scholarly journals Optimization of Urban Single-line Metro Timetable for Total Passenger Travel Time under Dynamic Passenger Demand

2016 ◽  
Vol 137 ◽  
pp. 151-160 ◽  
Author(s):  
Pan Shang ◽  
Ruimin Li ◽  
Liya Yang
Keyword(s):  
Travel Time ◽  
Single Line ◽  
Passenger Demand ◽  
Passenger Travel

scholarly journals Optimized Skip-Stop Metro Line Operation Using Smart Card Data

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Peitong Zhang ◽  
Zhanbo Sun ◽  
Xiaobo Liu
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Low Cost ◽  
Optimal Solution ◽  
Cost Savings ◽  
Passenger Demand ◽  
Passenger Travel ◽  
Smart Card Data ◽  
Transit Agencies ◽  
The Right

Skip-stop operation is a low cost approach to improving the efficiency of metro operation and passenger travel experience. This paper proposes a novel method to optimize the skip-stop scheme for bidirectional metro lines so that the average passenger travel time can be minimized. Different from the conventional “A/B” scheme, the proposed Flexible Skip-Stop Scheme (FSSS) can better accommodate spatially and temporally varied passenger demand. A genetic algorithm (GA) based approach is then developed to efficiently search for the optimal solution. A case study is conducted based on a real world bidirectional metro line in Shenzhen, China, using the time-dependent passenger demand extracted from smart card data. It is found that the optimized skip-stop operation is able to reduce the average passenger travel time and transit agencies may benefit from this scheme due to energy and operational cost savings. Analyses are made to evaluate the effects of that fact that certain number of passengers fail to board the right train (due to skip operation). Results show that FSSS always outperforms the all-stop scheme even when most passengers of the skipped OD pairs are confused and cannot get on the right train.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

scholarly journals Passenger Travel Time Reliability for Multimodal Public Transport Journeys

2019 ◽  
Vol 2673 (2) ◽  
pp. 149-160 ◽  
Author(s):  
Malvika Dixit ◽  
Ties Brands ◽  
Niels van Oort ◽  
Oded Cats ◽  
Serge Hoogendoorn
Keyword(s):  
Travel Time ◽  
Network Reliability ◽  
Real Life ◽  
Travel Time Reliability ◽  
Behavioral Models ◽  
Buffer Time ◽  
Passenger Travel ◽  
Departure Time Choice ◽  
Multiple Routes ◽  
The Impact

Urban transit networks typically consist of multiple modes and the journeys may involve a transfer within or across modes. Therefore, the passenger experience of travel time reliability is based on the whole journey experience including the transfers. Although the impact of transfers on reliability has been highlighted in the literature, the existing indicators either focus on unimodal transfers only or fail to include all components of travel time in reliability measurement. This study extends the existing “reliability buffer time” metric to transit journeys with multimodal transfers and develops a methodology to calculate it using a combination of smartcard and automatic vehicle location data. The developed methodology is applied to a real-life case study for the Amsterdam transit network consisting of bus, metro, and tram lines. By using a consistent method for all journeys in the network, reliability can be compared between different transit modes or between multiple routes for the same origin–destination pair. The developed metric can be used to study the reliability impacts of policies affecting multiple transit modes. It can also be used as an input to behavioral models such as mode, route, or departure time choice models.

scholarly journals Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Hezhou Qu ◽  
Xiaoyue Xu ◽  
Steven Chien
Keyword(s):  
Joint Probability ◽  
Wait Time ◽  
Service Planning ◽  
Data Driven ◽  
Passenger Demand ◽  
Passenger Travel ◽  
Data Driven Approach ◽  
System Data ◽  
Transit Performance

The service quality of public transit, such as comfort and convenience, is an important factor influencing ridership and fare revenue, which also reflects the passengers’ perception to the transit performance. Passengers are frustrated while waiting to board a crowded train especially during the peak hours, while the fail-to-board (FtB) situation commonly exists. The service performance measures determined by deterministic passenger demand and service frequency cannot reflect the perceived service of passengers. With the automatic fare collection system data provided by Chengdu Metro, we develop a data-driven approach considering the joint probability of spatiotemporal passenger demand at stations based on posted train schedule to approximate passenger travel time (e.g., in-vehicle and out-of-vehicle times). It was found that the estimated wait time can reflect the actual situation as passengers FtB. The proposed modeling approach and analysis results would be useful and beneficial for transit providers to improve system performance and service planning.

scholarly journals Multi-View Interactive Visual Exploration of Individual Association for Public Transportation Passengers

2020 ◽  
Vol 10 (2) ◽  
pp. 628
Author(s):  
Di Lv ◽  
Yong Zhang ◽  
Jiongbin Lin ◽  
Peiyuan Wan ◽  
Yongli Hu
Keyword(s):  
Travel Time ◽  
Public Transportation ◽  
Travel Behavior ◽  
Visual Exploration ◽  
Passenger Travel ◽  
Working Together ◽  
Transport Safety ◽  
Abnormal Behaviors ◽  
The Relationship ◽  
Pixel Matrix

More and more people in mega cities are choosing to travel by public transportation due to its convenience and punctuality. It is widely acknowledged that there may be some potential associations between passengers. Their travel behavior may be working together, shopping together, or even some abnormal behaviors, such as stealing or begging. Thus, analyzing association between passengers is very important for management departments. It is very helpful to make operational plans, provide better services to passengers and ensure public transport safety. In order to quickly explore the association between passengers, we propose a multi-view interactive exploration method that provides five interactive views: passenger 3D travel trajectory view, passenger travel time pixel matrix view, passenger origin-destination chord view, passenger travel vehicle bubble chart view and passenger 2D travel trajectory view. It can explore the associated passengers from multiple aspects such as travel trajectory, travel area, travel time, and vehicles used for travel. Using Beijing public transportation data, the experimental results verified that our method can effectively explore the association between passengers and deduce the relationship.

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