A mixed-equilibrium model of individual and household activity–travel choices in multimodal transportation networks

2021 ◽  
Vol 131 ◽  
pp. 103337
Author(s):  
Khoa D. Vo ◽  
William H.K. Lam ◽  
Zhi-Chun Li
2016 ◽  
Vol 2 (2) ◽  
pp. e1500445 ◽  
Author(s):  
Riccardo Gallotti ◽  
Mason A. Porter ◽  
Marc Barthelemy

Cities and their transportation systems become increasingly complex and multimodal as they grow, and it is natural to wonder whether it is possible to quantitatively characterize our difficulty navigating in them and whether such navigation exceeds our cognitive limits. A transition between different search strategies for navigating in metropolitan maps has been observed for large, complex metropolitan networks. This evidence suggests the existence of a limit associated with cognitive overload and caused by a large amount of information that needs to be processed. In this light, we analyzed the world’s 15 largest metropolitan networks and estimated the information limit for determining a trip in a transportation system to be on the order of 8 bits. Similar to the “Dunbar number,” which represents a limit to the size of an individual’s friendship circle, our cognitive limit suggests that maps should not consist of more than 250 connection points to be easily readable. We also show that including connections with other transportation modes dramatically increases the information needed to navigate in multilayer transportation networks. In large cities such as New York, Paris, and Tokyo, more than 80% of the trips are above the 8-bit limit. Multimodal transportation systems in large cities have thus already exceeded human cognitive limits and, consequently, the traditional view of navigation in cities has to be revised substantially.


2019 ◽  
Vol 6 (3) ◽  
pp. 4991-5000 ◽  
Author(s):  
Peng Cheng ◽  
Congwei Xu ◽  
Pierre Lebreton ◽  
Zidong Yang ◽  
Jiming Chen

2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu

Considering the un-deterministic transportation networks, the paper proposes the change of the route choice decisions under the stochastic transportation networks. The route choice behavior is described as a choice for a time shortest route which is subject to a time-reliability level. The paper also considered this new route choice behavior in the stochastic user equilibrium model, and proposed stochastic user equilibrium model based on the optimized reliability travel time route choice behavior in the stochastic networks. The equivalence and uniqueness of the solution of the model are demonstrated. Numerical results of a small network show that the proposed model can reflect the real traveler’s route choice behavior in stochastic transportation networks.


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