Advanced traffic control methods for network management

1990 ◽  
Vol 28 (10) ◽  
pp. 82-88 ◽  
Author(s):  
K. Mase ◽  
H. Yamamoto
2013 ◽  
Vol 23 (1) ◽  
pp. 183-200 ◽  
Author(s):  
Fei Yan ◽  
Mahjoub Dridi ◽  
Abdellah El Moudni

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.


2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>


1948 ◽  
Vol 52 (448) ◽  
pp. 251-258 ◽  
Author(s):  
E. G. Bowen ◽  
T. Pearcey

It is becoming recognised that before civil aircraft can operate at high density, the most important problem to be solved is that of traffic control. Methods exist by which a single aircraft can navigate from a distant point to an airport and let down to a safe landing under bad weather conditions. Difficulties arise when several aircraft are involved at once and long delays can occur in the neighbourhood of airports carrying high density traffic. In this paper an analysis is made of the traffic problem in an attempt to clarify some of the factors involved.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Lina Wu ◽  
Yusheng Ci ◽  
Yichen Sun ◽  
Wei Qi

The traffic operational efficiency of the urban expressway system will affect one of the entire cities. Moreover, the idea that traffic control can improve the traffic operational efficiency of the urban expressway system has been fully confirmed. At present, the main control methods include on-ramp metering and speed guidance control. However, there is a gap in using these two control methods together, such as unclear application conditions and unsystematic methods. In this paper, on-ramp metering and speed guidance control are combined effectively. Based on the research of METANET macroscopic traffic flow model and model predictive control (MPC), a novel joint control method based on MPC and connected vehicles (CVs) for on-ramp metering and speed guidance control of the urban expressway is proposed. Finally, the simulation results show that the proposed control method can effectively improve the traffic efficiency and traffic safety.


2021 ◽  
Author(s):  
Hossein Moradi ◽  
Sara Sasaninejad ◽  
Sabine Wittevrongel ◽  
Joris Walraevens

<p>The importance of addressing the complexities of mixed traffic conditions by providing innovative approaches, models, and algorithms for traffic control has been well highlighted in the state-of-the-art literature. Accordingly, the first aim of this study has been to enhance the traditional intersection control methods for the incorporation of autonomous vehicles and wireless communications. For this purpose, we have introduced a novel framework labeled by “PRRP-framework”. The PRRP-framework also enables flexible preferential treatments for some special vehicles within an implementable range of complexity while it addresses the stochastic nature of traffic flow. Moreover, the PRRP-framework has been coupled with a speed advisory system that brings complementary strengths leading to even better performance. Further simulations reported in this manuscript, confirmed that such an integration effort is a prerequisite to move towards sustainable results.<br></p> <p> </p>


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