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The planning of urban bus routes and frequencies: A survey
Abstract
Urban bus services still play an important role in the movement of people in Britain, although since the 1950's bus patronage has been declining and costs of operation have been increasing. Most of the urban bus networks in Britain (and to a very large extent the Western World) have developed or evolved over the years and it is sometimes said that, despite the changing conditions of bus transport, few of these bus networks in Britain have undergone major re-organisation. A survey was carried out to ascertain this view and to establish the approaches used by British urban bus operators.
Five approaches to the planning of urban bus routes and frequencies have been identified: (1) manual; (2) Market Analysis Project; (3) systems analysis; (4) systems analysis with interactive graphics; and (5) mathematical. Previous research in, and application of, the different approaches are described and examined.
Between 1970 and 1980, 82.4% of those British urban operators who responded to the survey carried out some kind of major bus study. The survey results run counter to the view that there has been little recent change in urban bus networks in Britain, but the alleged conservatism of the bus industry appears when the approaches used for re-planning bus services are examined - 71.4% of the operators used a manual approach and only a meagre 28.6% made use of simple assignment techniques to predict the potential passenger impacts of the alternative networks appraised.
... Line planning has been discussed in hundreds of publications over the past decades, as seen from survey papers [5,6,7]. However, the PRIVOL method, successfully used in the Czech and Slovak Republics, is not mentioned there. ...
... represents the inspiration for creating the method PRIVOL that is mentioned in the following Sections, it enters the bibliography although it is cited in [5]. ...
... Perhaps, even more than some hundreds papers have been focused on this topic. Survey type papers, like [5,6,7] have a prominent position among them. The last two are quite recent (2009/2012) and one can find much more than a hundred entries in their bibliography. ...
In the paper, the public transportation line planning means planning of routes and frequencies of vehicles on them. In the world literature, different criteria are used in this context; mainly the variable costs of lines, the fixed costs of lines, the fixed plus variable costs of lines, the number of direct travellers, the total or average riding time and the total or average travelling time. The current paper adds two more: the total number of used vehicles (to be minimized when all passengers are transported) and relative excess of supply over demand (to be maximized without exceeding the number of available vehicles). Basic mathematical models for both cases are presented and the motivation of such approach is described including a brief excursion into the history of the Czech and Slovak research of line planning where the use of these objectives has arisen. Further, the basic models were modified for the cases of fourteen special practical requirements, e.g. heterogeneous vehicle fleet (= rolling stock), limitation of transfers, elastic demand, limited total number of lines, etc. The brief outline of the experience with practical use is added as well.
... With respect to the transport services design methods and models, some interesting literature reviews were proposed by [23,[34][35][36], where [23] provides an extensive review concerning the public transport system design and scheduling; [34] describes the five main commonly applied techniques for planning urban bus routes and frequencies; [35] analyses the use of operation research techniques applied to the public transport domain; finally, [36] provides a wide review on the methodologies adopted for solving the Transit Route Network Design Problem (TRNDP). ...
... With respect to the transport services design methods and models, some interesting literature reviews were proposed by [23,[34][35][36], where [23] provides an extensive review concerning the public transport system design and scheduling; [34] describes the five main commonly applied techniques for planning urban bus routes and frequencies; [35] analyses the use of operation research techniques applied to the public transport domain; finally, [36] provides a wide review on the methodologies adopted for solving the Transit Route Network Design Problem (TRNDP). ...
The sustainable design of public transport services is a crucial issue that may affect the economy of local areas and the social inclusion of their inhabitants. Indeed, transport accessibility of households, businesses, and retail activities is one of the main drivers that influence location choices and sustainable development and where the public transport services may play a key (positive) role. Furthermore, the economic crisis of the 2009 and the current ones caused by the COVID-19 pandemic has further limited the funds available for public services, including the transport sector. In this critical context, sound design of public transport services assumes great importance, especially in light of financial constraints. Starting from these considerations, the aim of this paper has been to propose an innovative methodology for designing public transport services based on a rational decision-making process with stakeholder engagement, aiming to perform a sustainable development perspective. The proposed methodology combines technical aspects, social and political issues, equity perspectives, and it is aimed in obtaining a design solution that can be accepted by the whole community. The proposed theoretical design methodology has also been applied to a case study in order to verify its applicability to a real context, consisting of the design of the public transport plan of the province of Foggia in southern Italy. Applications results show that the sustainable design scenario is not only the best ones from a technical point of view, but also participated, equitable, and approved by both policymakers and stakeholders.
... Static route network planning has been studied widely in the past. Good reviews can be found in [4,5,6]. Typically, the approaches focus on the development of optimal or near-optimal plans using various types of effective vehicle routing algorithms. ...
... The central server 6 is in charge of maintaining the location, price and status (available, occupied) of each taxi, and provides a set of functionalities such as calculating the closest taxis to a given location. Taxis send periodically their location to the server, and update their status and cost. ...
Nowadays, vehicles of modern fleets are endowed with advanced devices that allow the operators of a control center to have global knowledge about fleet status, including existing incidents. Fleet management systems support real-time decision making at the control center so as to maximize fleet performance. In this paper, setting out from our experience in dynamic coordination of fleet management systems, we focus on fleets that are open, dynamic and highly autonomous. Furthermore, we propose how to cope with the scalability problem as the number of vehicles grows. We present our proposed architecture for open fleet management systems and use the case of taxi services as example of our proposal.
... Because the re-emergence of BRT systems is a relatively recent endeavor, most extant literature concentrates on the more classic problem of routing buses that move freely within the road network while sharing it with other modes of transportation (for a review of the bus routing problem prior to 1990, see Odoni, Rousseau, and Wilson 1994;Chua 1984). In that sense, the classic bus routing problem is to define which path on the road network enables buses to best serve passenger demand. ...
... Above all, most of the work in the literature on urban transit route design was originally formulated not for BRT systems but for the bus routing problem in road networks (Ceder and Israeli 1992;Odoni, Rousseau, and Wilson 1994;Chua 1984;Silman, Barzily, and Passy 1974;Mandl 1980;Mahmassani 1990, 1995;Pattnaik, Mohan, and Tom 1998;Fan and Machemehl 2006) and unfortunately, it is not clear how to extend these methodologies to work on BRT systems. As a result, the route design problem for a BRT system remains unsolved. ...
In recent years, well-designed bus rapid transit (BRT) systems have become a real alternative to more expensive rail-based public transportation systems around the world. However, once the BRT system is operational, its success often depends on the routes offered to passengers. Thus, the bus rapid transit route design problem (BRTRDP) is the problem of finding a set of routes and frequencies that minimizes the operational and passenger costs (travel time) while simultaneously satisfying the system's technical constraints, such as meeting the demands for trips, bus frequencies, and lane capacities. To address this problem, we propose a mathematical formulation of the BRTRDP as a mixed-integer program (MIP) with an underlying network structure. However, because of the vast number of routes, solving the MIP via branch and bound is out of reach for most practical instances. Hence, we propose a decomposition strategy that, given a certain set of routes, decouples the route selection decisions from the BRT system performance evaluation. The latter evaluation is done by solving a linear optimization problem using a column generation scheme. We embedded this decomposition strategy in a hybrid genetic algorithm (HGA) and tested it in 14 instances ranging from 5 to 40 stations with different BRT system topologies. The results show that in 8 of 14 problems, the HGA was able to obtain a solution that is provably optimal within 0.20%. Additionally, in 4 of 14 instances, HGA obtained the optimal solution.
... Analyzing their strengths and limitations is crucial for integrating autonomous driving technology [4][5][6][7]23]. Traditional public transportation systems operate primarily on fixed routes and schedules, designed based on predicted traffic demand [24][25][26][27][28][29][30]. Fixed routes enhance operational efficiency and facilitate movement between key locations but fail to meet the individual needs of diverse Sustainability 2024, 16, 8819 3 of 25 users [31] ...
