Transit network design based on travel time reliability

2014 ◽  
Vol 43 ◽  
pp. 233-248 ◽  
Author(s):  
Baozhen Yao ◽  
Ping Hu ◽  
Xiaohong Lu ◽  
Junjie Gao ◽  
Mingheng Zhang
2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Shushan Chai ◽  
Qinghuai Liang

The transit network design and frequency setting problem is related to the generation of transit routes with corresponding frequency schedule. Considering not only the influence of transfers but also the delay caused by congestion on passengers’ travel time, a multi-objective transit network design model is developed. The model aims to minimize the travel time of passengers and minimize the number of vehicles used in the network. To solve the model belongs to a NP-Hard problem and is intractable due to the high complexity and strict constraints. In order to obtain the better network schemes, a multi-population genetic algorithm is proposed based on NSGA-II framework. With the algorithm, network generation, mode choice, demand assignment, and frequency setting are all integrated to be solved. The effectiveness of the algorithm which includes the high global convergence and the applicability for the problem is verified by comparison with previous works and calculation of a real-size case. The model and algorithm can be used to provide candidates for the sustainable policy formulation of urban transit network scheme.


Author(s):  
R. van Nes ◽  
P.H.L. Bovy

Stop spacing and line spacing are key design variables in urban transit-network design. They determine both the travel time and the operational costs. It is therefore essential to know what the main relationships are for these design variables. The question is, What are the optimal values for stop spacing and for line spacing in urban transit networks, given traveler preferences and supply-budget constraints? Possible objectives are discussed and analyzed using analytical models. The results of these analytical models for two typical city types are analyzed by comparing performance characteristics (i.e., travel time, operator costs, and patronage). Modeling outcomes are compared with actual data for urban transit networks in Europe. A supplemental analysis is made of the impact of considering different traveler groups. It was found that although many objectives may be formulated, only a few objectives are suitable for transit-network design. Currently applied stop spacings prove to be too short. Focusing the design to specific traveler groups might lead to a variation of stop spacing and line spacing ranging from −12 percent to +13 percent at most. Recommendations for urban transit-network design and for further research are given.


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