Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

2018 ◽  
Vol 29 (02) ◽  
pp. 1850014 ◽  
Author(s):  
Shu-Bin Li ◽  
Dan-Ni Cao ◽  
Wen-Xiu Dang ◽  
Lin Zhang
Keyword(s):  
Complex Networks ◽  
Traffic Flow ◽  
Traffic Management ◽  
Flow Model ◽  
Complexity Science ◽  
Control Measures ◽  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Flow Model

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.

scholarly journals Modified Traffic Flow Model with Connected Vehicle Microscopic Data for Proactive Variable Speed Limit Control

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jie Fang ◽  
Huixuan Ye ◽  
Said M. Easa
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Simulation Software ◽  
Experimental Simulation ◽  
Speed Limit ◽  
Connected Vehicle ◽  
Flow Data ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Flow Model

Most previous prediction based Variable Speed Limit (VSL) control strategies focused on improving traffic mobility based on the macroscopic traffic data. Nowadays, the emerging technologies provide access to the microscopic traffic flow data, which better captures the details of traffic flow dynamics in the VSL controlled environment. Thus, in this paper, the microscopic traffic flow data were utilized as a supplement to predict the evolutions of traffic flow parameters. The proposed VSL control algorithm adopts the Model Predictive Control (MPC) framework, which employs a modified version of the classic traffic flow model METANET to take advantage of the microscopic data in traffic flow predictions. The microscopic traffic simulation software VISSIM was used to establish an experimental simulation platform and perform real time traffic responsive control based on field data. The proposed control strategy was evaluated against the no-VSL control and macroscopic-based VSL controlled scenario. The results show that utilizing the proposed modified METANET model reduced the error in speed prediction accuracy and improved system mobility performance.

scholarly journals Enhancing Freeway Safety through Intervening in Traffic Flow Dynamics Based on Variable Speed Limit Control

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jinming You ◽  
Shouen Fang ◽  
Lanfang Zhang ◽  
John Taplin ◽  
Jingqiu Guo
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
New Technologies ◽  
Flow Dynamics ◽  
Crash Risk ◽  
Speed Limit ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Traffic Conditions ◽  
Safety Research

New technologies and traffic data sources provide great potential to extend advanced strategies in freeway safety research. The High Definition Monitoring System (HDMS) data contribute comprehensive and precise individual vehicle information. This paper proposes an innovative Variable Speed Limit (VSL) based approach to manage crash risks by intervening in traffic flow dynamics on freeways using HDMS data. We first conducted an empirical analysis on real-time crash risk estimation using a binary logistic regression model. Then, intensive microscopic simulations based on AIMSUN were carried out to explore the effects of various intervention strategies with respect to a 3-lane freeway stretch in China. Different speed limits with distinct compliance rates under specified traffic conditions have been simulated. By taking into account the trade-off between safety benefits and delay in travel time, the speed limit strategies were optimized under various traffic conditions and the model with gradient feedback produces more satisfactory performance in controlling real-time crash risks. Last, the results were integrated into lane management strategies. This research can provide new ideas and methods to reveal the freeway crash risk evolution and active traffic management.

scholarly journals Predicting Traffic Dynamics with Driver Response Model for Proactive Variable Speed Limit Control Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Huixuan Ye ◽  
Lili Tu ◽  
Jie Fang
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Control Algorithm ◽  
Field Data ◽  
Speed Limit ◽  
Response Model ◽  
Variable Speed ◽  
Variable Speed Limit ◽  
Driver Response ◽  
Traffic State

Variable Speed Limit (VSL) control contributes to potential crash risk reduction by suggesting a suitable dynamic speed limit to achieve more stable and uniform traffic flow. In recent studies, researchers adopted macroscopic traffic flow models and perform prediction-based optimal VSL control. The response of drivers to the advised VSL is one of the most critical parameters in VSL-controlled speed dynamics modeling, which significantly affects the accuracy of traffic state prediction as well as the control reliability and performance. Nevertheless, the variations of driver responses were not explicitly modeled. Thus, in this research, the authors proposed a dynamic driver response model to formulate how the drivers respond to the advised VSL during various traffic conditions. The model was established and calibrated using field data to quantitatively analyze the dynamics of drivers’ desired speed regarding the advised VSL and current traffic state variables. A proactive VSL control algorithm incorporating the established driver response model was designed and implemented in field-data-based simulation study. The design proactive control algorithm modifies VSL in real-time according to the traffic state prediction results, aiming to reduce potential crash risks over the experiment site. By taking into account the real-time driver response variations, the VSL-controlled traffic state dynamics was more accurately predicted. The experimental results illustrated that the proposed control algorithm effectively reduces the crash probabilities in the traffic network.

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.

scholarly journals Evaluation of Integrated Variable Speed Limit and Lane Change Control for Highway Traffic Flow

2021 ◽  
Vol 54 (2) ◽  
pp. 107-113
Author(s):  
Tianchen Yuan ◽  
Faisal Alasiri ◽  
Yihang Zhang ◽  
Petros A. Ioannou
Keyword(s):  
Traffic Flow ◽  
Speed Limit ◽  
Lane Change ◽  
Variable Speed ◽  
Highway Traffic ◽  
Variable Speed Limit

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

2021 ◽  
Author(s):  
Cong Zhai ◽  
Weitiao Wu
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Flow Model ◽  
Transfer Functions ◽  
Delayed Feedback ◽  
Time Step ◽  
Current Time ◽  
Traffic Flow Model ◽  
Car Following ◽  
V2v Communication

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.

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