scholarly journals Extremum Seeking for Traffic Congestion Control With a Downstream Bottleneck

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Huan Yu ◽  
Shumon Koga ◽  
Tiago Roux Oliveira ◽  
Miroslav Krstic
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Extremum Seeking ◽  
Delay Compensation ◽  
Fundamental Diagram ◽  
Optimal Density ◽  
Traffic Demand ◽  
Traffic Congestion Control ◽  
On The Road ◽  
Capacity Drop

Abstract This paper develops boundary control for freeway traffic with a downstream bottleneck. Traffic on a freeway segment with capacity drop at outlet of the segment is a common phenomenon that leads to traffic bottleneck problem. The capacity drop can be caused by lane-drop, hills, tunnel, bridge, or curvature on the road. If incoming traffic flow remains unchanged, traffic congestion forms upstream of the bottleneck since the upstream traffic demand exceeds its capacity. Therefore, it is important to regulate the incoming traffic flow of the segment to avoid overloading the bottleneck area. Traffic densities on the freeway segment are described with the Lighthill–Whitham–Richards (LWR) macroscopic partial differential equation (PDE) model. The incoming flow at the inlet of the freeway segment is controlled so that the optimal density that maximizes the outgoing flow is reached and the traffic congestion upstream of the bottleneck is mitigated. The density and traffic flow relation at the bottleneck area, usually described with fundamental diagram, is considered to be unknown. We tackle this problem using extremum seeking (ES) control with delay compensation for the LWR PDE. ES control, a nonmodel-based approach for real-time optimization, is adopted to find the optimal density for the unknown fundamental diagram. A predictor feedback control design is proposed to compensate the delay effect of traffic dynamics in the freeway segment. In the end, simulation results are obtained to validate a desired performance of the controller on the nonlinear LWR model with an unknown fundamental diagram.

Path Reconstruction of Intelligent Traffic Based on Positive Feedback System

2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Supply And Demand ◽  
Demand Management ◽  
Reference Value ◽  
Feedback System ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Demand

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.

Characteristic Parameters Identification of Macro Traffic Flow on Urban Expressway

2013 ◽  
Vol 409-410 ◽  
pp. 1209-1212
Author(s):  
Da Shan Chen
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Network ◽  
Large Scale ◽  
Characteristic Parameters ◽  
Traffic Demand ◽  
Urban Expressway ◽  
Back Ground ◽  
Control And Management

The macroscopic traffic flow parameters characteristic is an important research content in traffic flow theory. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. With the growing of traffic demand and much more traffic congestion and accidents, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. As the backbone road network, traffic flow characteristic parameters have great value for the control and management of urban expressway. Then the characteristic variables of the expressway traffic flow were identified which support meticulous management for urban expressway.

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 Traffic signal coordination control along oversaturated two-way arterials

2020 ◽  
Vol 6 ◽  
pp. e319
Author(s):  
Haitao Xu ◽  
Zuozhang Zhuo ◽  
Jing Chen ◽  
Xujian Fang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Control Method ◽  
Traffic Signal ◽  
Coordination Control ◽  
Minimization Method ◽  
Traffic Condition ◽  
Traffic Demand ◽  
Signal Coordination ◽  
Arterial Coordination

As an effective method to alleviate traffic congestion, traffic signal coordination control has been applied in many cities to manage queues and to regulate traffic flow under oversaturated traffic condition. However, the previous methods are usually based on two hypotheses. One is that traffic demand is constant. The other assumes that the velocity of vehicle is immutable when entering the downstream section. In the paper, we develop a novel traffic coordination control method to control the traffic flow along oversaturated two-way arterials without both these hypotheses. The method includes two modules: intersection coordination control and arterial coordination control. The green time plan for all intersections can be obtained by the module of intersection coordination control. The module of arterial coordination control can optimize offset plan for all intersections along oversaturated two-way arterials. The experiment results verify that the proposed method can effectively control the queue length under the oversaturated traffic state. In addition, the delay in this method can be decreased by 5.4% compared with the existing delay minimization method and 13.6% compared with the traffic coordination control method without offset optimization. Finally, the proposed method can balance the delay level of different links along oversaturated arterial, which can directly reflect the efficiency of the proposed method on the traffic coordination control under oversaturated traffic condition.

