Showing papers on "Traffic wave published in 2022"

State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends

Abstract: The effective control and management of traffic at intersections is a challenging issue in the transportation system. Various traffic signal management systems have been developed to improve the real-time traffic flow at junctions, but none of them have resulted in a smooth and continuous traffic flow for dealing with congestion at road intersections. Notwithstanding, the procedure of synchronizing traffic signals at nearby intersections is complicated due to numerous borders. In traditional systems, the direction of movement of vehicles, the variation in automobile traffic over time, accidents, the passing of emergency vehicles, and pedestrian crossings are not considered. Therefore, synchronizing the signals over the specific route cannot be addressed. This article explores the key role of real-time traffic signal control (TSC) technology in managing congestion at road junctions within smart cities. In addition, this article provides an insightful discussion on several traffic light synchronization research papers to highlight the practicability of networking of traffic signals of an area. It examines the benefits of synchronizing the traffic signals on various busy routes for the smooth flow of traffic at intersections.

SWSCAV: Real-time traffic management using connected autonomous vehicles.

Abstract: Traffic management methods aim to increase the infrastructure's capacity to lower congestion levels. Using vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) connectivity technologies, connected autonomous vehicles (CAVs) have the potential to operate as actuators for traffic control. In this study, a CAV-based alternative approach for traffic management is proposed (SWSCAV), and its performance is compared to that of lane control signals (LCS) and variable speed limits (VSL), which are also traffic management systems. When a shockwave is detected due to an incident, the CAVs on the road slow until they reach the speed of the observed shockwave (SWS), according to this proposed procedure. Thus, the incoming traffic flow towards the incident is slowed, preventing the queue behind from extending. In a simulation of the urban mobility (SUMO) environment, the suggested method is evaluated for 4800 scenarios on a three-lane highway by varying the market penetration rate of CAVs in traffic flow, the control distances, the incident lane, and the duration. The proposed method reduces the incidence of density values of over 38 veh/km/lane and 28 veh/km/lane in the vicinity of the incident region by 12.68 and 8.15 percent, respectively. Even at low CAV market penetration rates, the suggested method reduces traffic density throughout the network and in the location of the incident site by twice as much as the LCS system application.

Effect of Mixed Traffic Platooning by Commercial Vehicle Types on Traffic Flow Characteristics of Highways

Abstract: The existence of different types of Commercial Vehicles (CVs) in the shared roadway affects traffic flow characteristics differently from other vehicles. Owing to the uncertain placement and movement of these CVs in both longitudinal and lateral directions, the opportunities for lane changing and overtaking by other vehicles with lower maneuverability decrease, resulting in the formation of platoons. The study's primary aim is to assess the effect of mixed traffic platoons formed by three different classes of CVs on highway traffic speed, flow, and density under two different traffic regimes (regimes A and B). In this study, regime A represents the non-platooning condition, and regime B represents the platooning condition. Bi-directional traffic data was collected from the highway sections in India using an Infra-Red sensor-based device. The critical leading time headway is determined for the different CVs (platoon leaders) based on the mean absolute relative speed of platoons. The speed-flow-density plots are established using the macroscopic fundamental diagrams for the highway sections under regimes A and B to quantify the platooning impacts of CVs on the traffic characteristics. The study findings reveal that the speed at capacity, density at capacity, and traffic capacity decreased significantly due to CVs' influence on the general traffic mix during the mixed traffic platooning conditions. However, this effect was found to be relatively higher during the Heavy Commercial Vehicle operation as a platoon leader compared to Medium Commercial Vehicle and Light Commercial Vehicle as a platoon leader.

Courteous Behavior of Automated Vehicles at Unsignalized Intersections Via Reinforcement Learning

Abstract: The transition from today's mostly human-driven traffic to a purely automated one will be a gradual evolution, with the effect that we will likely experience mixed traffic in the near future. Connected and automated vehicles can benefit human-driven ones and the whole traffic system in different ways, for example by improving collision avoidance and reducing traffic waves. Many studies have been carried out to improve intersection management, a significant bottleneck in traffic, with intelligent traffic signals or exclusively automated vehicles. However, the problem of how to improve mixed traffic at unsignalized intersections has received less attention. In this letter, we propose a novel approach to optimizing traffic flow at intersections in mixed traffic situations using deep reinforcement learning. Our reinforcement learning agent learns a policy for a centralized controller to let connected autonomous vehicles at unsignalized intersections give up their right of way and yield to other vehicles to optimize traffic flow. We implemented our approach and tested it in the traffic simulator SUMO based on simulated and real traffic data. The experimental evaluation demonstrates that our method significantly improves traffic flow through unsignalized intersections in mixed traffic settings and also provides better performance in a wide range of traffic situations compared to the state of the art.

