Effects of increased traffic volume and speed heterogeneity on the capacity of a railway with dense mixed traffic

Warg, Jennifer

doi:10.2495/cr120411

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…Literature [1] studied the impact of mixed operations on the carrying capacity of high-speed railways and concluded that trains with different speeds operating on the same signal display system would increase the train headway and reduce the line capacity. Literature [2][3][4] proposed that the increase in traffic volume and speed difference not only leads to a decrease in schedule flexibility and reliability but also makes the system sensitive to interruptions, with speed combinations having the most impact on high-density railway lines. Studies in the literature [5][6] show that when the speed difference between trains does not exceed 50 km/h and the proportion of low-speed trains running is about 90%, the impact on the line carrying capacity is minimal.…”

Section: Introductionmentioning

confidence: 99%

Impact of block section length on the headway of mixed speed trains in high-speed railway

Yang¹,

Zhou²,

Zhang³

et al. 2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

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Train mixed operation refers to the trains with different speeds running on the same line, such as CTCS-3 mixed-running line, which operates both CTCS-3 and CTCS-2 trains. Existing studies have shown that train speed differences increase the tracking interval time (headway) between trains, reducing the line carrying capacity. At present, much research has been conducted on the impact of train speed differences and the ratio of trains with different speeds on the carrying capacity of the mixed-running line from the standpoints of transportation organization and traffic scheduling. As an important component of the rail transit system, the train control system has a significant impact on the rail transit system's safety and efficiency. By constructing a cellular automata model for mixed speed trains under the fixed block system, this study analyzed the effect of different block section lengths on the headway of mixed speed trains in the same line. On this basis, the dynamic block section method was proposed in this work to shorten the headway between mixed speed trains. The study quantifies the effect of block section length on the headway of mixed speed trains, which can serve as a theoretical foundation for expanding the capacity of existing high-speed railway lines.

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Section: Introductionmentioning

confidence: 99%

Impact of block section length on the headway of mixed speed trains in high-speed railway

Yang¹,

Zhou²,

Zhang³

et al. 2023

International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023)

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“…Delays encountered in railway systems can be categorized as either primary or secondary delays. Warg et al [3] defines Primary delays as the types of delays affecting a particular train schedule and those delays are not as a result of malfunction of other trains using the line. Whereas secondary delays are defined as the delays caused by earlier delays of other trains within the network sharing the same infrastructures, passenger transfers, transfers and reallocation of crew and rolling stock connections among others.…”

Section: Introductionmentioning

confidence: 99%

Optimized Train Dispatching and Rescheduling During a Disruption in a Bottleneck Section

Byegon

Bisrat

Gashaw

2022

Preprint

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Railway transportation is nowadays becoming one of the most preferred mode of transport due to its safety, capacity and reliability; the capital cost for the construction of the railway infrastructure is however very high and is characterized by high rigidity as the track layout is fixed; therefore there is need to optimally use the available infrastructure. Minor delays arising from a simple disruptions or even a single train failure can have massive impacts in terms of overall delays for subsequent trains using the track facility if not solved amicably. Disruptions can be attributed to power outages, mechanical failures, derailments, accidents or even environmental factors. In a case of multiple uncertain perturbations happening in a busy complex railway network, where there are many trains requesting to use the available track resources concurrently, there will be massive delays which has a lot of negative operational and economic implications as well as passengers’ dissatisfaction. A mathematical model that is; a mixed-integer linear programming formulation is modelled to minimize total time delays in case of a set of multiple disruptions occurring on a busy track section i.e. bottleneck section, the model is formulated with consideration of sets of constraints factoring in feasible routes and safety margins and other operational dynamics such as dwell times to achieve optimal use of the available infrastructure. A number of numerical experiments based on arbitrary data and real network data are carried out to verify the effectiveness and efficiency of the proposed model. Performance of the designed model is evaluated and results are validated, the results obtained shows that the model offers an efficient rescheduled trains operation plan during disruptions, furthermore the performance of Fmincon solver and genetic algorithms (GA) are compared and their robustness evaluated, GA shows better performance during multiple disruption scenario.

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“…In Turkey, sharing High Speed Train (HST) infrastructure with both freight and passenger trains is advised; it is believed to be practical and economically efficient, especially for transporting small cargo and postal mail using HSTs (Ertem and Özcan, 2016). Warg (2012) indicated that there are requirements for increasing the maximum speed of HST and adding more new regional stops for flexibility in Sweden. Ramaraju (2013) stated that train speed and capacity are critical problems in India because of challenges associated with track sharing between passenger and freight trains.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Dynamic Behavior of Track Transitions Along Shared Track Corridors

Hou²,

Mishra

et al. 2021

Front. Built Environ.

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This paper presents findings from an analytical modeling effort undertaken to study the dynamic response of track transitions along shared-track corridors. A recently developed train-track-bridge model was used for this purpose. First, the model predictions are verified using field instrumentation data as well as data from other published literatures. Subsequently, the model is used to analyze the dynamic response of a typical bridge approach under the passage of a high-speed passenger train as well as six different freight trains comprising different freight car types. A speed sensitivity analysis of a freight train comprising one specific freight car type is also carried out. Geometric configuration of different freight trains is assessed as well as weight and speed of operation. Different track response parameters, including vertical displacement and rail-tie reaction force, are considered to highlight the differences in the track dynamic behavior under freight and passenger train loading. Analyses in both time and frequency domains illustrate the difference in track behavior under freight and passenger train loading. The significance of gap development at the tie-ballast interface near track transitions has been emphasized by illustrating the effect of tie gap on the dynamic track behavior. The paper concludes by emphasizing the importance of special consideration to track dynamic behavior for shared-track corridors.

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Effects of increased traffic volume and speed heterogeneity on the capacity of a railway with dense mixed traffic

Cited by 6 publications

References 4 publications

Impact of block section length on the headway of mixed speed trains in high-speed railway

Impact of block section length on the headway of mixed speed trains in high-speed railway

Optimized Train Dispatching and Rescheduling During a Disruption in a Bottleneck Section

Modeling the Dynamic Behavior of Track Transitions Along Shared Track Corridors

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