An Object-Oriented Traffic Simulation Model for Intersection Signal Control

2009 ◽  
Author(s):  
P. Agarwal ◽  
R.-L. Cheu ◽  
W.-T. Chan ◽  
E.-P. Chew ◽  
C.-J. Ong
Keyword(s):  
Simulation Model ◽  
Traffic Simulation ◽  
Object Oriented ◽  
Signal Control ◽  
Intersection Signal Control

scholarly journals Self-organisation in traffic signal control algorithms under light traffic conditions

ORiON ◽  
2019 ◽  
Vol 35 (1) ◽  
pp. 57-87
Author(s):  
SJ Movius ◽  
JH Van Vuuren
Keyword(s):  
Simulation Model ◽  
Traffic Simulation ◽  
Control Method ◽  
Fixed Time ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Light Traffic ◽  
Traffic Conditions ◽  
Self Organisation

Fixed-time control and vehicle-actuated control are two distinct types of traffic signal control. The latter control method involves switching traffic signals based on detected traffic flows and thus offers more flexibility (appropriate for lighter traffic conditions) than the former, which relies solely on cyclic, predetermined signal phases that are better suited for heavier traffic conditions. The notion of self-organisation has relatively recently been proposed as an alternative approach towards improving traffic signal control, particularly under light traffic conditions, due to its flexible nature and its potential to result in emergent behaviour. The effectiveness of five existing self-organising traffic signal control strategies from the literature and a fixed-control strategy are compared in this paper within a newly designed agent-based, microscopic traffic simulation model. Various shortcomings of three of these algorithms are identified and algorithmic improvements are suggested to remedy these deficiencies. The relative performance improvements resulting from these algorithmic modifications are then quantified by their implementation in the aforementioned traffic simulation model. Finally, a new self-organising algorithm is proposed that is particularly effective under lighter traffic conditions.

Intelligent control of complex traffic conditions based on machine learning

2021 ◽  
pp. 1-12
Author(s):  
Zhe Li
Keyword(s):  
Machine Learning ◽  
Simulation Model ◽  
Traffic Simulation ◽  
Learning Algorithms ◽  
Control Model ◽  
Machine Learning Algorithms ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Conditions ◽  
Simulation Control

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.

scholarly journals An Intersection Signal Control Mechanism Assisted by Vehicular Ad Hoc Networks

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1402 ◽  
Author(s):  
Zhen Cai ◽  
Zizhen Deng ◽  
Jinglei Li ◽  
Jinghan Zhang ◽  
Mangui Liang
Keyword(s):  
Waiting Time ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Control Mechanism ◽  
Signal Control ◽  
Traffic Flows ◽  
Intersection Signal Control ◽  
Intersection Area ◽  
Vehicle Information ◽  
Hoc Networks

The urban intersection signal decision-making in traditional control methods are mostly based on the vehicle information within an intersection area. The far vehicles that have not reached the intersection area are not taken into account, which results in incomplete information and even incorrectness in decision-making. This paper presents an intersection signal control mechanism assisted by far vehicle information. Using the aid of real-time information collection for far vehicles through vehicular ad hoc networks (VANETs), we can consider them together and calculate the accumulative waiting time for each intersection traffic flow at a future moment to make the optimal signal decision. Simulation results show that, under three different traffic flow environments—same even traffic flows, same uneven traffic flows, and different traffic flows—the two proposed implementation schemes based on the mechanism (fixed phase and period timing improvement scheme, and dynamic phase and period control scheme) show good performances, in which the average waiting time and the ratio of long-waiting vehicles are both less than the results of the traditional signal timing scheme. Especially, in the second scheme, the waiting time was reduced by an average of 38.6% and the ratio of long-waiting vehicles was reduced by an average of 7.67%.

scholarly journals An Evaluation Study on Bus Priority Measures Using Traffic Simulation Model

2000 ◽  
Vol 17 ◽  
pp. 933-940 ◽  
Author(s):  
Kazushi SANO ◽  
Shoji MATSUMOTO ◽  
Toru NOZAWA ◽  
Yuki OBANE
Keyword(s):  
Simulation Model ◽  
Traffic Simulation ◽  
Evaluation Study ◽  
Bus Priority
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