A SYSTEM-OPTIMAL ROUTING POLICY FOR ROAD TRAFFIC NETWORKS

2006 ◽  
Vol 39 (12) ◽  
pp. 141-146
Author(s):  
Bertrand Haut ◽  
Georges Bastin
Computing ◽  
2020 ◽  
Vol 102 (11) ◽  
pp. 2333-2360
Author(s):  
Tarique Anwar ◽  
Chengfei Liu ◽  
Hai L. Vu ◽  
Md. Saiful Islam ◽  
Dongjin Yu ◽  
...  

2013 ◽  
Vol 10 (1) ◽  
pp. 321-348 ◽  
Author(s):  
Tomas Potuzak

The computer simulation of road traffic is an important tool for control and analysis of road traffic networks. Due to their requirements for computation time (especially for large road traffic networks), many simulators of the road traffic has been adapted for distributed computing environment where combined power of multiple interconnected computers (nodes) is utilized. In this case, the road traffic network is divided into required number of sub-networks, whose simulation is then performed on particular nodes of the distributed computer. The distributed computer can be a homogenous (with nodes of the same computational power) or a heterogeneous cluster (with nodes of various powers). In this paper, we present two methods for road traffic network division for heterogeneous clusters. These methods consider the different computational powers of the particular nodes determined using a benchmark during the road traffic network division.


2015 ◽  
Author(s):  
Nadir Farhi ◽  
Habib Haj-Salem ◽  
Jean-Patrick Lebacque

2013 ◽  
Vol 361-363 ◽  
pp. 2173-2184 ◽  
Author(s):  
Jun Wang ◽  
Meng Liu ◽  
Hong Mei Zhou ◽  
Ying En Ge

This paper attempts to model stochastic choice behavior in simultaneous trip route and departure time decision-making on road traffic networks, taking into account information quality and individual differences in information interpretation among the population of travelers. Different from the traditional stochastic model, the proposed choice behavior model assumes that road users simultaneously select the trip routes and departure times that have the largest probabilities of incurring the least generalized travel costs. This model is applicable in both static and dynamic settings and can be applied to both ordinary travelers as well as operators of emergent vehicles, e.g., the fire engine. The preliminary numerical experiments show that the proposed stochastic choice model can reflect the overreaction phenomena reported in studies of traffic information provision and the impacts of the types of traffic information on the effectiveness of information provision. This model opens a potential way to analyze network equilibrium behavior taking into account individual differences in the ability of information interpretation as well as information quality.


2021 ◽  
pp. 170-180
Author(s):  
Xudan Song ◽  
Jing Wang ◽  
Sijia Liu ◽  
Xiaohan Cui ◽  
Rong-rong Yin

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