scholarly journals Freeway ramp metering based on PSO-PID control

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260977
Author(s):  
Junjun Wei ◽  
Kejun Long ◽  
Jian Gu ◽  
Zhengchuan Zhou ◽  
Shun Li
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Pid Controller ◽  
Ramp Metering ◽  
Flow Density ◽  
Freeway Traffic ◽  
Traffic Efficiency ◽  
Nonlinear Processing ◽  
Actual Profile

Ramp metering on freeway is one of the effective methods to alleviate traffic congestion. This paper advances the field of freeway ramp metering by introducing an application to the on-ramp, capitalizing on the macro traffic follow theory and improved the freeway traffic flow. The Particle Swarm Optimization (PSO) based on Proportional Integral Derivative (PID) controller is further developed to single ramp metering as well as to optimize the PID parameters. The approach is applied to a case study of the Changyi Freeway(G5513) in Hunan, China. The simulation is conducted by applying the actual profile traffic data to PID controller to adjust the entering traffic flow on the freeway on-ramp. The results show that the PSO-PID controller tends to converge in about 80 minutes, and the density tends to be stable after 240 iterations. The system has smaller oscillation, more accurate adjustment of ramp regulation rate, and more ideal expected traffic flow density. The traffic congestion on mainline is effectively slowed down, traffic efficiency is improved, and travel time and cost are reduced. The nonlinear processing ability of PSO-PID controller overcomes the defects of the traditional manual closing ramp, and can be successfully applied in the field of intelligent ramp metering.

scholarly journals Evaluation of the Applicability of the Ramp Metering to a Freeway Using Microsimulation: A Case Study in Riyadh, Saudi Arabia

2019 ◽  
Vol 9 (20) ◽  
pp. 4406
Author(s):  
Seongkwan Lee ◽  
Amr Shokri ◽  
Abdullah Al-Mansour
Keyword(s):  
Saudi Arabia ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Fixed Time ◽  
Ramp Metering ◽  
Traffic Data ◽  
Geometrical Data ◽  
Overall Performance ◽  
Length Reduction

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.

Macroscopic Simulation of Traffic Flow on Continuum Urban Networks

2014 ◽  
Vol 641-642 ◽  
pp. 887-891 ◽  
Author(s):  
Yan Qun Jiang ◽  
Shu Guang Zhou
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Choice Model ◽  
Macroscopic Model ◽  
Flow Density ◽  
Urban Network ◽  
Urban Networks ◽  
Richards Model ◽  
Macroscopic Simulation ◽  
Dynamical Features

In this paper, a macroscopic model is applied to simulate dynamical features of traffic flow on a continuum urban network. This model is described as the two-dimensional Lighthill-Whitham-Richards model coupled with a reactive dynamic user-optimal route choice model. Numerical results visualize the ability of the model to predict some macroscopic characteristics of traffic flow on networks, i.e. the spatial distribution of flow density and travel cost of users, as well as to capture traffic congestion build-up and dissipation.

scholarly journals Urban Wasteful Transport and Its Estimation Methods

2018 ◽  
Vol 10 (12) ◽  
pp. 4562 ◽  
Author(s):  
Xiangyang Cao ◽  
Bingzhong Zhou ◽  
Qiang Tang ◽  
Jiaqi Li ◽  
Donghui Shi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Transport Theory ◽  
Road Traffic ◽  
Urban Traffic ◽  
Flow Density ◽  
Urban Road ◽  
Road Capacity ◽  
Density Relationship

The paper studies urban road traffic problems from the perspective of resource science. The resource composition of urban road traffic system is analysed, and the road network is proved as a scarce resource in the system resource combination. According to the role of scarce resources, the decisive role of road capacity in urban traffic is inferred. Then the new academic viewpoint of “wasteful transport” was proposed. Through in-depth research, the paper defines the definition of wasteful transport and expounds its connotation. Through the flow-density relationship analysis of urban road traffic survey data, it is found that there is a clear boundary between normal and wasteful transport in urban traffic flow. On the basis of constructing the flow-density relationship model of road traffic, combined with investigation and analysis, the quantitative estimation method of wasteful transport is established. An empirical study on the traffic conditions of the Guoding section of Shanghai shows that there is wasteful transport and confirms the correctness of the wasteful transport theory and method. The research of urban wasteful transport also reveals that: (1) urban road traffic is not always effective; (2) traffic flow exceeding road capacity is wasteful transport, and traffic demand beyond the capacity of road capacity is an unreasonable demand for customers; (3) the explanation that the traffic congestion should apply the comprehensive theory of traffic engineering and resource economics; and (4) the wasteful transport theory and method may be one of the methods that can be applied to alleviate traffic congestion.

