A cellular automata traffic flow model combined with a BP neural network based microscopic lane changing decision model

2018 ◽  
Vol 23 (4) ◽  
pp. 309-318 ◽  
Author(s):  
Meiyu Liu ◽  
Jing Shi
Keyword(s):  
Neural Network ◽  
Cellular Automata ◽  
Traffic Flow ◽  
Bp Neural Network ◽  
Decision Model ◽  
Flow Model ◽  
Lane Changing ◽  
Traffic Flow Model

scholarly journals A Cellular Automata Traffic Flow Model considering Bus Lane Changing Behavior with Scheduling Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zun-dong Zhang ◽  
Yan-fang Yang ◽  
Wenjiao Qi ◽  
Abderrahim Chariete ◽  
Xing-xiang Lin
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Flow Density ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Traffic Flow Model ◽  
Mixed Traffic Flow ◽  
Bus Lane ◽  
Bus Stops

According to different driving behavioral characteristics of bus drivers, a cellular automata traffic model considering the bus lane changing behavior with scheduling parameters is proposed in this paper. Traffic bottleneck problems caused by bus stops are simulated in multiple lanes roads with no-bay bus stations. With the mixed traffic flow composed of different bus arrival rate, flow-density graph, density distribution graph, and temporal-spatial graph are presented. Furthermore, the mixed traffic flow characteristics are analyzed. Numerical experiment results show that the proposed model can generate a variety of complicated realistic phenomena in the traffic system with bus stops and provide theoretical basis for better using of traffic flow model.

A Second Order Traffic Flow Model with Lane Changing

2019 ◽  
Vol 81 (3) ◽  
pp. 1429-1445
Author(s):  
Jiah Song ◽  
Smadar Karni
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Second Order ◽  
Lane Changing ◽  
Traffic Flow Model

scholarly journals A Stochastic Continuous Cellular Automata Traffic Flow Model with a Multi-agent Fuzzy System

2012 ◽  
Vol 54 ◽  
pp. 1350-1359 ◽  
Author(s):  
Öznur Yeldan ◽  
Alberto Colorni ◽  
Alessandro Luè ◽  
Emanuele Rodaro
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Fuzzy System ◽  
Flow Model ◽  
Traffic Flow Model ◽  
Multi Agent

THE TRAFFIC BOTTLENECK EFFECTS CAUSED BY THE LANE CLOSING IN THE CELLULAR AUTOMATA MODEL

2003 ◽  
Vol 14 (10) ◽  
pp. 1295-1303 ◽  
Author(s):  
BIN JIA ◽  
RUI JIANG ◽  
QING-SONG WU
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Rate ◽  
Flow Model ◽  
Maximum Flow ◽  
Density Inversion ◽  
Cellular Automata Model ◽  
Traffic Flow Model ◽  
Density Distributions ◽  
Inversion Phenomenon

As a kind of bottleneck, the lane closing has seldomly been investigated with cellular automata model. In this paper, we study this issue using the cellular automata traffic flow model. The capacity and the density distribution of this kind of bottleneck are discussed in details. We find that (i) the capacity of the bottleneck is a little smaller than the maximum flow rate of single-lane road; (ii) different regulations may lead to different density distributions of the vehicles upstream of the lane closing. Moreover, the density inversion phenomenon is reported under certain conditions. This enlightens us to propose that the phenomenon of density inversion reported in many publications may be caused by the bottlenecks on the highway.

A study of a main-road cellular automata traffic flow model

2002 ◽  
Vol 11 (7) ◽  
pp. 678-683 ◽  
Author(s):  
Huang Ping-Hua ◽  
Kong Ling-Jiang ◽  
Liu Mu-Ren
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Main Road ◽  
Traffic Flow Model
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