In addition to addressing the labor shortage due to an aging population, the transition to autonomous vehicle (AV)-based mobility services offers enhanced efficiency and operational flexibility for public transportation. However, much of the existing focus has been on improving AV safety without fully considering road conditions and real-world service demand. This study contributes to the literature by proposing a comprehensive framework for efficiently integrating AV-based mobility services at the network level, addressing these gaps. The framework analyzes and optimizes service networks by incorporating actual demand patterns, quantifying road segment difficulty from an AV perspective, and developing an optimization model based on these factors. The framework begins by quantifying the operational difficulty of road segments through an evaluation of Operational Design Domains (ODDs), providing a precise measure of AV suitability under varying road conditions. It then introduces a quantitative metric to assess operational feasibility, considering factors such as the service margin, costs, and safety risks. Using these metrics alongside Genetic Algorithms (GAs), the framework identifies an optimal service network that balances safety, efficiency, and profitability. By analyzing real-world data from different mobility services, such as taxis, Demand-Responsive Transport (DRT), and Special Transportation Services (STSs), this study highlights the need for service-specific strategies to optimize AV deployment. The findings show that optimal networks vary with demand patterns and road difficulty, demonstrating the importance of tailored network designs. This research provides a scalable, data-driven approach for integrating AV services into public transportation systems and lays the foundation for further improvements by incorporating dynamic factors and broader urban contexts.
... Some of the studies which tackle the public bus operations include the works by Mohring (1972), Kocur and Hendrickson (1982), Ceder and Wilson (1986), Chang and Schonfeld (1991), Sinclair and van Oudheusden (1997), Prakash et al., (1999), Tóth and Krész (2013), and Segundo et al., (2016). The interested reader can also refer to Chua (1984) and Farahani et al. (2013) for a review of the urban transportation network design problems and Guihaire and Hao (2008) for a survey of the general design and scheduling of transportation network. Different from those works, Singgih and Lee (2014) tackle the military deployment problem, which incorporates the multimodal transportation models for troops and cargoes between nodes. ...
This study considers a real-life inter-city bus scheduling problem which incorporates central city locations and trip selection sub-problems. We seek to determine the size of the bus fleet, the cities to be served, the central cities, and the routes and schedules of buses in the fleet. For this purpose, we developed a number of investment scenarios, and for each scenario, we determined possible trip alternatives between cities and resulting expected profits. We then developed an integer linear programming model and a decomposition-based heuristic, which attempt to solve the problem with the objective of profit maximization. Finally, we compare the performance of both solution approaches in terms of the solution quality and computation time for each of the scenarios. The results show that both methods are capable of achieving satisfactory performance for small and medium-size instances, whereas the heuristic outperforms the exact method significantly on large instances.
... In the literature, the bus line planning problem has been extensively investigated, e.g., Ceder and Wilson (1986), Shih et al. (1998), Xu et al. (2019), Kılıç and Gök (2014), Fan and Mumford (2010), Mumford (2013), Baaj and Mahmassani (1991), Nikolić and Teodorović (2013), John et al. (2014), Zhao et al. (2015), Cancela et al. (2015), Jha et al. (2019). Many highlighted line planning approaches are documented in the survey papers Chua (1984), Schöbel (2012), Iliopoulou et al. (2019) and references therein. Though bus lines in many cities, especially metropolises, have been well designed by using advanced techniques, the bus service is still becoming less and less attractive to the passengers due to various issues such as long-standing time, longwaiting time, and unreliable and uncomfortable experience mainly caused by traffic congestion. ...
The increasingly serious traffic congestion makes the bus system more and more inefficient. It is recognized all over the world that designing an attractive bus transit network is primordial to alleviate traffic congestion and reduce pollution, but it is a big challenge from an economic and technical point of view. In the literature, dedicated bus lanes are generally set up to improve the efficiency of bus transit network without considering bus line planning. This study investigates a new bi-objective bus line planning and lane reservation integrated optimization problem that is a complex combinatorial optimization problem. The objective is to minimize the total travel time of passengers and the lane reservation negative impact, simultaneously. For the problem, a bi-objective integer linear programming model is first formulated and the problem complexity is proved to be NP-hard. Then, problem properties are explored to reduce search space for optimal solutions, and an iterative and fuzzy method based on -constraint is proposed to yield the Pareto frontier and suggest a preferred solution for decision-makers. Experimental results on a case study and randomly generated instances demonstrate the effectiveness and efficiency of the proposed model and method.
... However, objectives selection should consider both operators' and passengers' requirements which are often conflicting, leading to a design trade-off rather than an optimal solution [30]. Early bus network design is mainly based on surveys to get travel demands and passenger flows [9,12]. Some work [5,19] leverage passenger OD flows to find a bus route with a fixed frequency, maximizing the number of passengers along a fixed route subject to the total travel time constraint. ...
Shuttle buses have been a popular means to move commuters sharing similar origins and destinations during periods of high travel demand. However, planning and deploying reasonable, customized service bus systems becomes challenging when the commute demand is rather dynamic. It is difficult, if not impossible to form a reliable, unbiased estimation of user needs in such a case using traditional modeling methods. We propose a visual analytics approach to facilitating assessment of actual, varying travel demands and planning of night customized shuttle systems. A preliminary case study verifies the efficacy of our approach.
... Prioritizing urban bus networks (UBNs) has become an important way of solving many urban transportation problems, such as alleviating traffic congestion [1] and reducing emissions. In general, an urban bus is the most basic and important mode of transportation for urban and rural residents and is much more environmentally friendly than other modes of transportation [2]. ...
Urban bus networks play an important role, when the capacity of urban public services is evaluated. With recent advancements in Internet and Communication Technologies, there is an emerging interest in building an urban bus network model through open big data. This has rarely been investigated and exposes several challenges in the provision of transportation services in urban planning. On the one hand, it is necessary to combine bus stations based on spatial distance constraints due to their ambiguous definition in open big data; on the other hand, it is difficult and time-consuming to relocate and build new stations, but the optimization of bus lines is relatively easy to implement. This study aimed to develop an explicit methodological framework for building and analyzing two different types of urban bus network model using open big data. Thereafter, the framework was applied in two case studies in China, within a county-level administration and in a region including three county-level administrations. The key result shows that there was a shortage of urban bus services across these different administrations. This paper contributes to the body of research methodologies into public transport networks and to understanding the sharing of urban public services across administrations, improving the management of urban bus networks, and highlighting the importance of examining the characteristics of urban bus network in county-level administrations rather than just in large cities in China.
... Moreover, other performance analysis such as route design, urban bus planning [111], as well as bus and driver schedule [112] which tried to combine bus and driver schedule are other examples in bus scheduling. Some also set standards such as the number of passengers in a given bus [113], the average kilometers per day by urban buses [113,114]. ...
Anbessa City Bus Service Enterprise (ACBSE) is the only public enterprise that pro
vides transport services in and around the city of Addis Ababa. The transportation
service provided by ACBSE is the safest and cheapest as compared with other public
transport system in the city. However, due to the rapidly growing mass mobility, high
population growth and galloping urbanization in the city of Addis Ababa, providing
and improving urban public transport service is becoming highly difficult and the
enterprise leaves much to be desired and remains long to go. The enterprise as well as
the Ethiopian government has made different interventions to address the problem.
Notwithstanding the efforts attempted, the interventions in the short run as well
as in the long run could not fully address the problem without efficient utilization
and scheduling of buses. Whatever systems are in place as a solution, if there is no
efficient use of that system, it may rather create additional problem.
The unbalanced bus scheduling and fixed bus assignment systems currently used by
the enterprise contributed its share to the problem of poor service quality, low op
erational and financial performances. This dissertation, therefore, tries to assess the
existing operational and financial performances of the enterprise and develop differ
ent models that can improve the performances of the bus scheduling and assignment
systems of the enterprise.