An Integrative Behavioral-Based Physics-Inspired Approach to Traffic Congestion Control

2020 ◽  
Author(s):  
Hossein Rastgoftar ◽  
Jean-Baptiste Jeannin ◽  
Ella Atkins
Keyword(s):  
Traffic Congestion ◽  
Mass Conservation ◽  
Flow Density ◽  
Fundamental Diagram ◽  
Efficient Manner ◽  
Steady State Condition ◽  
Control Approach ◽  
Traffic Congestion Control ◽  
And Control ◽  
Control Traffic

Abstract This paper offers an integrative behavioral-based physics-inspired approach to model and control traffic congestion in an efficient manner While existing physics-based approaches commonly assign density and traffic flow states with the Fundamental Diagram, this paper specifies the flow-density relation using past traffic behavior (intent) recorded over a time sliding window with constant horizon length. With this approach, traffic coordination trends can be consistently learned and incorporated into traffic planning. This is integrated with mass conservation law (continuity) to model traffic coordination as a probabilistic process and obtain traffic feasibility conditions using linear temporal logic. By spatial discretization of a network of inter-connected roads (NOIR), the NOIR is represented by a graph with inlet boundary nodes, outlet boundary nodes, and interior nodes. The paper offers a boundary control approach to manage congestion through the inlet boundary nodes. More specifically, model predictive control (MPC) is applied to control traffic congestion through the boundary of the traffic network. Therefore, the optimal boundary in flow is assigned as the solution of a constrained quadratic programming problem with equality and inequality constrained. The simulation results shows that the proposed MPC boundary controller can successfully control the traffic through the inlet boundary nodes where traffic reaches the steady state condition.

Evaluation of Signalized Intersection Service Level in the Traffic Impact Assessment

2013 ◽  
Vol 869-870 ◽  
pp. 327-333
Author(s):  
Qian Wang ◽  
Chun Fu Shao
Keyword(s):  
Impact Assessment ◽  
Traffic Flow ◽  
Service Level ◽  
Signalized Intersection ◽  
Traffic Demand ◽  
The Road ◽  
Traffic Impact ◽  
On The Road ◽  
Vehicle Capacity ◽  
The Impact

Traffic Impact Assessment focuses on analysis and evaluation of the traffic flow generated by the proposed project impact on the road network in the future, through comparing the sections,intersection and other transportation infrastructure indexes such as traffic flow and road vehicle capacity, evaluate whether the traffic system can meet the increased traffic demand. In this paper, make the delay time and the road saturation as the evaluation index, studies the influence scope of the key signal intersection service level, in order to assess the impact of new projects on the signalized intersection. Cited Haikou province Hongzhou center as an example, based on the investigation of the traffic flow, calculate the time delay and road saturation to analyze the service level.

scholarly journals Quantifying the phantom jam externality: the case of an Autobahn section in Germany

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Kathrin Goldmann ◽  
Gernot Sieg
Keyword(s):  
Traffic Flow ◽  
Traffic Demand ◽  
Traffic Jam ◽  
The Road ◽  
Traffic Jams ◽  
On The Road ◽  
High Road

AbstractIf not restricted by tolls, private decisions to drive on a highway result in inefficiently high usage which leads to traffic jams. When traffic demand is high, traffic jams can occur simply because of the interaction of vehicle drivers on the road, a phenomenon called phantom jam. The probability of phantom jams occurring increases with traffic flow. Unpriced externalities lead to inefficiently high road usage. We offer a method for quantifying traffic jam externalities and identifying and isolating the phantom jam externality. We examine the method by applying it to a specific highway section in Germany. The maximal congestion externality for the analyzed highway section is about 38 cents per vehicle and kilometer. Congestion charges that are calculated ignoring phantom jam externalities, can only internalize two-thirds of the true externality.

scholarly journals Effect of Driver Behaviour on Traffic Jams

2020 ◽  
Vol 17 (4) ◽  
pp. 272-281
Author(s):  
V. N. Baskov ◽  
D. A. Krasnikova ◽  
E. I. Isaeva
Keyword(s):  
Probability Distribution ◽  
Response Time ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Road Safety ◽  
Experimental Studies ◽  
Driver Behaviour ◽  
Driving Style ◽  
The Road ◽  
On The Road

