scholarly journals On the robust guidance of users in road traffic networks

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

Influence ranking of road segments in urban road traffic networks

Computing ◽  
2020 ◽  
Vol 102 (11) ◽  
pp. 2333-2360
Author(s):  
Tarique Anwar ◽  
Chengfei Liu ◽  
Hai L. Vu ◽  
Md. Saiful Islam ◽  
Dongjin Yu ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Networks ◽  
Urban Road ◽  
Road Segments ◽  
Road Traffic Networks

scholarly journals Methods for division of road traffic network for distributed simulation performed on heterogeneous clusters

2013 ◽  
Vol 10 (1) ◽  
pp. 321-348 ◽  
Author(s):  
Tomas Potuzak
Keyword(s):  
Road Traffic ◽  
Distributed Simulation ◽  
Computation Time ◽  
Traffic Network ◽  
Traffic Networks ◽  
Computing Environment ◽  
Heterogeneous Cluster ◽  
Heterogeneous Clusters ◽  
The Road ◽  
Road Traffic Networks

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.

Stochastic Choice Behavior on Road Traffic Networks under Information Provision

2013 ◽  
Vol 361-363 ◽  
pp. 2173-2184 ◽  
Author(s):  
Jun Wang ◽  
Meng Liu ◽  
Hong Mei Zhou ◽  
Ying En Ge
Keyword(s):  
Individual Differences ◽  
Choice Behavior ◽  
Information Quality ◽  
Road Traffic ◽  
Information Provision ◽  
Traffic Information ◽  
Traffic Networks ◽  
Stochastic Choice ◽  
Information Interpretation ◽  
Road Traffic Networks

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.

Cascading Failure Mitigation Strategy for Urban Road Traffic Networks

2021 ◽  
pp. 170-180
Author(s):  
Xudan Song ◽  
Jing Wang ◽  
Sijia Liu ◽  
Xiaohan Cui ◽  
Rong-rong Yin
Keyword(s):  
Road Traffic ◽  
Mitigation Strategy ◽  
Cascading Failure ◽  
Traffic Networks ◽  
Urban Road ◽  
Failure Mitigation ◽  
Road Traffic Networks
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