Importance of Objectives in Urban Transit-Network Design

2000 ◽  
Vol 1735 (1) ◽  
pp. 25-34 ◽  
Author(s):  
R. van Nes ◽  
P.H.L. Bovy
Keyword(s):  
Network Design ◽  
Travel Time ◽  
Analytical Models ◽  
Urban Transit ◽  
Transit Network ◽  
Transit Networks ◽  
Design Variables ◽  
Line Spacing ◽  
Transit Network Design ◽  
Stop Spacing

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.

Multiuser-Class Urban Transit Network Design

2003 ◽  
Vol 1835 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Rob van Nes
Keyword(s):  
Network Design ◽  
Travel Behavior ◽  
Consumer Surplus ◽  
Urban Transit ◽  
Transit Network ◽  
Transit Networks ◽  
Optimal Network Design ◽  
Realistic Description ◽  
Design Characteristics ◽  
Transit Network Design

In transit network design it is common to use characteristics of the average traveler to describe travel behavior, while in reality different traveler groups can be distinguished that react differently with respect to transport service quality. A study is conducted of the possible consequences of basing the design of urban transit networks on the preferences of specific traveler groups. To that end, an analytical network optimization model is developed that considers a mix of different traveler groups simultaneously. Results from the analyses show that focusing on specific traveler groups leads to clearly different network design characteristics. However, the optimal network design developed for the average traveler proved to be the best network for all traveler groups. Furthermore, it was found that focusing on traveler groups having good transport alternatives led to very low values of consumer surplus and social welfare. Optimizing transit networks while considering different traveler groups simultaneously results in networks that are similar to those using the traditional single-user-class approach based on the average traveler. Differences in preferences for traveler groups are balanced by the size of the resulting transit patronage. Apparently, a more realistic description of the demand side is not essential for urban transit network design.

scholarly journals An Improved NSGA-II Algorithm for Transit Network Design and Frequency Setting Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-20 ◽  
Author(s):  
Shushan Chai ◽  
Qinghuai Liang
Keyword(s):  
Network Design ◽  
Travel Time ◽  
Policy Formulation ◽  
Nsga Ii ◽  
Transit Network ◽  
Generation Mode ◽  
Np Hard Problem ◽  
Transit Network Design ◽  
Population Genetic Algorithm ◽  
Transit Routes

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.

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
Keyword(s):  
Network Design ◽  
Travel Time ◽  
Travel Time Reliability ◽  
Transit Network ◽  
Transit Network Design

scholarly journals Regularity analysis for optimizing urban transit network design

2009 ◽  
Vol 1 (2) ◽  
pp. 155-168 ◽  
Author(s):  
Niels van Oort ◽  
Rob van Nes
Keyword(s):  
Network Design ◽  
Urban Transit ◽  
Transit Network ◽  
Transit Network Design

Sustainable urban transit network design

2015 ◽  
Vol 77 ◽  
pp. 276-291 ◽  
Author(s):  
Moschoula Pternea ◽  
Konstantinos Kepaptsoglou ◽  
Matthew G. Karlaftis
Keyword(s):  
Network Design ◽  
Urban Transit ◽  
Transit Network ◽  
Transit Network Design
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