An Analysis of the Catastrophe Model and Catastrophe Characteristics of Traffic Flow Based on Cusp Catastrophe Theory

Abstract: —The state of urban road traffic flow shows discontinuity and jumping phenomenon in the process of running. There was a data gap in the collected traffic flow data. Through the data analysis, it was found that the traffic flow state had the characteristics of multimode, mutation, inaccessibility, divergence and hysteresis, which were similar to the mutation characteristics of the basic model of catastrophe theory when the system state changed. The cusp catastrophe model of traffic flow based on traffic wave theory was established by analyzing the movement process of traffic flow. In this model, the traffic density was taken as the state variable, and traffic flow and wave speed were taken as the control variable. Referring to the basic idea of catastrophe theory, the solution method of the model was given, and the structural stability of the traffic flow state was analyzed. Through the critical equilibrium surface equation, the stability of the extreme value of the system potential function can be analyzed, and the bifurcation set equation when the traffic flow state changed can be obtained, which can be used to determine the critical range of the structural stability of the system. This paper discussed and analyzed the changing trend and constraint relationship among the wave speed, traffic density and traffic flow when the traffic flow state changed suddenly in different running environments. The analysis results were consistent with the actual road traffic flow state. A case was given, and the results showed that the cusp catastrophe model could describe the relationship among the three parameters of traffic flow from three-dimensional space, and could effectively analyze the internal relationship of the parameters when the traffic flow state changed. The validity of the model and analysis method was verified. The goal of this paper is to provide an analysis method for the judgment of urban road traffic state.

The Riemann problem for a traffic flow model on a road with variable widths

Abstract: Abstract We propose and investigate a model describing the traffic flow on a road with variable widths in this paper. The model, which is modified on the Aw–Rascle model, is not conservative because of the source term generated from the real traffic scenarios. The model also takes the stationary wave into considerations in the traffic flow based on the balance laws. We obtain the elementary waves of the new traffic flow model, including rarefaction waves, shock waves, contact discontinuities and particularly stationary waves. The Riemann problems to the system for the traffic flows are solved constructively, which can be further used to design numerical schemes and applied to more complex traffic flows in the future study. Some real traffic flow simulations are given, which verify the effectiveness and versatility of the model.

Study of automatic traffic signal system for chandigarh

Abstract: The increasing number of vehicles on our road intersections has given rise to the problems like road accidents, congestions, conflicts and bottlenecks. These problems can now only be solved by providing an efficient traffic control at intersections and that can be achieved by provision of automated volume-based traffic signal system at intersections for continuous and efficient movement of vehicles through the intersections Chandigarh – the city beautiful – though a modern and well-planned city, is also facing the same traffic problems. Here, the present traffic signals are based on the static feed of time without considering the actual available traffic. This leads to a situation where vehicles wait unnecessarily in one of the lanes while the traffic flow is not up to the considerable amount in the other lane. This paper provides the feasibility of replacing existing traffic signals with a system to monitor the traffic flow automatically in traffic signals where sensors are fixed in which the time feed is made dynamic and automatic by processing the live detections. The paper deals with the feasibility of provision of inductive loop detection-based traffic signals in place of existing Pretimed traffic signals by comparing their performance, suitability and economics. KEYWORDS: Traffic Control, Inductive loop Detector, PCU, Automatic Traffic Control, Intersection,Traffic Field Studies.

A Microscopic Heterogeneous Traffic Flow Model Considering Distance Headway

Abstract: The intelligent driver (ID) model characterizes traffic behavior with a constant acceleration exponent and does not follow traffic physics. This results in unrealistic traffic behavior. In this paper, a new microscopic heterogeneous traffic flow model is proposed which improves the performance of the ID model. The forward and lateral distance headways are used to characterize traffic behavior. The stability of the ID and proposed models is examined over a 1000 m circular road with a traffic disturbance after 30 s. The results obtained show that the proposed model is more stable than the ID model. The performance of the proposed and ID models is evaluated over an 1800 m circular road for 150 s with a platoon of 51 vehicles. Results are presented which indicate that traffic evolves realistically with the proposed model. This is because it is based on the lateral distance headway.