To achieve these objectives, the dissertation conducts an extensive literature review
related to Vehicle Routing Problem (VRP), urban bus public transport services and
different international standards related to urban bus transport. Primary and sec
ondary data related to route performance, bus utilization and scheduling techniques
of the enterprise were also collected. Using the data and the observations made,
first, different operational and financial performance analysis was made. Then an
LP model that can improve the performances of the enterprise was developed. It
is a new model in the knowledge of VRP and; was tested and validated using the
secondary data collected on 93 routes and 4 operating shifts. At last a new VRP
model that can address the stochastic pickup and stochastic delivery of passengers
with real simultaneous pickup and delivery services at each passenger location or bus
stop was developed and introduced to the literature.
The findings of the study show that the overall operational and financial perfor
mances of the enterprise are inadequate as compared with the international stan
dards. The operational performances of the enterprise, namely the Percentage Load
Factor (PLF), the Kilometer Per Vehicle Per Day (KPVPD), the numbers of Pas
sengers carried Per Vehicle Per Day (PPVPD), and the Fleet Utilization (FU) are
lower than the international standards but with higher fuel consumption to every
100kms (ltrs/100km). The PLF, PPVPD and FU have exhibited slight improvement
from time to time. Related to the financial performances, the results show that the
enterprise could not recover its operational costs from the traffic revenue or income
generated. It operates at a loss even before tax. But the results of the new model
show better performances: on the operating costs, bus utilizations, total trips made
and distance covered by the enterprise compared with the existing system. The en
terprise’s performance improvement achieved by the new system on the one hand
cut costs to the enterprise and on the other hand improves the service quality to
passengers by reducing congestion during peak hours.
The dissertation, further tries to develop a model that can address the stochastic
nature of passengers pickup and delivery/drop at each bus stop. Since the LP-model
developed improves the existing system does note exhibits breakthrough improve
ments, a new model was developed if dramatic improvement may be achieved. The
model is the first of its kind due to the fact that it addresses real simultaneous
stochastic pickup and stochastic delivery of passengers. However, due to limitation
of digital road data, the model was not fully tested and implemented. It is only tested by taking limited data on routes on Merkato terminal. The enterprise is expanding
and improving its service from time to time to serve the increasing demand. It serves
the people safely at a cheaper fare. In this regard, the enterprise contributes a lot
to the economy of the society. However, with regards to quality, performance, and
future expansion to regional cities still require extra miles to go. Therefore, based
on the findings of the study the following recommendations are forwarded to the en
terprise. ACBSE should develop and follow a continuous performance improvement
system so as to serve passengers’ need with maximum satisfaction and minimize its
operating costs. The enterprise should adopt the improved bus assignment system
developed in the dissertation so that buses can be assigned based on the demand
distribution of passengers for each route at a given shift or operating times and im
prove its transportation services to the international standards. Further ACBSE, by
improving the availability of buses, should also expand its service to regional cities
where population and mobility are very high.
Re-designing the new routes based on the stochastic distribution of pickup and de
livery of passengers using the proposed model and studying the ticketing services
would be research directions that can be addressed in the future.
... In early research on TRNDP, several categories of methodologies have been identified: manual approach, systems analysis approach, market analysis project (MAP) approach, and systems analysis with interactive graphic approach [6,7]. Recent research has focused on the development and application of mathematical methodologies. ...
This study proposed a hybrid optimization model for urban bus transit route network design problem (TRNDP). Although several mathematical methods had been developed to make the problem tractable, the methods relied on excessive assumptions, which resulted in over-simplification or idealization of the problems. In light of these considerations, a multi-level and multi-mode network design method was introduced in this study. A multi-level network consisted of three levels: skeleton network, arterial network, and feeder network. The different levels of network were associated with different modes of public transportation (such as subway, light rail transit, trolleybus, BRT, normal bus, and community branch) based on the features of bus routes, city sizes, etc. In addition, according to the respective features of urban transit route network structures, we developed different optimization models for different levels. Finally, the proposed methodology was applied to case studies of the city of Zhaoyuan in China and the transit network of Mandl benchmark. The results showed that the total travel time for the proposed method was significantly lower than that of the competing method, with a 21.51% reduction. In addition, the proposed method provided 85.23% direct travelers, 14.65% travelers with one transfer, 0.12% travelers with two transfers, and no unsatisfied demand, which were better than the results from the compared method.
... Urban bus systems, which are a major mode of transport serving the general public, play an important role in the efficient functioning of most urban areas by reducing congestion (Chua, 1984;Cipriani, Fusco, Gori, & Petrelli, 2005). Furthermore, the popularity of urban bus systems is beneficial for reducing energy consumption and pollutant emissions (Andre & Villanova, 2004;Barabino, Deiana, & Tilocca, 2012;Chen, Yu, Zhang, & Guo, 2009). ...
In urban areas, the spatial configuration of urban elements is vital to the sustainable development of cities. Due to the inherent spatial and networked characteristics of UBNs, research on the spatial configuration of UBNs requires a comprehensive approach involving the integration of spatial and network analysis methods. We propose a methodological framework for geospatial network analysis that combines spatial and network analysis to analyse the spatial configuration of UBNs. This framework is based on the construction of an urban bus spatial network (UBSN) in which the network nodes are spatial division units of urban space with more realistic geographical significance. Then, the framework analyses the spatial configuration of the UBN from the identification of macroscopic statistical characteristics to reveal the explicit roles played by microscopic elements such as individual nodes and to further identify the mesoscopic structural organization. The importance of nodes has spatial heterogeneity and directional imbalance. The community detection results demonstrate the UBSN presents obvious spatial agglomeration features, and the overlapping nodes are mostly distributed in the suburbs. With a novel viewpoint and detailed description of the spatial configuration of UBNs, this study provides meaningful insights for policy makers and planners seeking to optimize traffic infrastructure planning.
... Both subgroups use optimization algorithms like GA (Pattnaik et al. 1998;Chakroborty and Dwivedi 2002;Bielli et al. 2002;Tom and Mohan 2003;Fan and Machemehl 2006;Wang and Lin 2010;Cipriani et al. 2012;Deng et al. 2013;Arbex and da Cunha 2015;Zhu et al. 2017), GA with an elitism operator (GA-E) (Nayeem et al. 2014), ACO (Poorzahedy and Safari 2011;Yang et al. 2007;Euchi and Mraihi 2012), BCO (Nikolic and Teodorovic 2013;Jiang et al. 2013), or PSO (Kechagiopoulos and Beligiannis 2014), and search for the optimum solution based on the function of their operators. A comprehensive review of methods used to solve the BRND problem through both subgroups can be found in studies by Chua (1984), Desaulniers and Hickman (2007), Guihaire and Hao (2008), Kepaptsoglou andKarlaftis (2009), Farahani et al. (2013), Johar et al. (2016), and Tarajo and Lee (2016). ...
A simultaneous bus route network design and frequency setting model is formulated as the weighted sum multiobjective genetic algorithm optimization. It aims to search for a near-optimum set of routes and corresponding frequencies while minimizing both user and operator costs. It is a nondeterministic polynomial time complete optimization problem, and searching the entire space through metaheuristic algorithms is impractical. It does require narrowing down the search space into some feasible regions. In this paper, two strategies are implemented, offering a distinct advantage in the finding of near-optimum solutions. First, a set of constraints are imposed on resources defined through experience and route generation and filtration algorithms are implemented to increase the quality of the candidate solution pool. Second, in order to increase the probability of selecting better performing set of routes and reducing genetic algorithm’s degree of randomness, a specially designed transfer minimization operator is implemented within the optimization procedure. Results are then compared on the basis of Mandl’s network that has been used as the benchmark by various researchers. Further, the sensitivity of the model to different rules and parameters is carried out. Obtained solutions perform better as compared to the previous techniques.
... A vast body of literature and several survey papers reviewing existing literature cover line planning (see e.g. Chua 1984;Desaulniers and Hickman 2007;Guihaire and Hao 2008;Ibarra-Rojas et al. 2015;Schöbel 2012). Several authors use the term transit network design instead of line planning, but both problems come along with designing vehicle routes and assigning frequencies. ...
