which include the use of smart cards, limited-stop (express bus) service, and reserved bus lanes along this corridor. Using data collected on-board for instantaneous speeds and stop-level ridership, we estimated bus emissions of greenhouse gases and other pollutants at three levels: road segment, bus-stop, and per passenger. A regression of segment-level emissions against a number of explanatory variables reveals that reserved bus lanes and express bus service reduce emissions significantly. On the other hand, smart card use reduces idling emissions compared to other fare payment methods. Our findings are of most relevance for transit planners who are seeking to implement different strategies to reduce emissions and improve transit performance.

Incremental bus service design: combining limited-stop and local bus services

Long in-vehicle travel times resulting from frequent stops make bus service an unattractive choice for many commuters. Limited-stop bus services however have the advantage of shorter in-vehicle times experienced by passengers. In this work, we seek to modify a given bus service by optimally reassigning some number of bus trips, as opposed to providing additional trips, to operate a limited-stop service. We propose an optimization model to determine a limited-stop service route to be operated in parallel with the local service and its associated frequency to maximize total user welfare. A few theoretical properties of the model are established and used to develop a solution approach. As a proof of concept, we present numerical results obtained using real-world data together with comprehensive discussions of solution quality, computational times and the model’s sensitivity to different parameters. Finally, we solve the optimization model for 178 real-world bus routes with different characteristics in order to demonstrate the impacts of some key attributes on potential benefits of limited-stop services.