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Research and Development (R&D) Consultant Mashhad Traffic&Transportation Organization(MTTO)
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Associate Professor, Iran University of Science and Technology, Tehran.
Abstract
One ways to increase the willingness to use public transport, is greater coordination and integration between modes in the network. Using mass rapid transit is justifying when appropriate demand of them are provided by lower level networks such as feeder network. In this paper, the effect of changes in demand on the design parameters of the multimodal feeder network has been analyzed. According to complexity of mathematic approaches to solve public network design problems, we used a meta heuristic method, Ant Colony Optimization algorithm. The results show an increase in demand in the suburban areas has more effects on the functional parameters to CBD areas and total cost of system would be increased. Because of multimodal services, this is made possible to short-turn services in the network until the variable lines frequency decreased the user and operator costs and increased utility of modes. In the current case study, reduced demand of near and far area from rail route causing to improve about 7% number of route, 20% frequency, 2% total route length and their headway is decreased about 21% to base scenario.
Tahoorinia, M. M., & Shariat Mohaymany, A. (2019). Demand Sensitivity Analysis and It's impacts on the Multimodal Feeder Network Designing. Quarterly Journal of Transportation Engineering, (), -.
MLA
Mohammad Mahdi Tahoorinia; Afshin Shariat Mohaymany. "Demand Sensitivity Analysis and It's impacts on the Multimodal Feeder Network Designing". Quarterly Journal of Transportation Engineering, , , 2019, -.
HARVARD
Tahoorinia, M. M., Shariat Mohaymany, A. (2019). 'Demand Sensitivity Analysis and It's impacts on the Multimodal Feeder Network Designing', Quarterly Journal of Transportation Engineering, (), pp. -.
VANCOUVER
Tahoorinia, M. M., Shariat Mohaymany, A. Demand Sensitivity Analysis and It's impacts on the Multimodal Feeder Network Designing. Quarterly Journal of Transportation Engineering, 2019; (): -.
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