Variable Cell Transmission Model for Mixed Traffic Flow with Connected Automated Vehicles and Human-Driven Vehicles

Abstract: The current research on the mixed traffic flow characteristics of human-driven vehicles (HDVs) and connected automated vehicles (CAVs) mainly focuses on the micro-level. To study the characteristics of the mixed traffic flow from the medium and macro level, this paper proposes a variable cell transmission model (VCTM). First, the fundamental diagram is introduced based on the phenomena of hysteresis of traffic flow. Second, the VCTM with different market penetration rates (MPR) of CAVs is proposed based on the classical cell transmission model (CTM). Then, the effectiveness of VCTM is verified by micro-simulation based on the intelligent driver model (IDM). Finally, some congestion indexes are selected to discuss the characteristics of mixed traffic flow based on the VCTM with an expressway simulation. The results show that the traffic capacity and congestion dissipation capacity gradually are increased with the increase of MPR of CAVs. The homogeneous CAVs traffic flow capacity can reach 1.41 times that of the homogeneous HDVs traffic flow, and the congestion dissipation time can be reduced by 25%. The larger MPR is, the greater the improvement effect is. In addition, compared with CTM, VCTM can reflect the delay, queuing, and dissipation of mixed traffic flow more accurately, which is helpful to capture the evolution mechanism of mixed traffic flow in the future.

Traffic flow at signalized intersections with large volumes of bicycle traffic

Abstract: The popularity of utilitarian bicycling is increasing in many urban areas. As a result, growing volumes of bicycle traffic on road networks have significant impacts on traffic flow and the capacity of vehicular traffic, particularly at intersections. The goal of this paper is to quantify the impact of large volumes of bicycle traffic on the capacity of signalized intersections concerning vehicular streams crossing the intersection, turning right, and turning left. Empirical studies are conducted to gain insight into the speed, acceleration, queue density, queue discharge, and conflict zone occupancy time of bicycle traffic. Data were collected at sites with varying infrastructure designs and bicycle traffic volumes. The results of the empirical studies are used to assess the effects of bicycle infrastructure on traffic efficiency and build, calibrate, and validate microscopic traffic simulation models. The bicycle traffic volume is incrementally increased in the simulation models to supplement the data from the empirical studies. Based on the empirical findings and simulation results, the average queue discharge time per bicyclist based on the facility width is derived and two factors for the reduction in the capacity of vehicular traffic turning left and turning right based on the actual green time ratio and the volume of crossing bicycle traffic are proposed. If a bike box is present on an intersection approach, findings show that crossing bicycle traffic has a negligible effect on the capacity of crossing vehicular traffic, which bicyclists turning left impede vehicular traffic.

Comparing Roundabouts and Signalized Intersections Through Multiple- Model Simulation

Abstract: In modern transportation systems, more and more vehicles result in severe traffic congestion, affecting our daily life and modern logistics. Well-designed traffic infrastructures play an important role in implementing safe and efficient traffic systems. From subjective experience, roundabouts are more efficient than conventional signalized intersections because vehicles do not wait for traffic signals, decreasing which is the main reason for time-loss at signalized crossroads. This paper aims to further investigate the differences between intersections and roundabouts in the capacity of vehicle passing and other performance. Two scenarios with different traffic volumes are considered, including a large volume of traffic flow (2.44 vehicles per second) and a small volume of traffic flow (0.52 vehicles per second). In each scenario, we build six junction models including four intersections with different traffic light time and two roundabouts with different numbers of lanes. Multiple evaluation metrics (i.e., number of passing vehicles over time, mean speed of passing vehicles, mean number of halts per vehicle, mean time-loss per vehicle, and total time for all vehicles to pass) are considered to compare these models’ performance. Results illustrate that roundabouts have a higher capability of vehicle passing than intersections, especially for a large traffic volume. But roundabouts bring more halts per vehicle than signalized intersections when the traffic volume is large. When the volume of traffic flow is small, there is no significant efficiency difference between intersections and roundabouts. These results tend to be applied to future traffic junction designs to improve system efficiency.

