The efficiency of a transport system depends on several elements, such as available technology, governmental policies, the planning process, and control strategies. Indeed, the interaction between these elements is quite complex, leading to intractable decision making problems. The planning process and real-time control strategies have been widely studied in recent years, and there are several practical implementations with promising results. In this paper, we review the literature on Transit Network Planning problems and real-time control strategies suitable to bus transport systems. Our goal is to present a comprehensive review, emphasizing recent studies as well as works not addressed in previous reviews.

Planning, operation, and control of bus transport systems: A literature review

Synchronizing different lines at common stops can increase the level of service in transit systems, particularly for different lines in overlapping route segments or common stops (e.g. branching lines and limited-stop lines). In this study, we propose a measure of synchronization that penalizes the deviation from proposed arrivals' separation times of different lines at common stops. Then, we define two optimization problems that maximize the proposed measure considering bus speeds that dependents on the departure times. We implement a commercial solver and a Genetic Algorithm to obtain good quality solutions in short time for randomly generated instances. Finally, we implement our optimization approach for two branching lines of Redbus Urbano, an agency in Santiago, Chile. Numerical results show that it is possible to properly separate arrivals of different lines at common stops which benefits to passengers who may use more than one line.

Synchronizing different transit lines at common stops considering travel time variability along the day

This study proposes a solution to the feeder bus timetabling problem, in which the terminal departure times and vehicle sizes are simultaneously determined based on the given transfer passengers an...

Feeder Bus Timetable Design and Vehicle Size Setting in Peak Hour Demand Conditions

In this paper, we present a multi-objective simulation-based headway optimization for complex urban mass rapid transit systems. Real-world applications often confront conflicting goals of cost versus service level. We propose a two-phase algorithm that combines the single-objective covariance matrix adaptation evolution strategy with a problem-specific multi-directional local search. With a computational study, we compare our proposed method against both a multi-objective covariance matrix adaptation evolution strategy and a non-dominated sorting genetic algorithm. The integrated discrete event simulation model has several stochastic elements. Fluctuating demand (i.e., creation of passengers) is driven by hourly origin-destination-matrices based on mobile phone and infrared count data. We also consider the passenger distribution along waiting platforms and within vehicles. Our two-phase optimization scheme outperforms the comparative approaches, in terms of both spread and the accuracy of the resulting Pareto front approximation.

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Multi-objective simulation optimization for complex urban mass rapid transit systems

In this paper, we present a simulation-based headway optimization for urban mass rapid transit networks. The underlying discrete event simulation model contains several stochastic elements, including time-dependent demand and turning maneuver times as well as direction-dependent vehicle travel and passenger transfer times. Passenger creation is a Poisson process that uses hourly origin–destination-matrices based on anonymous mobile phone and infrared count data. The numbers of passengers on platforms and within vehicles are subject to capacity restrictions. As a microscopic element, passenger distribution along platforms and within vehicles is considered. The bi-objective problem, involving cost reduction and service level improvement, is transformed into a single-objective optimization problem by normalization and scalarization. Population-based evolutionary algorithms and different solution encoding variants are applied. Computational experience is gained from test instances based on real-world data (i.e., the Viennese subway network). A covariance matrix adaptation evolution strategy performs best in most cases, and a newly developed encoding helps accelerate the optimization process by producing better short-term results.

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Population-based simulation optimization for urban mass rapid transit networks

The coordination between bus rapid transit (BRT) and feeder bus service is helpful in improving the operational efficiency and service level of urban public transport system. Therefore, a coordinated operation model of BRT and bus is intended to develop in this paper. The total costs are formulated and optimized by genetic algorithm. Moreover, the skip-stop BRT operation is considered when building the coordinated operation model. A case of the existing bus network in Beijing is studied, the proposed coordinated operation model of BRT and bus is applied, and the optimized headway and costs are obtained. The results show that the coordinated operation model could effectively decrease the total costs of the transit system and the transfer time of passengers. The results also suggest that the coordination between the skip-stop BRT and bus during peak hour is more effective than non-coordination operation.

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Rui Song

Papers

Modeling the Coordinated Operation between Bus Rapid Transit and Bus