Total Travel Time Of Passengers Research Articles

Comprehensive optimization of urban rail transit timetable by minimizing total travel times under time-dependent passenger demand and congested conditions

The comprehensive optimization of the timetables of urban rail transit systems under more realistic conditions is essential for their practical operation. Currently, most time-dependent timetabling models do not adequately consider train capacity and variable operation parameters. To bridge this gap, this study mainly investigates the timetable design problem of the urban rail transit system so as to adapt to time-dependent passenger demand under congested conditions by considering the variable number of trains, train running time, and train dwell time. Two nonlinear non-convex programming models are formulated to design timetables with the objective of minimizing the total passenger travel time (TTT) under the constraints of train operations, and passenger boarding and alighting processes. The difference between the two models is that one is a train-capacity unconstrained model and the other is a train-capacity constrained model. The proposed models are examined through real-world cases solved by the adaptive large neighborhood search algorithm. The results show that the first model can minimize passenger TTT under dynamic passenger demand, whereas the second can comprehensively optimize passenger TTT and meantime keep the train load factor within a reasonable level. Accordingly, it is concluded that the proposed models are more realistic.

Environmental impacts of public transport systems using real-time control method

Public Transport (PT) systems rely more and more on online information extracted from both operator’s intelligent equipment and user’s smartphone applications. This allows for a better fit between supply and demand of the multimodal PT system, especially through the use of PT real-time control actions/tactics. In doing so there is also an opportunity to consider environmental-related issues to approach energy saving and reduced pollution. This study investigates and analyses the benefits of using real-time PT operational tactics in reducing the undesirable environmental impacts. A tactic-based control (TBC) optimization model is used to minimize total passenger travel time and maximize direct transfers (without waiting). The model consists of a control policy built upon a combination of three tactics: holding, skip-stops, and boarding limit. The environmental-related measure is the global warming potential (GWP) using the life cycle assessment technique. The methodology developed is applied to a real life case study in Auckland, New Zealand. Results show that TBC could reduce the GWP by means of reduction of total passenger travel times and vehicle travel cycle time. That is, the TBC model results in a 5.6% reduction in total GWP per day compared with an existing no-tactic scenario. This study supports the use of real-time control actions to maintain a reliable PT service, reducing greenhouse gas emissions and subsequently moving towards greener PT systems.

Setting services in public transit lines in short time periods under time-varying demand

Abstract: This paper focuses on a mathematical programming based model for setting the schedule of a given number of services on a public transportation network. The structure of the model is that of a time-expanded or diachronic network, where origin to destination flows vary dynamically over a short time horizon (several hours) and are assumed to be known deterministically. The model basically aims to minimize the total travel time of passengers during the time horizon by properly setting the lag times between services on the lines and thereby accommodating conveniently the schedules of the services on different lines in order to enhance transfers. Two different types of diachronic networks are considered, in which three basic algorithmic alternatives have been tested: a heuristic method based on the classical projected gradient, Benders decomposition, and a combination of both. Among other applications, the model can potentially be applied in operational aspects for disruption recovery in Rail-Rapid Transit and Suburban Railway systems by using bus shuttles or auxiliary bus lines. The computational viability of the model, in terms of adequate response time, is shown using test networks of auxiliary bus lines. Its computational performance in readjusting schedules for larger suburban rail systems is also evaluated.

Real-Time Public Transport Operations: Library of Control Strategies

Modern public transport (PT) operations have evolved into a complex multimodal system in which small-scale disorder can propagate. Large-scale disruptions to passengers and PT agencies result. Various studies have been developed to model PT control at the operational level; however, the main downside of possible real-time control actions is the lack of intelligent modeling and a systematic process that can activate such actions immediately. This study presents a real-time control procedure to increase service reliability and to improve successful coordinated transfers in a complex PT system. The developed method aims at minimizing total travel time for passengers and reducing the uncertainty of meetings between PT vehicles. A library of operational tactics is first built to serve as a basis of the real-time decision-making process. The methodology developed is applied to a real-life case study in Auckland, New Zealand. The results showed improvements in system performance and confirmed the use of real-time control actions to maintain reliable PT service.