A Queuing Model for Mixed Traffic Flows on Highways considering Fluctuations in Traffic Demand

Abstract: Modelling the mixed traffic flows of autonomous vehicles (AVs) and human-driven vehicles (HVs) on highways is challenging. Randomness, fluctuations, and congestion exist in the mixed traffic flows. This paper extends the current literature by proposing an M/G(n)/c/c state-dependent queuing model operating in a random environment. The fluctuating traffic demand is addressed by arrival rates modulated by the random environment. Meanwhile, a Markovian arrival process (MAP) is incorporated to describe the platoons. We investigate the performance of the mixed traffic flow under the I policy (AVs and HVs travel together in all lanes) and the D policy (one lane is designated to AVs). Numerical experiments reveal the following interesting findings: (1) the fluctuation degree of traffic demand, the traffic intensity, and the penetration rate of AVs play essential roles in determining the performance of mixed traffic flows. (2) The I policy should always be adopted if the travel time is more valuable. In terms of output rate, the choice between the I and the D policies depends on the traffic intensity, SCV of arrival rates and penetration rate. (3) A larger penetration rate is required to completely eliminate congestion on a longer highway segment.

Virtual Rings on Highways: Traffic Control by Connected Automated Vehicles

Abstract: This work gives introduction to traffic control by connected automated vehicles. The influence of vehicle control on vehicular traffic and traffic control strategies are discussed and compared. It is highlighted that vehicle-to-everything connectivity allows connected automated vehicles to access the state of the traffic behind them such that feedback can be utilized to mitigate evolving congestions. Numerical simulations demonstrate that such connectivity-based traffic control is beneficial for smoothness and energy efficiency of highway traffic. The dynamics and stability of traffic flow, under the proposed controllers, are analyzed in detail to construct stability charts that guide the selection of stabilizing control gains.

Dynamic Traffic Signal Split Control Method at Pedestrian Crossings

Abstract: In order to facilitate and guarantee the safety of vehicular traffic on roadways, traffic control is crucial. Currently, there is a lot of study on how to effectively alter the control parameters of traffic lights for the aim of facilitating road traffic, but the observation targets of such research are restricted to vehicles. Traffic congestion in urban areas is a severe issue. However, the interference between automobiles and pedestrians creates the actual traffic, making pedestrians a vital aspect to take into account. In this article, we suggest a strategy for parameter-based traffic signal split control that will increase pedestrian traffic by taking both vehicle and pedestrian traffic into account.

Density waves in an improved car-following model under intelligent transportation system environment

Abstract: The intelligent transportation system (ITS) can effectively utilize the existing transportation facilities and improve traffic safety and efficiency. To study and evaluate the dynamic characteristics of traffic flow, a novel car-following model is proposed based on the two-velocity difference model (TVDM) with connected consideration of headway memory and backward looking effect under ITS environment. The linear stability theory is used to acquire the stability condition of the improved model, which shows that the proposed model can effectively strengthen the traffic flow stability. According to the nonlinear theory, the time-dependent Ginzburg–Landau (TDGL) equation and modified Korteweg–de Vries (mKdV) equation are obtained to exhibit the evolution characteristics of traffic flow density wave. At last, numerical simulation is performed to further validate that the improved model can enhance the traffic flow stability and eliminate traffic congestion.

Traffic dynamics with slowdown vehicles based on the traffic wave theory

Abstract: In this paper, we study the macroscopic traffic dynamics and propose models of traffic mean speed and density of each lane under speed drop of connected and autonomous vehicles (CAVs) in three-lane freeway scene in wave propagation perspective. The propagation of macroscopic traffic waves in mixed streams is analyzed to derive functions of macroscopic traffic flow parameters of each lane in different evolution process. Three superposition principles of traffic wave are proposed to analyze compound disturbances in different propagation periods. The experiments are performed in simulation of urban mobility SUMO platform under various CAVs penetration, speed drop of CAV, the proposed model is capable of adequately describing the evolution process of mixed traffic flow after speed drop,

Large-scale traffic flow simulation based on intelligent PSO

Abstract: With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.

Placement of points for recording traffic flow parameters, taking into account minimizing the impact of traffic light objects

Abstract: The paper considers the influence of the location of traffic control zones on the accuracy of the received data. It is established that when they are located in front of intersections with traffic light regulation, it leads to noise of the received data, strengthening of the stochastic component. When solving the problem of placing zones for accounting for traffic flow parameters, they should, if possible, be placed at the beginning of transport links.