In public transportation, frequency assignment is a sub-problem of line planning which is responsible for assigning each route of a line a certain frequency with which they are serviced by vehicles. Frequency assignment is among the most important decision problems for optimizing the waiting times in a transportation network and is often a very complex matter. This paper focuses on different aggregation techniques for reducing the computational effort to obtain (near-)optimal line frequencies. In detail, the influence of different model formulations and strategies for customer input data aggregation are investigated. For this purpose, six models are provided, their computational complexity is investigated and suitable mixed-integer mathematical programs are developed. These models vary in the levels of line utilization detail and predict the resulting travel times. Both aggregation techniques are evaluated according to their influence on the solution quality, which is determined by the transport suppliers’ point of view as forecast accuracy of the weighted number of customers using the transport. This comprehensive computational study reveals that some model formulations reduce the computational effort considerably by only small losses in line frequency quality. Furthermore, dramatically compressed customer data lead to (near-)optimal line frequencies.
... Having said that, the transit planners and practitioners still consider the problem challenging ( Amiripour, Mohaymany, & Ceder, 2015 ). In addition, the UTNDP is comprehensively surveyed in Chua (1984), Farahani, Miandoabchi, Szeto, and Rashidi (2013), Guihaire and Hao (2008), Ibarra-Rojas, Delgado, Giesen, and Muñoz (2015), Kepaptsoglou and Karlaftis (2009) , and Buba and Lee (2016a) . Pattnaik, Mohan, and Tom (1998) introduced a GA to tackle the problem with the objective of minimizing the costs incurred by both the passenger and the operator. ...
The urban transit network design problem (UTNDP) is concerned with the development of a set of transit routes and corresponding schedules on an existing road network with known demand points and travel time. It is an NP-hard combinatorial optimization problem characterized by high computational intractability, leading to utilization of a wide variety of heuristics and metaheuristics in an attempt to find near-optimal solutions. This paper proposes a differential evolution approach to address the UTNDP by simultaneously determining the set of transit routes and their associated service frequency with the objective to minimize the passenger cost, as well as the unmet demand. In addition, a combined repair mechanism is employed to deal with the infeasible route sets generated from the route construction heuristic and the operators of the differential evolution. The proposed algorithm is evaluated on a well-known Mandl's Swiss network reported in the literature. Computational experiments show that the proposed algorithm is competitive according to the performance metrics with other approaches in the literature.
... Apart from the behavioral aspects, several studies have been reported in the literature on network timetabling/scheduling (Bookbinder and Dé silets, 1992;Chakroborty et al., 1995Chakroborty et al., , 2001Deb and Chakroborty, 1998;Bielli et al., 2010). Several studies have also been reported on network design problems (Chua, 1984;Ceder and Wilson, 1986;Chang and Schonfeld, 1991;Baaj and Mahmassani, 1995;Lee and Vuchic, 2005;Cipriani et al., 2012), most of which aimed to minimize operators' cost or maximize the profit. A few of them also considered social benefits during the design. ...
An approach is documented for identifying optimal service headway and fare for rural bus routes with due consideration to user costs and operational viability of the service. User costs are considered in terms of a comprehensive measure called as ‘Generalized Cost (GC)’. GC is developed using the willingness-to-Pay (WTP) of users with respect to hard and soft factors of rural bus service. As GC varies with service headway and fare, it is aimed to minimize the GC (or maximize user benefits) through selection of optimal service headway and fare. The operational viability of service is duly considered in the process. A simulation model is development for simulating movements of passengers and buses along the route with different service headways and fares. Although travel demand varies during different hours of the day, the work is carried out considering only the peak hour demand. During simulation runs, the arrival of passengers at a bus stop is assumed as random (uniformly distributed) and the headway for operation of buses is assumed as uniform (or fixed). The inputs include route and demand characteristics, bus characteristics, users WTP with respect to various attributes of bus system, fixed cost and variable cost associated with bus, etc. The major outcomes are optimal service headway, fare, GC per passenger, number of bus, etc. The effect of demand on optimal service headway, fare and GC is also studied.
... Static route network planning has been studied widely in the past. Good reviews can be found in [13,26,7]. Typically, the approaches focus on the development of optimal or near-optimal plans using various types of effective vehicle routing algorithms. Fleet schedules designed a priori with static route planning assume the following: all relevant data is known before the planning starts, and the time required for creation, verification, and implementation of route plans is of minor importance (e.g., offline planning). ...
Nowadays, vehicles of modern fleets are endowed with advanced devices that allow the operators of a control center to have global knowledge about fleet status, including existing incidents. Fleet management systems support real-time decision making at the control center so as to maximize fleet performance. In this paper, setting out from our experience in dynamic coordination of fleet management systems, we focus on fleets that are open, dynamic and highly autonomous. Furthermore, we propose how to cope with the scalability problem as the number of vehicles grows. We present our proposed architecture for open fleet management systems and use the case of taxi services as example of our approach. We carried out some experiments, which showed our proposed algorithm outperform the most common assignment method both in waiting times of clients and taxi costs.
... The generation of an efficient bus network and schedule is a difficult optimization problem. We refer to [27], [28], [20], [9], [8] and [3] as pioneering studies of the topic and to [5], [18], [31], [13], [23] and [30] for more recent references. For the study in this paper we use a grid like bus network consisting of horizontal and vertical bus routes. ...
In this paper we present the results of a simulation study aimed at assessing an on-demand transportation system. The on-demand system uses minibuses that have neither fixed itineraries nor fixed stops. The minibuses are dynamically routed to accommodate the requests received by the users. To use the on-demand service, users communicate, close to their desired departure time, the origin and destination of the trip. They accept the service if the estimated arrival time at destination fulfills their service level threshold. In the simulation users may decide whether to walk, to use a standard bus, to call the on-demand service, and, if none of these options is satisfactory, to use a private car. We consider different scenarios to assess the potential benefits of the introduction of an on-demand service. We also analyze the scalability and responsiveness of the service. The results suggest that an on-demand system may be able to satisfy a large portion of user transportation requests and may be put beside standard transportation systems in order to provide a better transportation service to the users and substantially reduce the use of private cars.
... It is the main issue in increasing reliability. Proper headway of buses along the route can reduce delays in arrivals of buses at each stop (Chua, 1984;Lin and Ruan, 2009). Operating speed: is defined as average speed in total traveling time. ...
In developing countries, demand for passenger travel is higher, due to economic growth. Government policy encourages people to use public transportation instead of their private carsto reduce of traffic congestion and air pollution. In the city areas, bus networks are the major part of the public transportation system because they are easily accessible and cheaper compared to other types of public transportation. In this study revelation of details of bus operation included different agents is studied. Bus operations, during provision of their service, have interaction with three main agents: bus agent, passenger agent and traffic agent. Study of the influence of each agent in bus operation is presented in this study, using the macroscopic way.
... The generation of an efficient bus network and schedule is a difficult optimization problem. We refer to [28], [29], [21], [10], [9] and [4] as pioneering studies of the topic and to [6], [19], [32], [14], [24] and [31] for more recent references. For the study in this paper we use a grid like bus network consisting of horizontal and vertical bus routes. ...
In this paper we assess an on-demand public transportation system through a simulation study. The on-demand system makes use of minibuses that have neither fixed itineraries nor fixed stops. The minibuses are rerouted online to dynamically accommodate the requests received by the users.
To use the on-demand service users communicate, close to their desired departure time, the origin and destination of the trip.
If the estimated arrival time at destination fulfills the user acceptance threshold, it will be chosen. In the simulation we allow the user to walk, to use the on-demand service, a bus or a private car.
We will consider a large number of scenarios to evaluate the potential
costs/benefits of the introduction of an on-demand service. We will also analyze the scalability and the responsiveness of the service. The results suggest that an on-demand public transportation system would be preferred by most users to the private car and to a bus service. This in turn would imply a more efficient and environmentally friendly transportation system.
... The aim is to determine bus routes and operation frequencies that achieve certain objectives, subject to the constraints and passenger flows. The popular objectives include shortest route, shortest travel time, lowest operation cost, maximum passenger flow, maximum area coverage and maximum service quality while the constraints include time, capacity and resources [30,36,69,163]. ...