scholarly journals Left-Side On-Ramp Metering for Improving Safety and Efficiency in Underground Expressway Systems

2019 ◽  
Vol 11 (12) ◽  
pp. 3247 ◽  
Author(s):  
Minhua Shao ◽  
Congcong Xie ◽  
Lijun Sun ◽  
Xiaomin Wan ◽  
Zhang Chen
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Traffic Control ◽  
Flow Characteristics ◽  
Ramp Metering ◽  
Accident Risk ◽  
Data Traffic ◽  
Traffic Efficiency ◽  
Traffic Characteristics ◽  
Two Parameter

As one of the effective measures of intelligent traffic control, on-ramp metering is often used to improve the traffic efficiency of expressways. Existing on-ramp metering research mainly discusses expressways with right-side on-ramps. However, for underground expressway systems (UESs), left-side on-ramps are frequently adopted to reduce the ground space occupied by ramp construction. Since traffic entering from the left and right sides of the mainline may have different traffic characteristics, on-ramp metering for UESs with left-side on-ramps should be explored specifically. This study examines the impacts of left-side on-ramps on the traffic safety and efficiency of UESs and proposes an effective on-ramp metering strategy. Firstly, using field data, traffic flow fundamental diagrams and speed dispersion are discussed to explore the traffic flow characteristics of the “left-in” UES. The results show that the capacity and critical occupancy are both reduced in left-side on-ramp compared to right-side on-ramp expressways. Meanwhile, the speed dispersion is higher in left-side on-ramp UESs, which means a higher accident risk. Based on this, considering traffic safety and efficiency, a novel two-parameter left-side on-ramp metering strategy for UESs is proposed, in which occupancy and speed are used as the control indicators simultaneously. Additionally, the mechanism of the metering strategy is explained. Finally, the proposed on-ramp metering strategy is simulated on a real UES. The results demonstrate the advantages of the proposed two-parameter on-ramp metering strategy for improving the traffic safety and efficiency of UESs.

Freeway Ramp Metering Based on Cell Transmission Model and Single Neuron

2013 ◽  
Vol 423-426 ◽  
pp. 2877-2881
Author(s):  
Yan Di Ye ◽  
Yan Yan Liu ◽  
Xin Rong Liang ◽  
Chao Jun Dong
Keyword(s):  
Traffic Congestion ◽  
Single Neuron ◽  
Learning Algorithm ◽  
Ramp Metering ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Freeway Traffic ◽  
Tracking Process ◽  
Cell Transmission ◽  
Control Objective

In this work, we apply single neuron method to relieve freeway traffic congestion. We consider a freeway composed of cells and entry/exit ramps, and formulate the ramp metering problem as a density tracking process. The cell transmission model (CTM) is firstly formulated and ramp control objective is determined. Based on CTM and single neuron, a freeway ramp metering system is then designed, and the learning algorithm of single neuron is given in detail. Finally, the ramp metering system is simulated in MATLAB software. The results show that this method can effectively deal with this class of control problem, and can achieve a perfect density tracking performance. This ramp metering can eliminate traffic congestion and maintain traffic flow stability.

scholarly journals Linear Data-Model Based Adaptive ILC for Freeway Ramp Metering without Identical Conditions on Initial States and Reference Trajectory

2019 ◽  
Vol 48 (2) ◽  
pp. 268-277
Author(s):  
Hao Liang ◽  
Na Lin ◽  
Ronghu Chi ◽  
Yumei Sun
Keyword(s):  
Traffic Flow ◽  
Data Model ◽  
Controller Design ◽  
Ramp Metering ◽  
Reference Trajectory ◽  
Initial State ◽  
Freeway Traffic ◽  
Traffic System ◽  
Model Based ◽  
The Time Domain

Although freeway traffic system is conducted with a repeatable pattern day-to-day, the initial volume/or speed and the desired density of the traffic flow may vary with days due to the external disturbances. In this paper, a new linear data-model based adaptive ILC (LDM-AILC) is proposed to address ramp metering in a macroscopic level freeway environment. A linear data-model is developed for the nonlinear macroscopic traffic flow model by introducing an equivalent dynamical linearization approach in the time domain. Then the LDM-AILC is designed with a feedback control law and a parameter updating law. The proposed scheme is data-driven intrinsically, where only the I/O data is required for the controller design and analysis. The convergence is shown by rigorous analysis without any identical conditions exposed on both the initial state and the reference trajectory. Extensive simulation results are provided to verify the effectiveness of the proposed LDM-AILC.

