- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | WANG Zhijian, LIU Shijie, ZHOU Jinyao, SUN Jian. Multimodal Public Transportation Route Planning Considering Personalized Travel Demand[J]. Journal of Southwest Jiaotong University, 2022, 57(6): 1319-1325, 1333. doi: 10.3969/j.issn.0258-2724.20210633
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Traditional route planning scheme cannot meet the increasing travel demand of travelers in the process of multimodal transportation. To provide personalized route planning scheme based on various travel demands of travelers, public transport timetable is simulated with the integrated circuit card data, and a multimodal transportation network modal is established based on simulated schedule. A dynamic thresholding method is used to establish the personalized travel demand evaluation value model. The depth first search-genetic algorithm (GA-DFS) is designed, and the initial population generation strategy and two-point mutation method based on this combination algorithm are proposed. Finally, three scenarios with different travel demands are assumed, the example data of a multimodal transportation network in an urban area is applied to the modal and the solution algorithm, comparing with the simulated annealing-genetic algorithm (GA-SA) which is widely used. The results show that compared with GA-SA, the proposed algorithm reduces the average number of iterations by 42%, improves the optimization ability by 50% and provides a route planning scheme based on multiple travel demands of passengers.
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