Driving in a traffic flow implies involvement in difficult traffic situations that adversely affects response time of a driver, which in turn is considered when estimating stopping distance of a vehicle and determines road safety. This relationship shows the effect of driver behaviour in traffic flow on the road traffic situation. The objective of the study was to study behavioural factors that influence driver’s decisions. The study used methods of driver behaviour modelling, mathematical modelling, experimental studies of the mental and psychological functions of drivers. Modelling the driver’s behaviour, considering various combinations of many behavioural and other factors, leads to a large number of options for mathematical description of driver behaviour, which makes it difficult to use this approach to describe behaviour of drivers under the conditions of a real street-road network. The research has analysed several works devoted to the study of control action of drivers, using unknown coefficients, describing a model of movement of vehicles considering accuracy of their control. Driving through an unregulated intersection is considered as the most complex and informative version of driver’s behaviour. It is found that when modelling a traffic flow, it is necessary to take into account the degree of resoluteness of drivers (through determination of a coefficient of resoluteness which is a random variable that takes into account the probability distribution of the coefficient’s value in conjunction with the probability distribution of the function of traffic flow intensity). The distribution of the coefficient of resoluteness of drivers, obtained from experimental data, was subject to analysis. It is determined that the driving style affects formation of traffic congestion. The assessment of the driving style is made through conditional classification of driver behaviour on the road, namely marked by manifestation of aggression and timidity. When studying the behaviour of timid and aggressive drivers, several pairs of trajectories and the dynamics of the corresponding traffic flow density, were considered and calculated based on Edie’s model. It has been confirmed that traffic congestion has the greatest negative effect on choleric drivers and sanguine drivers. Besides, there is a relationship between the response time of a driver and the change in his functional condition. It is concluded that to improve road safety thanks to a more accurate assessment of possible risks of formation of congestion situations, it is necessary to consider behavioural characteristics and temperaments of the drivers.

Land Use-Slow Traffic and Demand Forecasting

2017 ◽  
Vol 42 (3) ◽  
pp. 130-134
Author(s):  
Ren Hong ◽  
Zhang Zhengtong ◽  
Ma Xianrui ◽  
Tang Xilai
Keyword(s):  
Land Use ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Population Distribution ◽  
Demand Forecasting ◽  
Urban Traffic ◽  
High Tech ◽  
Traffic Demand ◽  
The Cross ◽  
Traffic Systems

In the face of solving the urban traffic congestion problem radically, emphasis has been laid on the research on slow traffic planning of urban built environment. Hence, research on slow traffic demand forecasting can provide a basis for the planning of urban slow traffic systems. Based on land use, the overall planning of the new Guangming (GM) district, and the population prediction results, the slow traffic demand within the scope of the new district was forecasted by combining the per capita trip frequency, and the spatial distribution of the slow traffic flow of the new GM district was forecasted per the forecasted demand quantity for slow traffic. The following research conclusions were obtained. Within the new GM district, the correlation of the total demand for slow traffic with the land use functions and population distribution was high, and the cross-zone traffic was mainly decided by the land usage of this district. The cross-unit slow traffic flow was concentrated in the Gongming central, Guangming central, high-tech zone, and Yutian zones. This research provides a guideline for the layout of slow traffic facilities in the future.

Video Stream Mining for On-Road Traffic Density Analytics

2012 ◽  
pp. 182-194
Author(s):  
Rudra Narayan Hota ◽  
Kishore Jonna ◽  
P. Radha Krishna
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Video Stream ◽  
Traffic Density ◽  
Svm Classifier ◽  
Stream Mining ◽  
The Road ◽  
Video Frames ◽  
Traffic Congestion Control ◽  
On The Road

Traffic congestion problem is rising day-by-day due to increasing number of small to heavy weight vehicles on the road, poorly designed infrastructure, and ineffective control systems. This chapter addresses the problem of estimating computer vision based traffic density using video stream mining. We present an efficient approach for traffic density estimation using texture analysis along with Support Vector Machine (SVM) classifier, and describe analyzing traffic density for on-road traffic congestion control with better flow management. This approach facilitates integrated environment for users to derive traffic status by mining the available video streams from multiple cameras. It also facilitates processing video frames received from video cameras installed in traffic posts and classifies the frames according to traffic content at any particular instance. Time series information available from various input streams is combined with traffic video classification results to discover traffic trends.

Sign in / Sign up

Export Citation Format

Share Document