Improve urban traffic efficiency with prohibiting left-turn policy

2021 ◽  
Author(s):  
Meng-Qin Cheng ◽  
Lele Zhang ◽  
Xue-Dong Hu ◽  
Mao-Bin Hu
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Critical Length ◽  
Urban Traffic ◽  
Flow Density ◽  
Route Guidance ◽  
Left Turn ◽  
Traffic Efficiency ◽  
Quickest Path ◽  
The Impact

Enhancing traffic flow plays an important role in the traffic management of urban arterial networks. The policy of prohibiting left-turn (PLT) at selected highly demanded intersections has been adopted as an attempt to increase the efficiency at these intersections. In this paper, we study the impact of PLT by mathematical analysis and simulations based on the cellular automaton model. Using the flow-density relation, three system performance indexes are examined: the average trip completion rate, the average traffic flow, and the average velocity of vehicles. Different route guidance strategies, including the shortest path and the quickest path, are investigated. We show that when left turn is prohibited, vehicles are distributed more homogeneously in the road network, and the system performs better and reaches a higher capacity. We also derive a critical length of link, above which the benefit of PLT will decrease.

Using GPS Technology to Relate Macroscopic and Microscopic Traffic Parameters

1996 ◽  
Vol 1520 (1) ◽  
pp. 89-96 ◽  
Author(s):  
Matthew J. Barth ◽  
Eric Johnston ◽  
Ramakrishna R. Tadi
Keyword(s):  
Traffic Congestion ◽  
Vehicle Emissions ◽  
Velocity Variation ◽  
Flow Density ◽  
Emission Model ◽  
Freeway Traffic ◽  
Traffic Sensors ◽  
Statistical Measures ◽  
Speed Flow ◽  
Emission Models

Traffic congestion on today's freeways is a serious problem, causing significant delays for both passengers and goods. Freeway traffic congestion also results in increased vehicle emissions; however, this increase has not been quantified using current vehicle emission models. Current models use emission factors based on driving cycles that do not properly represent freeway driving characteristics. This paper presents a new methodology for relating the macroscopic speed, flow, and density parameters measured by traffic sensors with statistics of microscopic driving traces under different levels of congestion. This approach can be used to better estimate freeway emissions when combined with an appropriate modal emissions model. Preliminary experimentation has been carried out with a vehicle equipped with global positioning system (GPS) instrumentation, allowing for precise localization in both space and time. With the GPS, second-by-second velocity traces are acquired and matched with simultaneously measured freeway traffic data obtained by embedded traffic sensors. Statistical measures of velocity variation are derived from the velocity traces and are functionally related to the macroscopic traffic parameters of speed, flow, and density. Given a known distribution of vehicle types, models, and model years, vehicle emissions can be related to these statistical measures of velocity variation using a modal emission model, and, thus given speed-flow-density measures of freeway traffic, localized emissions estimates can be made.

scholarly journals Urban road traffic flow control under incidental congestion as a function of accident duration

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 1085-1093
Author(s):  
Yang Xu ◽  
Duojia Zhang ◽  
Ahmad Jalal Khan Chowdhury
Keyword(s):  
Flow Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Abrupt Increase ◽  
Urban Road ◽  
Catastrophe Model ◽  
Traffic Capacity ◽  
Control Scheme

Abstract An abrupt increase in urban road traffic flow caused by incidental congestion is considered. The residual traffic capacity varies in different lanes after an accident, and the influence of accident duration on traffic flow is taken into account. The swallowtail catastrophe model was built based on catastrophe theory. The critical state of traffic congestion under incidental congestion was analyzed using this model, and a traffic flow control scheme is proposed with the goal of maximizing the traffic capacity. Finally, the operational state of traffic flow under different scenarios is analyzed through case study and the feasibility of the model is validated.

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