Real-Time Integrated Limited-Stop and Short-Turning Bus Control with Stochastic Travel Time

Zhang, Hu; Zhao, Shengchuan; Cao, Yang; Liu, Huasheng; Liang, Shidong

doi:10.1155/2017/2960728

Cited by 22 publications

(20 citation statements)

References 16 publications

(16 reference statements)

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“…Equation 40is to ensure that passengers in the same bus have common time window at the transit hub. Equation (41) constrains that every type P passenger(type D passenger) should be collected (distributed) within their own time windows. Equation (42) guarantees that the in-vehicle time of passengers no longer than their maximum ride time.…”

Section: B Constraintsmentioning

confidence: 99%

“…Besides, to authors' knowledge, no research has discussed the elasticity of DRC operation plan, where unforeseen delay often occurs because of some stochastic factors. In the area of traditional bus operation, the robustness of operation plan has received more and more attention to increase service regularity [41], [42] however. In addition, researchers usually prefer not to optimize the number of vehicles considering the low demand level of DRC.…”

Section: Introductionmentioning

confidence: 99%

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Compatibility-Based Approach for Routing and Scheduling the Demand Responsive Connector

2020

IEEE Access

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This study concentrates on the routing and scheduling problem of Demand Responsive Connector to build feeder plans for people traveling from and to transit hub. An in-depth analysis on the characteristics of feeder services was implemented to inspire the compatibility-based algorithm design. With the goal of reducing operating cost and passenger inconvenience, the proposed algorithm took several factors critical to the real-word operation into consideration, such as double time window assurance (the time constraints at the beginning and end of passenger travels), the flexibility of feeder plans, and the number of vehicles. Our method was validated on numerical instances of 400, 600, 800 and 1000 passengers. Simulation results show that the compatibility-based algorithm can effectively reduce the number of vehicles with acceptable increase of passengers' inconvenience, and can improve the algorithm efficiency considerably. In addition, the setting of flexible time window of shutter plan can hold some elasticity for feeder services. Sensitivity analysis was conducted to help service providers evaluate the trade-off between the operation cost and level of service. INDEX TERMS Compatibility-based approach, demand responsive connector, routing and scheduling.

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Section: B Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Compatibility-Based Approach for Routing and Scheduling the Demand Responsive Connector

2020

IEEE Access

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“…e information required included origin-destination (O-D) demand matrix, distances between stations, headways, and maximum link speeds. Under those operational stopping strategies, a subset of the stops which were skipped would be selected and passengers' travel time and buses' running time could be shortened [4][5][6][7][8][13][14][15]. Chen et al [9] used a hybrid artificial bee colony (ABC) and Monte Carlo method to solve the optimal stopping strategy, considering the effect of vehicle capacity and stochastic travel time on actual operation.…”

Section: Introductionmentioning

confidence: 99%

“…Chen et al [9] used a hybrid artificial bee colony (ABC) and Monte Carlo method to solve the optimal stopping strategy, considering the effect of vehicle capacity and stochastic travel time on actual operation. Instead of designing stop-skipping service in tactical planning, a rolling time horizon approach was adopted to achieve real-time optimization [10][11][12][13][14][15][16]. Specifically, Ould Sidi et al [17] proposed a multi-objective optimization approach to determine the dynamic stopping pattern and the departure time when a disruption occurred.…”

Section: Introductionmentioning

confidence: 99%

Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints

Mou

Zhang

Liang

2020

Journal of Advanced Transportation

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In a bus line with high passenger demand, the stop-skipping operation can benefit both users and operators as well as improve the service level of bus line, but it usually cannot be effectively adopted by operators because of the unordered operation of buses and the discomfort of waiting passenger at stops. Therefore, the stop-skipping operation requires higher reliability for stop serving. This paper proposes a reliable stop-skipping service design with holding strategy by taking into account bus capacity constraints. Under a stop-skipping service, the holding strategy is used to balance the interval of stop serving rather than the headway of buses. Meanwhile, to reflect the actual boarding process of waiting passengers, the number of left-over passengers and the waiting time are calculated during serving time and holding time, respectively. The objective function is to minimize the total costs of bus operation system. Besides, a Genetic Algorithm combined with Monte Carlo Simulation method is defined and implemented to solve the reliability optimization model. Finally, a numerical example based on a bus route in Changchun city is carried out to test the reliability optimization model. Results showed that the reliability optimization strategy can improve the stability of stop service and then save cost of passengers’ travel time.

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“…Ibarra-Rojas et al [1] provided an excellent summary of the previous work on realtime headway control strategies. In terms of spatial configuration, different control strategies can be classified into two categories: station control, including holding strategies [2][3][4] and stop-skipping strategies [5][6][7], and interstation control, including bus speed regulation strategies [8] and traffic signal priority strategies [9][10][11]. In addition, two control methods can be integrated to regulate bus headways or optimize operations of public transport systems [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimal Formulations for Bus Fleet Size of Public Transit under Headway-Based Holding Control

Liang

2019

Journal of Advanced Transportation

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In recent years, with the development of advanced technologies for data collection, real-time bus control strategies have been implemented to improve the daily operation of transit systems, especially headway-based holding control which is a proven strategy to reduce bus bunching and improve service reliability for high-frequency bus routes, with the concept of regulating headways between successive buses. This hot topic has inspired the reconsideration of the traditional issue of fleet size optimization and the integrated bus holding control strategy. The traditional headway-based control method only focused on the regulation of bus headways, without considering the number of buses on the route. The number of buses is usually assumed as a given in advance and the task of the control method is to regulate the headways between successive buses. They did not consider the bus fleet size problem integrated with headway-based holding control method. Therefore, this work has presented a set of optimal control formulations to minimize the costs for the passengers and the bus company through calculating the optimal number of buses and the dynamic holding time, taking into account the randomness of passenger arrivals. A set of equations were formulated to obtain the operation of the buses with headway-based holding control or the schedule-based control method. The objective was to minimize the total cost for the passengers and the bus company in the system, and a Monte Carlo simulation based solution method was subsequently designed to solve the optimization model. The effects of this optimization method were tested under different operational settings. A comparison of the total costs was conducted between the headway-based holding control and the schedule-based holding control. It was found that the model was capable of reducing the costs of the bus company and passengers through utilizing headway-based bus holding control combined with optimization of the bus fleet size. The proposed optimization model could minimize the number of buses on the route for a guaranteed service level, alleviating the problem of redundant bus fleet sizes caused by bus bunching in the traditional schedule-based control method.

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Real-Time Integrated Limited-Stop and Short-Turning Bus Control with Stochastic Travel Time

Cited by 22 publications

References 16 publications

Compatibility-Based Approach for Routing and Scheduling the Demand Responsive Connector

Compatibility-Based Approach for Routing and Scheduling the Demand Responsive Connector

Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints

Multiobjective Optimal Formulations for Bus Fleet Size of Public Transit under Headway-Based Holding Control

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