Taxis equipped with GPS sensors are an important sensory device for examining people's movements and activities. They are not constrained to a pre-defined schedule/route. Big taxi GPS data recording the spatio-temporal traces left by taxis provides rich and detailed glimpse into the motivations, behaviours, and resulting dynamics of a city's mobile population through the road network. In this dissertation, we aim to uncover the "hidden facets" regarding social and community dynamics encoded in the taxi GPS data to better understand how urban population behaves and the resulting dynamics in the city. As some "hidden facets" are with regard to similar aspect of social and community dynamics, we further formally define three categories for study (i.e. social dynamics, traffic dynamics, and operational dynamics), and explore them to fill the wide gaps between the raw taxi GPS data and innovative applications and smart urban services. Specifically, 1. To enable applications of real-time taxi fraud alerts, we propose iBOAT algorithm which is capable of detecting anomalous trajectories "on-the-fly" and identifying which parts of the trajectory are responsible for its anomalousness, by comparing them against historically trajectories having the same origin and destination. 2. To introduce cost-effective and environment-friendly transport services to citizens, we propose B-Planner which is a two-phase approach, to plan bi-directional night bus routes leveraging big taxi GPS data. 3. To offer a personalized, interactive, and traffic-aware trip route planning system to users, we propose TripPlanner system which contains both offline and online procedures, leveraging a combination of Location-based Social Network (i.e. LBSN) and taxi GPS data sets. Finally, some promising research directions for future work are pointed out, which mainly attempt to fuse taxi GPS data with other data sets to provide smarter and personalized urban services for citizens
... )ȂҏϚ၏क़ӨࣺᜰМᝦϱৠȄޱџՃԃ Jansson [2] ȃKocur ڷ Hendrickson [3] ȃChua [4] ȃKoutsopoulos ้Ρ [5] ȃCeder ڷ Wilson [6] ȃ van Nes ้Ρ [7] ȃںဎЅප [8] ȃCeder [9] ȃChang ڷ Schonfeld [10,11] ...
In the past, research scholars usually used deterministic passenger demands as input for inter-city bus scheduling, simplifying the stochastic disturbances of daily passenger demands in actual operations. In addition, inter-city bus carriers in practice may aim at maximizing both the operating profit and the market share in their short-term operations, instead of confining to a single objective which was usually adopted in the inter-city bus scheduling literature. Considering the multiple objective and stochastic demands in actual operations, we employed network flow techniques to construct a stochastic-demand multi-objective scheduling model, with the objectives of maximizing the operating profit and the number of passengers, to help inter-city bus carriers effectively plan their bus fleet routes and timetables in their short-term operations. The model is formulated as a multiple objective nonlinear mixed integer program. We used the weighting method and the simulation technique to develop a heuristic algorithm to solve the model. To compare the performance of the deterministic-demand and stochastic-demand scheduling models in actual operations, we developed a simulation-based evaluation method. Finally, we conducted a case study using real operating data from a major Taiwan inter-city bus carrier. The results indicated that the model and the solution algorithm could be useful for inter-city bus carriers.
... Moreover, other performance analysis such as route design urban bus planning [16], as well as bus and driver schedule [6] which tried to combine bus and driver schedule are other examples in bus scheduling. Some also set standards such as the number of passengers in a given bus [17], the average kilometers per day [1,17]. ...
Providing and improving urban public transport
service is becoming highly important to meet the demand of
rapidly growing mass mobility due to high population growth
and galloping urbanization in and around the city of Addis
Ababa. This paper tries to assess the existing operational and
financial performances of Anbessa City Bus Service Enterprise
(ACBSE), which is the sole and government owned transport
enterprise. The research used primary data, and secondary data
collected from ACBSE for the last nineteen months. The findings
of the study showed that the overall operational and financial
performance of the enterprise is inadequate. In allthe
parameters of the operational performance, the enterprise
operates under the international standard and couldnot recover
its operational cost from the traffic revenue. Moreover, the
enterprise has deficiency to meet the level of service quality
required as well as to attract more passengers in the future.
Therefore, the enterprise should design an optimum bus
assignment and bus scheduling system so as to serve passengers'
need with maximum satisfaction and minimize its operating
costs.
... Apart from the behavioral aspects, several studies have been reported in the literature on network timetabling/scheduling (Bookbinder and Dé silets, 1992;Chakroborty et al., 1995Chakroborty et al., , 2001Deb and Chakroborty, 1998;Bielli et al., 2010). Several studies have also been reported on network design problems (Chua, 1984;Ceder and Wilson, 1986;Chang and Schonfeld, 1991;Baaj and Mahmassani, 1995;Lee and Vuchic, 2005;Cipriani et al., 2012), most of which aimed to minimize operators' cost or maximize the profit. A few of them also considered social benefits during the design. ...
An approach is demonstrated for identifying optimal bus service giving due considerations to both user costs and operational viability. The effects of demand level and route length on optimal service attributes are also investigated. A model is developed for simulating passenger movements and identifying the optimal service attributes for a demand level. The model is applied for different hypothetical scenarios in order to understand the variation of the optimal attributes with demand and route characteristics. The results indicate the influence of route characteristics, demand level, user costs, required cut-off revenue, etc. on the optimal bus service attributes. The findings from the present work related to fare model indicates that it is necessary to give due considerations to the demand and its distribution as well as length of different routes while recommending an optimal fare model for all the routes in a geographic region. The findings from the present work encourage further investigation on the effect of demand pattern on optimal bus service and selection of an optimal fare model for all routes in a geographic region.
*Full text available @http://authors.elsevier.com/a/1RVf3,oLFq3Pb~ for limited period only
... Once these milestones are set, it is possible to determine the remaining parts with good approximation [2,3]. Generally, approaches used to resolve Transit Bus Route Network Design (TBRND) problem can be classified into empirical, what if and what to [4][5][6]. Empirical methods consist mainly of a qualitative approach, based on the experience of the planner or on the indications supplied by control organisations [7]. The generated networks are not subject to simulation tests. ...
This paper deals with the TBRND and proposes a new heuristic model for its resolution. Planning a bus network is a coordinate and logical process which leads to the definition of routes, frequencies, timetable plans, vehicles and bus drivers scheduling. Routes and frequencies are the most important phases of the planning. Therefore, a model defining a complex objective function has been structured to determine routes and frequencies. This model considers many interesting parameters related to the public transportation network. For its resolution, a complex two-phase heuristic algorithm has been used. In the first one, the route lines are characterized whilst in the second, the frequencies are determined, respecting geometric, operative and congruence constraints. Greedy resolution techniques were employed in the first part, while the second part of the algorithm has been resolved through a random optimization process. The method was implemented and resolved using JAVA language. This model has been experimented on a medium-sized city in Italy, and it has provided some interesting results which make the adopted procedure valid in comparison to the existing network. In particular, they proved effective with specific regard to the business service, standing out for shorter distances covered by the lines, and a 22% reduction of the total travel time against the present scenario.
... The aim is to determine bus routes and operation frequencies that achieve certain objectives, subject to the constraints and passenger flows. The popular objectives include shortest route, shortest travel time, lowest operation cost, maximum passenger flow, maximum area coverage and maximum service quality while the constraints include time, capacity and resources [11], [22], [15], [49]. ...
Abstract—Taxi GPS traces can inform us the human mobility patterns in modern cities. Instead of leveraging the costly and inaccurate human surveys about people’s mobility, we intend to explore the night bus route planning issue by using taxi GPS traces. Specifically, we propose a two-phase approach for bi-directional night-bus route planning. In the first phase, we develop a process to cluster “hot” areas with dense passenger pick-up/drop-off, and then propose effective methods to split big “hot” areas into clusters and identify a location in each cluster as a candidate bus stop. In the second phase, given the bus route origin, destination, candidate bus stops as well as bus operation time constraints, we derive several effective rules to build the bus route graph, and prune invalid stops and edges iteratively. Based on this graph, we further develop a Bi-directional Probability based Spreading (BPS) algorithm to generate candidate bus routes automatically. We finally select the best bi-directional bus route which expects the maximum number of passengers under the given conditions and constraints. To validate the effectiveness of the proposed approach, extensive empirical studies are performed on a real-world taxi GPS data set which contains more than 1.57 million night passenger delivery trips, generated by 7,600 taxis in a month.
