Spatial-Temporal Correlation Prediction Modeling of Origin-Destination Passenger Flow Under Urban Rail Transit Emergency Conditions

Li, Chen; Huang, Jian; Wang, Bo; Zhou, Yiren; Bai, Yunyun; Chen, Yanyan

doi:10.1109/access.2019.2951604

Cited by 12 publications

(4 citation statements)

References 27 publications

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“…In Section VII, we explain the determination of w k based on a survey. It should be aware that although the work presented in this paper determine the parameters for the individual choice model and aggregation based on the survey data, the data from automatic fare collection (AFC) can be used to assist the model development [51].…”

Section: B Aggregated Travel Demandmentioning

confidence: 99%

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Yang

Lai

et al. 2020

IEEE Access

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Urban subway, because of its speed and punctuality, receives considerable popularity and injects great vitality into the city's economic development. However, overcrowding frequently observed in subway carriages during peak hours potentially leads to an increase in accident risk, while there are still some spaces available in buses in some situations. Such imbalance between the two public transits, which was examined based on the load ratios reported for Beijing public transits in a map App, motives us to develop a periodic stop-skipping strategy to shift the excessive demand from subway to bus to alleviate the overloaded situations while to reduce the unwanted influence on the passengers. To achieve such bi-objectives, we propose a non-linear model with consideration of the passengers' choice under the stop-skipping operation. To avoid to exhaustively examine all stop patterns, the stop patterns required to evaluate are identified theoretically. We develop a genetic algorithm to generate the optimal plan, with the triggering mechanism devised to give the priority to the safety objective. With the calibrated choice model, four sets of numerical experiments were performed to evaluate the proposed approach. The results indicate that our approach can effectively alleviate the overcrowding while the efficiency can be increased in some circumstances as the remaining bus capacity is utilized. The optimality and the efficiency of the algorithm and the effectiveness of the triggering mechanism were also verified. The proposed approach can be applied as an effective and economical way to rebalance the peak demand when the bus capacity is surplus.

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Section: B Aggregated Travel Demandmentioning

confidence: 99%

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Yang

Lai

et al. 2020

IEEE Access

Self Cite

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“…Terefore, path selection probability prediction and OD demand prediction are studied as branches of research on inter-OD trafc assignment. For example, some studies have predicted the paths chosen by groups by constructing probabilistic models of path selection [23] or by matching travel time clustering to OD routes [24]; others have predicted the OD demand by constructing improved LSTM models [4,25], improved CNN models [26,27], or for emergency [28] or COVID-19 periods [29].…”

Section: Introductionmentioning

confidence: 99%

Passenger Flow Path Prediction Based on Urban Rail Transit AFC Data: An Example of Chengdu, China

Wang,

Qin,

Chen

et al. 2023

Journal of Advanced Transportation

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The development of the automatic fare collection (AFC) systems provides significant support for predicting passenger flow on urban rail transit. This paper extracts passenger travel patterns using AFC data on urban rail transit in Chengdu, China, over a one-month period. Passengers are divided into two categories based on their travel habits and data mining models, and multinomial logit (MNL) models are separately used to predict their destinations. Furthermore, a two-way search algorithm is developed to search the optimal paths between origin-destination (OD) pairs by considering interchange constraints. Start a path search through the origin point and destination point, respectively, until the shortest path is found. The maximum effectiveness of a path is measured by travel time, interchange time, and the number of interchanges between the OD pairs. Finally, the validity of the proposed passenger flow path prediction method is verified by using the AFC data of Chengdu metropolitan rail transit from April 2018.

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“…Rail-based transit systems can operate at higher speeds than buses typically used in traditional transport systems. However, urban rail transit line emergencies cause unexpected disruptions that can lead to interrupted operations and passenger delays [1][2][3]. A variety of random events ranging from train malfunctions to bomb threats and power failures can cause unexpected service disruptions of varying degrees.…”

Section: Introductionmentioning

confidence: 99%

Transit-Based Evacuation for Urban Rail Transit Line Emergency

Hou

Cao

Lv³

et al. 2020

Sustainability

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Urban rail systems are the backbone of urban transit networks and are characterized by large passenger volumes, high speeds, punctuality, and low environmental impacts. However, unforeseen events such as rail transit line emergencies can lead to unexpected costs and delays. As a means of disruption management, we divide the decision support system for urban rail transit line emergency situations into two stages—transit-based evacuation and bus bridging management. This paper focuses on the transit-based evacuation under emergency scenarios on a single rail line. The model determines the vehicles and routes within traditional transit systems required to evacuate stranded passengers within a given time window. In addition, the proposed method ensures the reliability of traditional transit systems by considering the operating fleet and reserve fleet in the traditional transit systems. Therefore, the proposed optimization model is established with the objective of maximizing the total number of stranded passengers transferred within the given time window and headway constraint. Herein, we present the optimization model and solution method, and the proposed method is validated. The effectiveness of the proposed control method is evaluated in the Changchun urban transit network. By analyzing stranded passengers at stations under different numbers of vehicles and time periods, the results show that the proposed model can significantly provide routing arrangements to maximize the number of passengers evacuated from stations. The results are useful in the development of emergency evacuation plans to prevent secondary accidents and evacuate stranded passengers during a rail transit line emergency.

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Spatial-Temporal Correlation Prediction Modeling of Origin-Destination Passenger Flow Under Urban Rail Transit Emergency Conditions

Cited by 12 publications

References 27 publications

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Rebalancing the Passenger Flow Between Subways and Buses: A Periodic Stop-Skipping Strategy

Passenger Flow Path Prediction Based on Urban Rail Transit AFC Data: An Example of Chengdu, China

Transit-Based Evacuation for Urban Rail Transit Line Emergency

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