Reducing the passenger travel time in practice by the automated construction of a robust railway timetable

Automatically generating timetables has been an active research area for some time, but the application of this research in practice has been limited. We believe this is due to two reasons. Firstly, some of the models in the literature impose artificial upper bounds on time supplements. This causes a high risk of generating infeasibilities. Secondly, some models that leave out these upper bounds often generate solutions that contain some very large time supplements because these supplements are not penalised in the objective function. The reason is that these objective functions often do not completely correspond to the true goal of a timetable. We solve both problems by minimising our objective function: total passenger travel time, expected in practice. Since this function evaluates and indirectly steers all time related decision variables in the system, we do not need to further restrict the ranges of any of these variables. As a result, our model does not suffer from infeasibilities generated by such artificial upper bounds for supplements.Furthermore, some measures are taken to significantly speed up the solver times of our model. These combined features result in our model being solved more quickly than previous models. As a result, our method can be used for timetabling in practice. We demonstrate our claims by optimising, in about two hours only, the timetable of all 196 hourly passenger trains in Belgium. Assuming primary delay-distributions with an average of 2% on the minima of each activity, the optimised timetable reduces expected passenger time in practice, as evaluated on the macroscopic level, by 3.8% during peak hours. This paper demonstrates that we added two important missing steps to make cyclic timetabling for passengers really useable in practice: (i) the addition of the objective function of expected passenger time in practice and (ii) the reduction of computation time by addition of well chosen additional constraints.

Optimization of Urban Single-line Metro Timetable for Total Passenger Travel Time under Dynamic Passenger Demand

This paper studies the optimization of an urban single-line metro timetable for total passenger travel time adapted to dynamic passenger demand, which arises in an urban metro service and is a common problem in major cities. After analyzing the components of the total passenger travel time, a model is presented with the aim of minimizing total passenger travel time. An S-pattern function is proposed to represent the cumulative demand function for each pair of origin and destination in an urban single-line metro. Furthermore, a spatial branch and bound algorithm that is applicable to the model is presented. The advantages of designing a timetable that optimizes the total passenger travel time adapted to dynamic passenger demand are depicted through extensive computational experiments on several cases derived from a real urban single-line metro. An extensive computational comparison of a regular timetable, a timetable optimizing average waiting time, and a timetable optimizing total passenger travel time timetable are performed.

A Self-Adjusting Method to Resist Bus Bunching Based on Boarding Limits

Bus bunching is one of the most serious problems of urban bus systems. Bus bunching increases waiting and travel time of passengers. Many bus systems use schedules to reach equal headways. Compared to the idea of schedules and the target headway introduced later, we propose a new method to improve the efficiency of a bus system and avoid bus bunching by boarding limits. Our solution can be effectively implemented when buses cannot travel as planned because of bad road conditions and dynamic demands at bus stops. Besides, using our method, bus headways reach the state with equal headways dynamically and spontaneously without drivers’ explicit intervention. Moreover, the method can improve the level of the bus service and reduce total travel time of passengers. We verify our method using an ideal bus route and a real bus route, both showing the success of the proposed method.

Efficient Real-Time Train Scheduling for Urban Rail Transit Systems Using Iterative Convex Programming

The real-time train scheduling problem for urban rail transit systems is considered with the aim of minimizing the total travel time of passengers and the energy consumption of the operation of trains. Based on the passenger demand in the urban rail transit system, the optimal departure times, running times, and dwell times are obtained by solving the scheduling problem. A new iterative convex programming (ICP) approach is proposed to solve the train scheduling problem. The performance of the ICP approach is compared with other alternative approaches, i.e., nonlinear programming approaches, a mixed-integer nonlinear programming (MINLP) approach, and a mixed-integer linear programming (MILP) approach. In addition, this paper formulates the real-time train scheduling problem with stop-skipping and shows how to solve it using an MINLP approach and an MILP approach. The ICP approach is shown, via a case study, to provide a better tradeoff between performance and computational complexity for the real-time train scheduling problem. Furthermore, for the train scheduling problem with stop-skipping, the MINLP approach turns out to have a good tradeoff between the control performance and the computational efficiency.