... However again there is a tendancy for these sources to emphasise short range planning with little coverage of network planning or restructuring. One UK study reviewed the nature and occurrence of major bus network reviews (Chua, 1984). Some 82% of UK authorities had undertaken a ―major bus network‖ review over a 10 year period between 1970-1980 suggesting such large scale analysis were not quite as rare as has been suggested. ...
Despite an overwhelming case for the redevelopment of historically based bus networks, reviews are difficult to implement because of limited funding, equity concerns, complex technical challenges, difficulty communicating technical issues to stakeholders and the potential displacement of existing users. This paper describes a bus network review process designed in Melbourne, Australia to address these issues. The process adopts evidence based planning and achieves a consensus of outcomes using an inclusive design process adopting advanced analysis tools to communicate technical issues effectively to a non-technical audience.Previous research does not directly address the practical implementation of bus review processes and tends to either focus on short term bus planning approaches or consider theoretical applications with limited practical value.The bus network review process developed is based on strategic studies aimed at opportunities to grow bus markets. The process is highly consultative to build stakeholder ‗buy-in‘ and adopts a two stage program (1. problem identification inputs and 2. draft network review inputs) using nominal group techniques to ensure inclusive participation and quantification of outputs. The review process uses a simple to understand hierarchy approach to review services including assessment of Access, Time Factors, Ease of Use, Safety and Awareness. Graphical techniques including GIS are adopted for clear and simple presentation of technical outputs.The process has been powerful in building ‗buy-in‘ and has resulted in $A1.4B of investment in improved services with high ridership growth outcomes. Experience and impacts are outlined including areas for future research.
... We will sketch generalizations of the basic models and review solution approaches. For literature up to the beginning of the 1990s, we refer to the surveys by Israeli and Ceder (1995) and Chua (1984) for more application-oriented approaches. ...
The problem of defining suitable lines in a public transportation system (bus, railway, tram, or underground) is an important
real-world problem that has also been well researched in theory. Driven by applications, it often lacks a clear description,
but is rather stated in an informal way. This leads to a variety of different published line planning models. In this paper,
we introduce some of the basic line planning models, identify their characteristics, and review literature on models, mathematical
approaches, and algorithms for line planning. Moreover, we point out related topics as well as current and future directions
of research.
KeywordsLine planning–Public transportation–Mathematical programming
Santiago, the capital city of Chile, has seven million inhabitants in an area of 850 km². This city has a metro network with seven lines extending 140 kilometers and transports approximately 2.6 million people daily. The bus system has undergone significant transformations over the last three decades. The most relevant change having been Transantiago, the public transportation system implemented in 2007 for Santiago, Child, which combines the use of Metro and buses (BRT). Metropolitan Mobility Network (called Red) is the latest version of the public transportation plan. This paper aims to analyze the current subway infrastructure using the continuous approximation method for Santiago, Chile. We previously proposed a macroscopic methodology to identify the needs for an adequate level of service in urban mobility and transportation, and we applied it to Santiago’s Metro network. Our work focuses on functionality and demand distribution. Santiago’s demand varies spatially in volume and extension throughout the city. Using the latest origin-destination survey from 2012, we deduct the critical components in this current network structure. It is worth mentioning that the Metro design bases its network on a ring-radial structure. With our macroscopic model applied to Santiago, Chile, we have detected infrastructure needs in the current transit network. The supply of infrastructure should increase for two reasons: first, to achieve balanced cost levels between users and the agency and second, to reduce subway occupations. The optimal model outcomes for Santiago define the optimal network in which the system requires five rings and ten end-to-end longitudinal lines (20 radial routes), including lower levels of occupation. The obtained results are a good preliminary solution, considering the subway infrastructure supply could be sub-estimated in the public transportation plan.
Enhanced bus services that aim to attract potential car users by offering qualities of services more closely aligned with those offered by the private car tend to emphasise frequency, connectivity, speed and travel time reliability. ?Full? Bus Rapid Transit (BRT) is one end of the spectrum of such services that requires substantial investment in dedicated infrastructure to provide fast services but examples of enhanced services that do not require such infrastructure are more common in Australia and Europe than full BRT. This paper uses historical evidence to provide an overview of the development of these services in Australia and documents the existing evidence for the success of these initiatives taking into account the trade-offs that naturally occur as a result of the inherent constraints of network design with limited financial resources. This paper uses the concept of the passenger supply chain to describe which service attributes were targeted by the implementation of the enhanced service. It adds to the bus service literature by looking at aspects of quality of service rather than how the vehicles traverse the physical infrastructure.
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.
Given the public transportation network, i.e., information about the location of the stations, the tracks connecting the stations, and the lengths of the tracks, line planning
aims at determining the lines, i.e., the routes served regularly by a train. Furthermore, in many line planning approaches, not only the routes which should be served are considered, but also the frequencies of the services are planned.
In the beginning of the paper, the position of routing problems in the historical development of public transport is outlined. It is explained why the boom of research papers on this issue came in the seventies of the last century. It is described, how the contacts of Czechoslovak and Swedish researchers, at the same time, motivated the first ones to use the Erlander principle, i.e. starting with a set of "candidate" routes and afterwards choosing some of them by variables which are equal to the number of assigned buses. Afterwards it is shown that the original Erlander approach used the total passenger time losses as objective function. It led to a non-linear model since the unknown variable expressing the number of vehicles enters into the denominator of the objective function. Another complication of the model was in the necessity to avoid zeroes in the denominators. Czechoslovak researchers did not possess any computer enabling to solve non-linear optimization problems of the dimensions met in practice, Therefore, they decided to replace the indicator of total passenger time losses by another one which would not contain the decision variable in the denominator, but in the numerator They took the numerical ratio of number of places in vehicles to the number of passengers. Further, the paper embodies the results achieved in the Czech and Slovak Republic into the context of world literature. The optimization methodology PRIVOL is then described in details, together with a brief outline of its application. Finally, the further development of research is predicted. E.g. the incorporation of demand elasticity with respect to the transport supply into the constraints in the model.
Seasonal demand variation is a somewhat neglected aspect of transit demand. Many cities worldwide experience seasonal variation of passenger demand that deserves not only changes of service frequency, but also and often more importantly, changes in the transit network of routes. Literature dealing with optimal bus networks shows that it is an non polynomial (NP)-hard complexity problem with the demand being the most important variable affecting the network. Thus, the bus network of concern should be robust from the optimization perspective when a new demand arises. This paper introduces a model and a solution algorithm to take into account the variation of passenger demand in the design of bus networks. The solution algorithm developed is a hybrid method that optimizes the design of a bus network at the route and network levels. The model was applied to the city of Mashhad in Iran with a population of over 3.2million and 20million visitors annually. The results are promising and demonstrate how to determine the best single network of bus routes to suit variable passenger demand.
The bus network design problem refers to a determination of optimizing the network of bus routes, usually in urban areas. The optimal routes must comply with a given passenger demand matrix and attain a compromise best solution from the user, the operator, and the community. This paper proposes the use of a genetic algorithm as a tool to handle the complexity of the bus network design problem. The methodology developed considers a mechanism to maintain as many satisfactory routes of the existing network as possible and, at the same time, to incorporate experience-based suggestions, such as minimizing of the number of transfers required by a passenger, into the revised bus network. The solution method, using genetic algorithm, has four steps: (1)generating a set of potential routes, (2)designing the bus network, (3)checking the routes for implementation, and (4)examining the extension of routes for improvement. The proposed method is validated through a benchmark bus network and a case study. The result of the case study, with a bus network serving a city with a population of 3.2million, shows an improvement of 26.36% in the objective function value over the existing bus network. This improvement was realized by modifying only 36% of the routes while the remaining 74% of the existing network remained intact.
