scholarly journals Self-Delayed Feedback Based Car Following Control With Velocity Uncertainty of Preceding Vehicle On Gradient Roads

Author(s):  
Cong Zhai ◽  
Weitiao Wu

Abstract Uphill and downhill roads are prevalent in mountainous areas and freeways. Despite the advancement of vehicle-to-vehicle (V2V) communication technology, the driving field of vision is still largely limited under such a complex road environment, which hinders the sensors accurately perceiving the speed of the front vehicle. As such, a fundamental question for autonomous traffic management is how to control traffic flow associated with the velocity uncertainty of preceding vehicles? This paper seeks to develop a controlling framework for corporative car following control under such complex road environment. To this end, we first propose a traffic flow model accounting for the uncertainty effect of preceding vehicles velocity on gradient road. We further design a new self-delayed feedback controller based on the velocity and headway difference between the current time step and historical time step, in an aim to enhance the robustness of traffic flow. The sufficient condition where traffic jam does not occur is derived from the perspective of the frequency domain via Hurwitz criteria H∞ and norm of transfer functions. The bode diagram reveals that the robustness of closed-loop traffic flow model has been significantly enhanced. We also conduct simulations to verify the theoretical analysis.

2012 ◽  
Vol 178-181 ◽  
pp. 2717-2720
Author(s):  
Man Xian Tuo

An extended traffic flow model is proposed by introducing the multiple information of preceding cars. The linear stability condition of the extended model is obtained, which shows that the stability of traffic flow is improved by considering the interaction of preceding cars to the following car. Numerical simulation shows that the traffic jams are suppressed efficiently by taking into account the multiple information of the preceding cars.


Author(s):  
Delina Mshai Mwalimo ◽  
Mary Wainaina ◽  
Winnie Kaluki

This study outlines the Kerner’s 3 phase traffic flow theory, which states that traffic flow occurs in three phases and these are free flow, synchronized flow and wide moving jam phase. A macroscopic traffic model that is factoring road inclination is developed and its features discussed. By construction of the solution to the Rienmann problem, the model is written in conservative form and solved numerically. Using the Lax-Friedrichs method and going ahead to simulate traffic flow on an inclined multi lane road. The dynamics of traffic flow involving cars(fast moving) and trucks(slow moving) on a multi-lane inclined road is studied. Generally, trucks move slower than cars and their speed is significantly reduced when they are moving uphill on an in- clined road, which leads to emergence of a moving bottleneck. If the inclined road is multi-lane then the cars will tend to change lanes with the aim of overtaking the slow moving bottleneck to achieve free flow. The moving bottleneck and lanechange ma- noeuvres affect the dynamics of flow of traffic on the multi-lane road, leading to traffic phase transitions between free flow (F) and synchronised flow(S). Therefore, in order to adequately describe this kind of traffic flow, a model should incorporate the effect of road inclination. This study proposes to account for the road inclination through the fundamental diagram, which relates traffic flow rate to traffic density and ultimately through the anticipation term in the velocity dynamics equation of macroscopic traffic flow model. The features of this model shows how the moving bottleneck and an incline multilane road affects traffic transistions from Free flow(F) to Synchronised flow(S). For a better traffic management and control, proper understanding of traffic congestion is needed. This will help road designers and traffic engineers to verify whether traffic properties and characteristics such as speed(velocity), density and flow among others determines the effectiveness of traffic flow.


2010 ◽  
Vol 13 (2) ◽  
pp. 279-303 ◽  
Author(s):  
Marte Godvik ◽  
◽  
Harald Hanche-Olsen

2018 ◽  
Vol 29 (02) ◽  
pp. 1850014 ◽  
Author(s):  
Shu-Bin Li ◽  
Dan-Ni Cao ◽  
Wen-Xiu Dang ◽  
Lin Zhang

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.


2020 ◽  
Vol 31 (12) ◽  
pp. 2050167
Author(s):  
Qi-Lang Li ◽  
Rui Jiang ◽  
Zhong-Jun Ding ◽  
Bing-Hong Wang

This study examines the cellular automata traffic flow model, which considers the asynchronous update of vehicles’ velocities. Computer simulations are used to identify three typical phases: linear free flow phase, nonlinear moving phase and traffic jam phase. Compared to the original NaSch model, the system of the present model can reach the maximum flow when the vehicle density is higher. The influence of the delay probability and the maximum time step in which drivers intend to keep their current velocity on fundamental diagram is discussed.


2017 ◽  
Vol 89 (2) ◽  
pp. 1099-1109 ◽  
Author(s):  
Yongsheng Qian ◽  
Junwei Zeng ◽  
Neng Wang ◽  
Jinlong Zhang ◽  
Bingbing Wang

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