Improved reliability of public transportation using real-time transfer synchronization

Service reliability of public transportation (PT) systems is a dominant ingredient in what is perceived as the PT image. Unreliable service increases the uncertainties of simultaneous arrivals of vehicles at a transfer point. Implementing proper control actions leads to preventing missed transfers, one of the undesirable features of PT service and a major contributor to a negative image. The present work focuses on performance measurements of a PT system offering direct transfers on multi-legged trips. The method developed evaluates and improves system performance by applying selected operational tactics in real-time scenarios. In order to investigate the efficiency level of the PT system, five types of vehicle positional situations with reference to a transfer point are considered: considerably ahead of schedule, ahead of schedule, on schedule, behind schedule, and considerably behind schedule. Each situation contributes differently to the degree of system performance. The optimization framework developed results in selected operational tactics to attain the maximum number of direct (without waiting) transfers and minimize total passenger travel time. The implementation of the concept is performed in two steps: optimization and simulation. The optimization process searches for the best operational tactics, using the states of the five vehicle-position types, and the simulation serves to validate the optimal results under a stochastic framework using the concept of a multi-agent system. A case study of Auckland, New Zealand, is described for assessing the methodology developed. Results showed a 58% improvement in the system performance index compared to no-tactic operations.

Integrating the Bus Vehicle Class Into the Cell Transmission Model

The traditional cell transmission model (CTM), a well-known dynamic traffic simulation method, does not cater to the presence of moving bottlenecks, which may be caused by buses traveling within a network. This may affect the dynamics of congestion that is present and may also affect route choice by all vehicles on a network. The main contribution of this paper is to provide an analytical formulation for a mixed traffic system that includes cars and buses, which realistically replicates moving bottlenecks. We modify the CTM model using methods from the lagged CTM to recognize speed differentials between the free-flow speed of buses and cars. In addition, the impact of capacity reduction caused by buses was incorporated. These developments led to the replication of moving bottlenecks caused by buses within the CTM framework. The formulated variant of CTM was utilized to determine a system optimal assignment that minimizes the total passenger travel time across cars and buses. The proposed modified CTM model, defined as the BUS-CTM, has been applied on a road link and a more detailed network to demonstrate the effectiveness of the approach. The numerical results and the depiction of the bottleneck phenomenon within the model suggests that the BUS-CTM obtains more realistic results compared with the application of the traditional CTM in a mixed car–bus transportation system. The sensitivity analysis shows that bus passenger demand, passenger occupancy of bus, and bus free-flow speeds are the key parameters that influence the system performance.

A robust, tactic-based, real-time framework for public-transport transfer synchronization

Missed transfers affect public transport (PT) operations by increasing passenger’s waiting and travel times and frustration. Because of the stochastic and uncertain nature of PT systems, synchronized transfers do not always materialize. This work proposes a new mathematical programming model to minimize total passenger travel time and maximize direct (without waiting) transfers. The model consists of four policies built on a combination of three tactics: holding, skip-stops, and short-turn, the last applied, for the first time, as a real-time control action. The concept is implemented in two steps: optimization and simulation. An agent-based simulation framework is used to represent real-life scenarios, generate random input data, and validate the optimization results. In order to assess the robustness of this framework, a wide range of schedule-deviation scenarios are defined using efficient algorithms for solving the control models within a rolling horizon structure. A case study of the Auckland, New Zealand, PT system is described for assessing the methodology developed. The results show a 4.7% reduction in total passenger travel time and a more than 150% increase in direct transfers. The best impressive results are attained under short headway operations.