The design of urban bus transit systems aims to determine a network configuration with a set of bus lines and associated frequencies that achieve the targeted objective. This paper presents a methodology framework to formulate and solve the bus transit network design problem (TNDP). It first proposes a TNDP taking into account the travel time stochasticity. A robust optimization model is formulated for the proposed problem, which aims to minimize the sum of the expected value of the operator cost and its variability multiplied by a weighting value. A heuristic solution approach, based on k-shortest path algorithm, simulated annealing algorithm, Monte Carlo simulation, and probit-type discrete choice model, is subsequently developed to solve the robust optimization model. Finally, the proposed methodology is applied to a numerical example. (C) 2013 American Society of Civil Engineers.
Creating a bus network that covers passenger demand conveniently is an important ingredient of the transit operations planning process. Certainly determination of optimal bus network is highly sensitive to any change of demand, thus it is desirable not to consider average or estimated figures, but to take into account prudently the variations of the demand. Many cities worldwide experience seasonal demand variations which naturally have impact on the convenience and optimality of the transit service. That is, the bus network should provide convenient service across all seasons. This issue, addressed in this work, has not been thoroughly dealt with neither in practice nor in the literature. Analyzing seasonal transit demand variations increases further the computational complexity of the bus-network design problem which is known as a NP-hard problem. A solution procedure using genetic algorithm efficiently, with a defined objective-function to attain the optimization, is proposed to solve this cumbersome problem. The method developed is applied to two benchmarked networks and to a case study, to the city of Mashhad in Iran with over 3.2 million residents and 20 million visitors annually. The case study, characterized by a significant seasonal demand variation, demonstrates how to find the best single network of bus routes to suit the fluctuations of the annual passenger demand. The results of comparing the proposed algorithm to previously developed algorithms show that the new development outperforms the other methods between 1% and 9% in terms of the objective function values.
This paper shows the iterative approach to solving transit network design problem, particularly with variable transit demand under a given fixed total demand. Although recent studies, which use a simplified combinatorial search approach, showed their capability of building optimal transit networks and handling the complicated transit travel time characteristics, only this iterative approach is believed to properly handle the dynamic characteristics of the relationship between variable transit trip demand and optimal transit network design. Since transit demand depends on the configuration of the transit network and frequencies of the routes, this approach is more desirable for transit network planning than combinatorial approach. The basic approach generates the optimal transit network from the initial network, which requires the shortest in-vehicle travel time, through iterating the assignment procedure and the improvement procedure until there is no more improvement in the network. With variable transit demand, the modal split procedure is added to the basic model to generate the optimal transit network and to estimate transit demand simultaneously. This paper also shows the relationship between optimal transit network design and critical design inputs, such as transit operating speed, total demand size, and transfer penalty. As results of the analysis, synergistic effect of variable transit demand and the optimal transit network are discussed.
Despite an overwhelming case for the redevelopment of historically based bus networks, reviews are difficult to implement because of limited funding, equity concerns, complex technical challenges, difficulty in communicating technical issues to stakeholders, and potential displacement of existing users. This paper describes a bus network review process designed in Melbourne, Australia, to address these issues. The process adopts evidence-based planning and achieves a consensus of outcomes by using an inclusive design process with advanced analysis tools to communicate technical issues effectively to a nontechnical audience. Previous research does not directly address the practical implementation of bus review processes and tends either to focus on short-term bus planning approaches or to consider theoretical applications with limited practical value. The bus network review process developed is based on strategic studies aimed at opportunities to grow bus markets. The process is highly consultative to build stakeholder buy-in and adopts a two-stage program of (a) problem identification inputs and (b) draft network review inputs using nominal group techniques to ensure inclusive participation and quantification of outputs. The review process uses a simple-to-understand hierarchy approach to review services including assessment of access, time factors, ease of use, safety, and awareness. Graphical techniques including geographic information systems are adopted for clear and simple presentation of technical outputs. The process has been powerful in building buy-in and has resulted in A1.4 billion (US1.3 billion) of investment in improved services with high ridership growth outcomes. Experience and effects, including areas for future research, are outlined.
Urban bus route network design involves determining a route configuration with a set of transit routes and associated frequencies that achieves the desired objective. This can be formulated as an optimization problem of minimizing the overall cost (both the user`s and the operator`s) incurred. In this paper, the use of genetic algorithms (GAs), a search and optimization method based on natural genetics and selection, in solving the route network design problem is reported. The design is done in two phases. First, a set of candidate routes competing for the optimum solution is generated. Second, the optimum set is selected using a GA. The GA is solved by adopting the usual fixed string length coding scheme along with a new variable string length coding proposed in this study. The former assumes a solution route set size, and tries to find that many best routes from the candidate route set, using a GA. The route set size is varied iteratively to find the optimum solution. In the newly proposed variable string length coding method, the solution route set size and the set of solution routes are found simultaneously. The model is applied to a case study network, and results are presented.
Taxi GPS traces provide us with rich information about the human mobility pattern in modern cities. Instead
of designing the bus route based on inaccurate human survey regarding people’s mobility pattern, we intend to address the night-bus route planning issue by leveraging taxi GPS traces. In this paper, we propose a two-phase approach based on the crowd-sourced GPS data for night-bus route planning. In the first phase, we develop a process to cluster “hot” areas with dense passenger pick-up/drop-off, and then propose effective methods to split big “hot” areas into clusters and identify a location in each cluster as a candidate bus stop. In the second phase, given the bus route origin, destination, candidate bus stops as well as bus operation time constraints, we derive several effective rules to build bus routing graph and prune the invalid stops and
edges iteratively. We further develop two heuristic algorithms to automatically generate candidate bus routes, and finally we select the best route which expects the maximum number of passengers under the given conditions. To validate the effectiveness of the proposed approach, extensive empirical studies are performed on a real-world taxi GPS data set which contains more than 1.57 million passenger delivery trips, generated by 7,600 taxis for a month in Hangzhou, China.
Cited By (since 1996): 14, Export Date: 8 January 2013, Source: Scopus
In this paper we examine the transit network design problem under the assumption of elastic demand, focusing on the problem of designing the frequencies of a regional metro. In this problem, investments in transit services have appreciable effects on modal split. Neglecting demand elasticity can lead to solutions that may not represent the actual objectives of the design. We propose four different objective functions that can be adopted to assume demand as elastic, considering the costs of all transportation systems (car, bus and rail) as well as the external costs, and we define the constraints of the problem. Heuristic and meta-heuristic solution algorithms are also proposed. The models and algorithms are tested on a small network and on a real-scale network.
An interactive modelling approach is developed to solve the practical problem of bus route network design. Possible bus routes are identified with facilities which can be located. Zones or pairs of zones in the urban area are identified with customers who will be allocated to the established facilities. It is shown that the classical Set Covering Problem is useful under the assumption of fixed demand; the Simple Plant Location Problem is effective under the assumption of demand which is sensitive to the level of bus service provided.
The setting of timetables and bus routing/scheduling are essential to an inter-city bus carrier's profitability, its level of service and its competitive capability in the market. In the past, carriers in Taiwan usually set their timetables and bus routes/schedules manually, which was inefficient. In this research we thus attempt to develop a model that will help Taiwan inter-city bus carriers in timetable setting and bus routing/scheduling. The model employs multiple time–space networks that can formulate bus movements and passenger flows and manage the interrelationships between passenger trip demands and bus trip supplies to produce the best timetables and bus routes/schedules. Mathematically, the model is formulated as a mixed integer multiple commodity network flow problem. An algorithm, based on Lagrangian relaxation, a sub-gradient method, the network simplex method, a Lagrangian heuristic and a flow decomposition algorithm, is developed to efficiently solve the problem. The results of a case study, regarding a major Taiwan inter-city bus operation, illustrate the model performance.
This paper evaluates an experimental approach for designing a bus rapid transit system. The particular system was to serve a single large destination, the University of Washington, and to meet desired levels of performance within a series of constraints regarding its physical characteristics. The experimental definition included a large and complex network, a demand set, a cost-benefit framework that includes 23 performance measures, a group-determined set of weights of relative importance for the performance measures, acceptable and ideal standards for the performance measures, a group-determined set of parameters for the modal-split model contained in UTRANS, and a set of upper limits on the size of the system. The design strategies used are discussed and the experience of one team that processed 28 design alternatives is illustrated.
