Flexible feeder transit route design to enhance service accessibility in urban area

2015 ◽  
Vol 50 (4) ◽  
pp. 507-521 ◽  
Author(s):  
Xiaolin Lu ◽  
Jie Yu ◽  
Xianfeng Yang ◽  
Shuliang Pan ◽  
Nan Zou
Keyword(s):  
Urban Area ◽  
Service Accessibility ◽  
Route Design ◽  
Feeder Transit ◽  
Transit Route

Contextual Bandit-Based Sequential Transit Route Design under Demand Uncertainty

2020 ◽  
Vol 2674 (5) ◽  
pp. 613-625
Author(s):  
Gyugeun Yoon ◽  
Joseph Y. J. Chow
Keyword(s):  
Demand Uncertainty ◽  
Operating Cost ◽  
Generation Process ◽  
Random Choice ◽  
Heuristic Solution ◽  
Line Planning ◽  
Route Design ◽  
Transit Route ◽  
Transit Network Design ◽  
Better Than

While public transit network design has a wide literature, the study of line planning and route generation under uncertainty is not so well covered. Such uncertainty is present in planning for emerging transit technologies or operating models in which demand data is largely unavailable to make predictions on. In such circumstances, this paper proposes a sequential route generation process in which an operator periodically expands the route set and receives ridership feedback. Using this sensor loop, a reinforcement learning-based route generation methodology is proposed to support line planning for emerging technologies. The method makes use of contextual bandit problems to explore different routes to invest in while optimizing the operating cost or demand served. Two experiments are conducted. They (1) prove that the algorithm is better than random choice; and (2) show good performance with a gap of 3.7% relative to a heuristic solution to an oracle policy.

scholarly journals Solving urban transit route design problem using selection hyper-heuristics

2019 ◽  
Vol 274 (2) ◽  
pp. 545-559 ◽  
Author(s):  
Leena Ahmed ◽  
Christine Mumford ◽  
Ahmed Kheiri
Keyword(s):  
Design Problem ◽  
Urban Transit ◽  
Route Design ◽  
Transit Route

scholarly journals Optimal Integrated Model for Feeder Transit Route Design and Frequency-Setting Problem with Stop Selection

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Ming Wei ◽  
Tao Liu ◽  
Bo Sun ◽  
Binbin Jing
Keyword(s):  
Walking Distance ◽  
Load Factor ◽  
Chongqing City ◽  
Proposed Model ◽  
Route Design ◽  
Feeder Transit ◽  
Total Travel Time ◽  
Test Instance ◽  
Np Hard Problem ◽  
Lower Limits

This study proposed a mathematical model for designing a feeder transit service for improving the service quality and accessibility of transportation hubs (such as airport and rail station). The proposed model featured an integrated framework, which simultaneously guided passengers to reach their nearest stops to get on and off the bus, designed routes to transport passengers from these selected pick-up stops to the transportation hubs, and calculated their departure frequencies. In particular, the maximum walking distance, the upper and lower limits of route frequencies, and the load factor rate of each route were fully accounted for in this study. The main objective of the proposed model was to simultaneously minimize the total walking, riding time, and waiting time of all passengers. As this study explored an NP-hard problem, a two-stage genetic algorithm combining the Dijkstra search method was further developed to yield metaoptimal solutions to the model within an acceptable time. Finally, a test instance in Chongqing City, China, demonstrated that the proposed model was an effective tool to generate a pedestrian, route, and operation plan; it reduced the total travel time, compared with the traditional model.

Transit Route Design Solved with Wireless Data Collection Algorithms

2014 ◽  
Vol 2466 (1) ◽  
pp. 42-51 ◽  
Author(s):  
David Rey ◽  
Khaled Almi'ani ◽  
Anastasios Viglas ◽  
Lavy Libman ◽  
S. Travis Waller
Keyword(s):  
Data Collection ◽  
Wireless Data ◽  
Route Design ◽  
Transit Route ◽  
Wireless Data Collection

Transit Route Design in the Emerging City Unit around High-Speed Rail Station

2014 ◽  
Vol 1030-1032 ◽  
pp. 2166-2169
Author(s):  
Xiao Wen Liu
Keyword(s):  
High Speed ◽  
High Speed Rail ◽  
Evaluation Standards ◽  
Traffic Demand ◽  
Route Design ◽  
Transit Route ◽  
The Government ◽  
Set Up ◽  
Transit Routes ◽  
The City

Most high-speed rail stations are generally built in the periphery of the city. Therefore, it is necessary for the government to build new transit routes to meet the traffic demand in the emerging city unit around the high-speed rail stations. This paper formulates a model based on genetic algorithms (GA) to design transit route considering various evaluation standards. Numerical example is set up to illustrate the model and algorithm.

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