A Robust, Tactic-Based, Real-Time Framework for Public- Transport Transfer Synchronization

Missed transfers affect public transport (PT) operations by increasing passenger's waiting and travel times and frustration. Because of the stochastic and uncertain nature of PT systems, synchronized transfers do not always materialize. This work proposes a new mathematical programming model to minimize total passenger travel time and maximize direct (without waiting) transfers. The model consists of four policies built on a combination of three tactics: holding, skip-stops, and short-turn, the last applied, for the first time, as a real-time control action. The concept is implemented in two steps: optimization and simulation. An agent-based simulation framework is used to represent real-life scenarios, generate random input data, and validate the optimization results. In order to assess the robustness of this framework, a wide range of schedule-deviation scenarios are defined using efficient algorithms for solving the control models within a rolling horizon structure. A case study of the Auckland, New Zealand, PT system is described for assessing the methodology developed. The results show a 4.7% reduction in total passenger travel time and a more than 150% increase in direct transfers. The best impressive results are attained under short headway operations.

Efficient Bilevel Approach for Urban Rail Transit Operation With Stop-Skipping

The train scheduling problem for urban rail transit systems is considered with the aim of minimizing the total travel time of passengers and the energy consumption of the trains. We adopt a model-based approach, where the model includes the operation of trains at the terminus and at the stations. In order to adapt the train schedule to the origin-destination-dependent passenger demand in the urban rail transit system, a stop-skipping strategy is adopted to reduce the passenger travel time and the energy consumption. An efficient bilevel optimization approach is proposed to solve this train scheduling problem, which actually is a mixed-integer nonlinear programming problem. The performance of the new efficient bilevel approach is compared with the existing bilevel approach. In addition, we also compare the stop-skipping strategy with the all-stop strategy. The comparison is performed through a case study inspired by real data from the Beijing Yizhuang line. The simulation results show that the efficient bilevel approach and the existing bilevel approach have a similar performance but the computation time of the efficient bilevel approach is around one magnitude smaller than that of the bilevel approach.

Optimal combinations of selected tactics for public-transport transfer synchronization

Handling efficiently and effectively real-time vehicle control is of major concern of public transport (PT) operators. One related problem is on how to reduce the uncertainty of simultaneous arrivals of two or more vehicles at a transfer point. Improper or lack of certain control actions leads to have missed transfers, one of the undesirable features of the PT service. Missed transfers result in increase of passenger waiting and travel times, and of passenger frustration. This work focuses on reducing the uncertainty of missed transfers by the use of control tactics in real-time operation. The developed model improves the PT service performance by optimally increasing the number of direct transfers and reducing the total passenger travel time. This model consists of two policies built upon a combination of two tactics: holding and skip-stop/segment, where a segment is a group of stops. The implementation of the concept is performed in two steps: optimization and simulation. The optimization searches for the best combination of operational tactics. The simulation serves as a validation of the optimal results under a stochastic framework. A case in Auckland, New Zealand is used. The results show that by applying the holding-skip stop, and holding-skip segment tactics the number of direct transfers are increased by about 100% and 150%, and the total passenger travel time is reduced by 2.14% and 4.1%, respectively, compared with the no-tactic scenario. The holding-skip segment tactic results with 47% more direct transfers than the holding-skip stop tactic for short headway operation.

Synchronizing Public Transport Transfers by Using Intervehicle Communication Scheme

Synchronized transfers in public transport (PT) networks play an important role in reducing transfer walking time, increasing PT network connectivity, and improving PT reliability and the attractiveness of the PT service. However, because of the dynamic, stochastic, and uncertain nature of traffic, planned synchronized PT transfers do not always materialize. Missed connections frustrate the PT passengers and reduce potential new users. This research proposed an intervehicle communication (IVC)-based scheme to optimize the synchronization of planned transfers in PT networks. A semidecentralized control strategy was developed for the IVC systems to make the optimization a parallel process. Two operational tactics, changing vehicle speed and holding vehicles at transfer points, were used in the optimization with real-time vehicle speed and location information. A distance-based dynamic speed-adjustment model was developed for updating vehicle running speed under the fixed single-point encounter scenario and flexible road-segment encounter scenario. The impact of the proposed IVC scheme on the total number of direct transfers and the total passenger travel time (TPTT) was investigated with a case study of a PT network from Beijing. Results showed that by applying the proposed methodology, the number of direct transfers was considerably increased by 1,100%, and the TPTT was significantly reduced by 13.2%.