A man-computer interactive graphic system, developed at the University of Washington, is applied to a series of experiments designed to identify the characteristics of high-performance bus rapid transit systems for CBD-bound riders who reside in a generalized suburban corridor. The solution spaces of each 12 problem cases, derived from the combination of several trip demand densities, highway network characteristics, and trip-making behaviors, are explored in an interactive graphic search process.
A man-computer interactive graphic system for planning node-oriented (multiple-origin to single-destination) transit systems is presented. The system is implemented in a real-time computer environment with a cathode-ray tube. The paper describes the modal split/network equilibrium model on which the prediction process is based and illustrates in an example the mechanics and capabilities of the man-computer interactive approach.
This paper describes a model for determining the general dimensions of an optimal mass transit system for an idealized urban area. The model is based on a circular city with a definite center and with density declining uniformly from the center in all directions according to the negative exponential function. The transit system consists of radial routes that emanate from the center and contain discrete stops. Only trips to or from the center are considered, and travel is assumed to occur only in radial and circumferential directions. The model represents total community costs of the system, defined to include travel time, operating costs, equipment, and construction.
A computer-based model is described that evaluates bus networks, i. e. it predicts the patronage expected on a network, and works out the implications of that patronage for each route, and for the network as a whole. The model is orientated towards the use of generalised cost.
A person-computer interactive graphics system for optimizing the routing structure on an urban transit network is presented. The system allows a user to design bus, streetcar, and subway routes on a display scope and to specify route frequencies and types of vehicles. The system is based on a multipath transit assignment model that is a further development of R. B. Dial's stochastic assignment algorithm. The methodology and some results of these applications are described.
The paper presents a discussion of some issues relating to the design of minimum cost bus routes serving a multiple origin-multiple destination trip distribution. It is shown that the objective function (total cost) is a nonconvex function of the assignment; the higher the demand for trips on a route, the better is the service that one can provide. One consequence of this is that a square grid of straight line bus routes is not likely to be an optimal geometry even under highly idealized conditions. ″Good″ geometries are more likely to focus routes onto a single street and past a common junction.
This paper describes a case study of the reorganization of a municipal bus undertaking. The terms of reference were to consider reorganizing the route structure, to advise on frequencies to operate on the chosen routes, to compile timetables, and to design bus schedules so that the recommended system could be implemented with the minimum number of active buses. Theoretically, all of these variables can interact and one global model should be used to optimize the entire system simultaneously. In practice, the components of this problem had to be uncoupled and tackled separately. An heuristic model designed to provide a "good" route network was developed. Service frequencies were allocated to routes so that a measure of service to passengers was maximized. Bus timetables were compiled using conventional methods and a linear programming model used to assign individual buses to journeys. A new scheme based on the recommendations of the study has been implemented. It is expected that it will reduce the annual operating deficit by [pound]35,000 without appreciably decreasing the overall level of service offered.
Passengers are to be carried to a rapid transit line by feeder transit lines perpendicular to the rapid transit line. How should the feeder lines be located and how should their schedules respond to a passenger arrival pattern that varies with location and time? These questions are answered for a system with a simple cost structure by using continuous functions to approximate the behavior of the system, then minimizing the cost by the methods of elementary calculus.
In this paper, a model of a transit system is built in polar coordinates with radial transit lines in order to find the line positions and headways which minimize user (travel time) and transit agency (operating) costs in response to a general population density function. It is found that the optimum line location is related to the population density and the circumferential access. The optimum headway is found to be that which causes user waiting time cost to equal the operating cost. The simplification of a population density function varying only radially is introduced. A method for determining the optimum number of lines is developed. This number depends upon the ratio of the access cost to the sum of the waiting and operating costs. It is proven that, for optimality, lines should be located in the centers of corridors of uniform width and have equal headways. A fleet size constraint is also introduced for the simplified case. It is proven that for optimality, the fleet is divided equally between lines.
The paper presents a technique for determining headways for transit routes, which is the first task in the overall scheduling procedure. Based on an optimization approach, a chance constrained programming model is developed. The scope of using vehicles of different sizes and operating costs is built into the model, which attempts to minimize the total operating cost. The uncertainty associated with demand forecasts is expressed as a chance constraint that specifies the desired level of reliability with respect to the satisfaction of demand. The model also includes a constraint related to the management policy regarding the minimum service to be provided on a transit route. The deterministic equivalent of the model is solved by linear programming and its application is demonstrated with an example problem.This report was prepared as part of a program of Research and Training in Urban Transportation at Marquette University sponsored by the Urban Mass Transportation Administration of the U.S. Department of Transportation. The results and views expressed are not necessarily concurred in by the sponsoring agency.
The problem of finding the best fixed routes for node oriented transit systems is used for an initial implementation and evaluation of a man-machine interactive problem solving system. The interactive graphic system enables a planner/analyst to effectively search for and evaluate a large number of alternative designs in a short period of time. This evaluation is based on a modal split model which predicts the system utilization and cost consequences of each alternative design. The model performs a detailed analysis of the components of the trip of each potential trip maker by the alternative modes of travel by transit or private automobile and it is based on values reflecting the average trip makers perception of disutility of the various trip components.After a conceptual discussion of the problem, the interactive graphic problem solving environment and the model underlying the prediction process, the mechanics of the actual implemented system are described, both in terms of computer hardware and software features. The use of the system is then illustrated with a hypothetical problem situation and the ability of the interactive process to assist the resolution of conflicting objectives and to help a policy making body to reach compromises after a value-oriented discussion. Finally, the paper discusses some issues raised in the prototype analysis relative to (1) the role and performance of the human in the interactive process, (2) alternative solution generation schemes and (3) model calibration.
In this paper, a model of a transit system is built in order to find for parallel lines in a rectangular city the lengths, positions, and headways which minimize user (travel time) and operating costs in response to a general population density function and differing line speeds. It is found that, at some point, low speed lines should be cut off, this point depending upon the relative positions, headways and speeds of adjacent lines. Further, it is found that the optimum position depends upon the tributary population and the changes in operating costs due to changes in line position. The optimum headway depends upon the tributary population, the operating cost and the change in operating cost due to changes in headway.Simplifying the problem by assuming a uniform population density, it is found that the optimum headway depends upon the average headway and the deviations of the reciprocal speed from the average reciprocal speed. Furthermore, if the fleet size is constrained, the optimum headway depends not only on these, but also on the variance of the headway and the covariance of the headway and reciprocal speed among the lines.
It is assumed that the number of buses to be operated during the various periods of the day, which is the primary factor determining costs, has already been determined and is a problem constraint. The method determines the frequencies on each route but no attempt at scheduling is made. The city is divided into zones and the number of journeys to be made by the public between each pair of zones is a data input expressed in matrix form. The objective function, to be minimized, is the sum of the journey time (which includes allowance for transfer times) plus discomfort penalties proportional to the number of passengers who cannot find seats.The planning method has two phases. In the first, desirable routes, which may be added to an initial set of routes, are generated; and routes, which may be deleted from the augmented set of routes, are pointed out. The routes to be added are selected from a set of candidate routes each of which is based on a route skeleton consisting of four zones with the extremes restricted to a set of terminal zones. In the second phase, optimal frequencies for a set of routes, under the constraint of a given number of available buses, are determined by a gradient method. The optimal value of the objective function in the second phase serves as a more accurate evaluator of a generated set of routes.Fortran programs implementing the two phases have been run for the Haifa area which was represented by 41 zones. The route determining algorithm produces a set of routes in 3 min C.P.U. on an I.B.M. . The frequency program effectively minimized the objective function for 20 routes in 15 min run time on an I.B.M. .There is strong evidence that the programs provide useful results and they appear to be useful planning tools.
Thesis (Ph.D.)--University of Washington, 1971. Includes bibliography.
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- O ' Brien
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