Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time

Bai, Yun; Hu, Qianyun; Ho, Т.K.; Guo, Haiyang; Mao, Baohua

doi:10.1109/tits.2019.2954895

Cited by 17 publications

(12 citation statements)

References 35 publications

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“…The departure efficiency of the five connection areas is selected as the primary index layer. The SP, WT and DT, as the indicators we collected for passenger comfort [55,56], are selected as the secondary index layer. The passenger departure evaluation index system is shown in Table 5.…”

Section: Plos Onementioning

confidence: 99%

Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model

et al. 2022

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Evaluation of the passenger departure efficiency of a comprehensive transport hub is essential for traffic managers. Through the evaluation, security risks in the hub can be found in time to ensure the safe departure of passengers. The attention of existing studies has focused on the analysis of the overall situation of the hub, and the quantitative description of departure status in different connection areas inside the hub is insufficient. In this study, a multilayer hybrid model based on an analytic hierarchy process and entropy weight method was established. The data collected using Wi-Fi probe technology were clustered by a K-means algorithm. The first level of the model was divided according to the connection areas of the passenger hub, and the second level was based on the number of stranded people, wait time and departure time in each connection area. It was found that the SP index has the greatest impact on departure efficiency. In addition, the impact of passenger flow aggregation on each connection area is different, and the management department should treat it accordingly. The applicability of the proposed multilayer hybrid model was verified in the example of the Chongqing north railway station.

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Section: Plos Onementioning

confidence: 99%

Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model

et al. 2022

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“…Crowd prediction algorithms for transport applications can be classified on the basis of the prediction horizon into short-term (less than 60 minutes) and long-term ones [67]. Moreover, they can be classified, on the basis of the prediction methodology, into model-based methods or data-driven ones.…”

Section: A Crowd Predictionmentioning

confidence: 99%

“…In [67] a timetable optimization method aimed at reducing the passenger waiting time (PWT) in metro scenarios is proposed, employing a Genetic Algorithm (GA) integrated with the Interior-Point Algorithm (IPA). The proposed method is tested by simulation on data of the Bejing Metro, showing that the PWT under the optimized timetable is reduced at best by 17.18 % in off-peak hour and 3.22 % in peak hour in comparison with the standard timetable.…”

Section: B Crowd Controlmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena¹,

Gelli²,

Iudice³

et al. 2022

Preprint

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<p>Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.</p>

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“…The adoption of an iterative process alone may not be sufficient because the TTP is a non-deterministic polynomialtime (NP)-hard problem for which an exact global optimum is hard to find [18]. Many methods have been proposed to solve this problem, including genetic algorithm [28]- [31], Lagrangian duality theory [32], alternating direction method of multipliers algorithm [33], and decomposition approach (DA) [34]- [36]. The DA has been widely adopted to solve TTPs because it can handle complex problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (31) requires that if n is not scheduled, no track is assigned to n; whereas if n is scheduled, one track is assigned to n. In addition, if n stops at s, a track equipped with a platform must be assigned to n.…”

Section: ; Xu Et Al 2018)mentioning

confidence: 99%

A Schedule-Based Model for Passenger-Oriented Train Planning With Operating Cost and Capacity Constraints

Xie

Shou-yi

Wong

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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In the planning stage, train operators design timetables to serve passenger trips and a train circulation plan to support these timetables. These designs consider not only operating costs but also passenger convenience. In this study, we developed an optimization model for a new problem that focuses on timetabling and train-unit scheduling while also considering passenger itinerary choices in a schedule-based train system. This optimization model minimizes passenger travel costs within the constraints of a limited budget available for operating costs. The model is solved by an iterative heuristic that simulates the interaction between train operations and passenger itinerary choices. The heuristic solves the timetabling and train-unit scheduling problem using a decomposition approach to increase computational efficiency, while passenger loading is solved by a user-equilibrium passenger assignment model. An example based on the high-speed railway network in southern China was used to demonstrate the effectiveness of the proposed model and method.

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Timetable Optimization for Metro Lines Connecting to Intercity Railway Stations to Minimize Passenger Waiting Time

Cited by 17 publications

References 35 publications

Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model

Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

A Schedule-Based Model for Passenger-Oriented Train Planning With Operating Cost and Capacity Constraints

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