The Optimal Design Project about Bus Station Spacing in the City

Urban public transport is the main means of urban resident trip. With the rapid development of national economy, the city size is expanding, and the urban population is becoming larger and larger. However, the development of urban transportation doesnt keep up the pace of development of socio-economic. Traffic jam has become a problem to be urgent solved to some cities. This article selects No.23 bus line in Huaian as studying object, analyzes characteristics of resident trip in Huaian, By referencing the minimum total system cost model, which aims at minimizing the total passenger travel time costs and operating costs, to optimize station distance of No.23 bus line, so can improve bus running efficiency, meet the travel needs of residents better.

Joint Optimization of a Rail Transit Route and Bus Routes in a Transit Corridor

Urban transit network is mainly composed of rail transit routes and bus routes in many large cities of China. Previous studies have been made to optimal either rail transit network design or bus network design. This paper was concerned with joint optimization of a rail transit route and bus routes in a transit corridor. Firstly, a method for classifying bus routes under a given rail route transit was proposed. Then, a multi-objective model was developed for designing an integrated rail transit and bus network to maximize rail ridership and minimize total passenger travel time. An algorithm for solving the proposed model based on genetic algorithm was presented. At last, a numerical example was given. The results demonstrate feasible and effective of the proposed model and solution methodology, and show that rail ridership increases and total passenger travel time declines after optimization.

Transit Network Design: a Hybrid Enhanced Artificial Bee Colony Approach and a Case Study

A bus network design problem in a suburban area of Hong Kong is studied. The objective is to minimize the weighted sum of the number of transfers and the total travel time of passengers by restructuring bus routes and determining new frequencies. A mixed integer optimization model is developed and was solved by a Hybrid Enhanced Artificial Bee Colony algorithm (HEABC). A case study was conducted to investigate the effects of different design parameters, including the total number of bus routes available, the maximum route duration within the study area and the maximum allowable number of bus routes that originated from each terminal. The model and results are useful for improving bus service policies.

Optimal Skip-Stop Schedule under Mixed Traffic Conditions for Minimizing Travel Time of Passengers

Given the lower efficiency resulting from the overload of bus stops, the capacity and travel time of passengers influenced by skip-stop operation are analyzed under mixed traffic conditions, and the travel time models of buses and cars are developed, respectively. This paper proposes an optimization model for designing skip-stop service that can minimize the total travel time for passengers. Genetic algorithm is adopted for finding the optimal coordination of the stopping stations of overall bus lines in an urban bus corridor. In this paper, Tian-Mu-Shan Road of Hangzhou City is taken as an example. Results show that the total travel time of all travelers becomes 7.03 percent shorter after the implementation of skip-stop operation. The optimization scheme can improve the operating efficiency of the road examined.

Transfer Synchronization of Public Transport Networks

Transfers in public transport, especially in bus operations, are used to create a more efficient network by the reduction of operational costs and the allowance of more flexible route planning. However, because of the stochastic nature of traffic, scheduled transfers do not always occur; this situation increases the total passenger travel time and reduces the attractiveness of the public transport service. The use of selected operational tactics in public transport networks for increasing the actual occurrence of scheduled transfers was analyzed. A model was developed to determine the impact that instructing vehicles to either hold at or skip certain stops had on total passenger travel time and the number of simultaneous transfers. The model consisted of two components. First, a simulation of a public transport network examined the two tactics for maximizing the number of transfers. Second, an ILOG optimization model was used for optimal determination of the combination of the two tactics to achieve the maximum number of simultaneous transfers. A bus network was created as a case study, in Auckland, New Zealand, to verify the impact of the model's application. Results showed that applying online operational tactics dramatically improved the frequency of simultaneous transfers by more than 100%. The concept has great potential for increasing the efficiency and attractiveness of public transport networks that involve scheduled transfers.