An original traffic flow model with signal effect for energy dissipation

2014 ◽  
Vol 25 (07) ◽  
pp. 1450018 ◽  
Author(s):  
Wen-Xing Zhu ◽  
Li-Dong Zhang
Keyword(s):  
Energy Dissipation ◽  
Traffic Flow ◽  
Flow Model ◽  
Mathematical Expression ◽  
Velocity Model ◽  
Energy Dissipation Rate ◽  
Traffic Density ◽  
Traffic Signal Control ◽  
Optimal Velocity ◽  
Traffic Flow Model

We proposed an original traffic flow model with a consideration of signal effect based on Bando's optimal velocity model. The optimal velocity function was improved more realistically in describing the motion process of vehicles moving on a road with signals. Based on the improved model, we derived the mathematical expression for energy dissipation. Simulations are conducted to verify the energy dissipation laws in traffic flow with signals. Numerical results show that energy dissipation (rate) can be affected not only by traffic density, but also traffic signal control parameters: split and cycle.

An Extended Optimal Velocity Model of Traffic Flow with Backward Power Cooperation

2013 ◽  
Vol 336-338 ◽  
pp. 561-565
Author(s):  
Kang Li Chen ◽  
Zhi Peng Li
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Velocity Model ◽  
Mkdv Equation ◽  
Reductive Perturbation Method ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Unstable Region ◽  
Optimal Velocity ◽  
The Stability

In this paper, an extended traffic flow model which considers the strategy of the backward power cooperation is proposed by taking account of the power assist of the nearest rear car. The stability condition of the new model is derived by using the linear stability theory with finding that the power assist of the nearest rear car can stabilize the traffic flow and efficiently suppress traffic jams. Moreover, the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic density waves in the unstable region by using the reductive perturbation method and nonlinear analysis..

The Role of Traffic Flow Preview for Planning Fuel Optimal Vehicle Velocity

2010 ◽  
Author(s):  
Behrang Asadi ◽  
Chen Zhang ◽  
Ardalan Vahidi
Keyword(s):  
Traffic Flow ◽  
Fuel Economy ◽  
Flow Model ◽  
Optimal Velocity ◽  
Traffic Flow Model ◽  
Traffic Pattern ◽  
Vehicle Velocity ◽  
Simulation Results ◽  
Traffic Wave

A vehicle’s untimely arrival at a local traffic wave with lots of stops and goes increases its fuel use. This paper proposes predictive planning of the vehicle velocity for reducing the velocity transients in upcoming traffic waves. Macroscopic evolution of traffic pattern along the vehicle route is first estimated by combining a traffic flow model. The fuel optimal velocity trajectory is calculated by solving an optimal control problem with the spatiotemporally varying constraint imposed by the traffic. Preliminary simulation results indicate the potential for improvement in fuel economy with a little compromise on travel time.

scholarly journals Mixed Vehicular Traffic Flow Model on an Inclined Multilane Road

2020 ◽  
Vol 5 (7) ◽  
pp. 331-342
Author(s):  
Delina Mshai Mwalimo ◽  
Mary Wainaina ◽  
Winnie Kaluki
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Flow Model ◽  
Free Flow ◽  
Traffic Density ◽  
Fundamental Diagram ◽  
Traffic Flow Model ◽  
The Road ◽  
Slow Moving

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.

Fuzzy Logic Based Traffic Density Control via Ramp Metering

2011 ◽  
Vol 97-98 ◽  
pp. 888-891
Author(s):  
Xin Rong Liang ◽  
Di Qian Wang
Keyword(s):  
Fuzzy Logic ◽  
Traffic Flow ◽  
Flow Model ◽  
Tracking Error ◽  
Control Variable ◽  
Ramp Metering ◽  
Traffic Density ◽  
Rule Base ◽  
Traffic Flow Model ◽  
Density Control

In this work, we apply fuzzy logic method to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The second-order traffic flow model is firstly formulated. Then traffic density is selected as the control variable in place of traffic occupancy. Based on the traffic flow model and in conjunction with nonlinear feedback theory, a fuzzy logic based traffic density controller is designed. The ramp metering rate is determined by the fuzzy control according to density tracking error and error variation. Triangle curves are used for the membership functions of the fuzzy variables. The rule base including 56 fuzzy rules is also established. Finally, the fuzzy logic based feedback controller is simulated in Matlab software. Simulation results show that this method has good dynamic and steady-state performance, and can achieve an almost perfect tracking performance.

Congestion Induced by Bottlenecks in Two-Lane Optimal Velocity Traffic Flow Model

2003 ◽  
pp. 211-220 ◽  
Author(s):  
S. Tadaki ◽  
M. Kikuchi ◽  
K. Nishinari ◽  
Y. Sugiyama ◽  
S. Yukawa
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Optimal Velocity ◽  
Traffic Flow Model

An Iterative Learning Approach for Freeway Traffic Density Control

2011 ◽  
Vol 317-319 ◽  
pp. 1394-1397 ◽  
Author(s):  
Xin Rong Liang ◽  
Xiao Yan Wu ◽  
Jian Ye Li
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Control Variable ◽  
Iterative Learning ◽  
Ramp Metering ◽  
Traffic Density ◽  
Nonlinear Feedback ◽  
Freeway Traffic ◽  
Traffic Flow Model ◽  
Density Control

In this work, we apply iterative learning method to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The second-order traffic flow model is firstly formulated. Then traffic density is selected as the control variable in place of traffic occupancy. Based on the traffic flow model and in conjunction with nonlinear feedback theory, an iterative learning based traffic density controller is designed. Finally, the iterative learning based feedback controller is simulated in Matlab software. Simulation results show that this method has good dynamic and steady-state performance, and can achieve an almost perfect tracking performance.

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