Smart city: road traffic evaluation based on traffic flow model

Abstract: In the urban intelligent transportation system, the traffic department can better grasp the current situation of traffic flow through the collection and analysis of road traffic information. In the description of the overall traffic situation, most scholars still rely on the observation data in a certain period of time to give subjective evaluation, and can only roughly describe the overall change of traffic data in a certain period of time on a road. The traffic flow model can be used to simulate the traffic congestion situation more accurately, and combined with the developed evaluation index, any instantaneous traffic congestion situation can be evaluated at multiple points, providing a scientific and effective theoretical basis for the traffic diversion and traffic control of smart cities.

Density Based Traffic Control Techniques-A Review

Abstract: In modern days with the tremendous rise of vehicle numbers on the roadways, traffic jams have been found a massive problem. In the current scenario we can't say that traffic jam is occurring mainly in urban areas, in rural area also traffic jams are increasing. These traffic jams are behind problems like air pollution, noise pollution or delay in time. These traffic jams can't be resolved by only deploying traffic lights in all cities because these lights have fixed intervals of time between red and green lights. Keeping this in mind many attempts were done to change the time interval according to the density of vehicles on the road. This paper summarizes different techniques for traffic management and control systems that can be used for the improvement of the current system.

Development of lane change models through microscopic simulation under mixed traffic

Abstract: The number of motor vehicles and traffic demand is growing in tandem with society's rapid economic development and the quickening process of urbanization. In India, traffic congestion has become the most serious issue. Vehicle's poor lane-changing behaviors have a significant impact on the speed of the traffic system. The lane change behavior was observed in the study with the traffic flow simulation model VISSIM. The purpose of this investigation is to estimate the number of lane changes by simulating them at different volume levels. The study also shows the capacity estimate and its relationship with the lane change. The maximum traffic flow and lane changes were calculated based on the proportions of each vehicle type in the standard car traffic flow. The maximum number of lane change models for known traffic compositions on 4-lane, 6-lane, and 8-lane divided highways has been developed. According to the results, the number of observed lane changes depends on the volume of traffic and the number of lanes provided for a particular direction of travel. The composition and vehicle types also have a significant influence on lane changes and highway capacity, which involves uncertainties in the analysis of traffic flow properties.

Coordinated Traffic Signal Design for Major Intersections in Sylhet City

Abstract: Traffic delay is a very common phenomenon in urban intersections where the traffic volume on the approach roads is high. Coordinated traffic signals based on real-time traffic can be very useful for minimizing intersection traffic delays. Therefore, this study is aimed to investigate the prospect of a coordinated signal system for the busiest and most closely spaced intersections (Ambarkhana, Chowhatta, and Zindabazar) in the Sylhet city of Bangladesh. This signal system will allow a continuous flow of traffic through moving vehicles between successive coordinated intersections so that the vehicles that running at the design speed can pass through the coordinated intersections without a significant halt. An isolated signal is designed for three intersections and linked up to them based on offset values (time to travel from one intersection to another). Phase splits were adjusted using the Time-Space diagram.

Automation of Traffic Control Systems with Deep Q-Learning Network

Abstract: Traffic signal infrastructure is used to manage the flow of traffic and vehicle congestion that occurs on the road. In cities with high population densities and smart cities, traffic has been extremely hard to control, and vehicle delay times have been immense. High congestion due to traffic has caused an increase in the delay times of passengers and the need for an effective traffic control system. Thus, there is a need for automated traffic control systems. Tampering and altering the signals may cause traffic jams and can cause a delay due to signals displaying an incorrect phase for a particular intersection or junction. By implementing a Deep Q-Learning (DQN) network, the traffic signals can be automated with more efficiency. This algorithm will take into account the cumulative number of vehicles at the signal, and the vehicles' delay time and identify which signal phase to output. Instead of waiting for a full phase cycle to switch signals, the signals can change phases reactively to real-world traffic. Data about the vehicle's presence, vehicle count, and delay time are collected to predict the correct phase of a given signal. The significance of an attack can be quantified by a delay in travel time caused to a vehicle on the road. The model will take the vehicles' presence in each lane of the road from SUMO and identify which signal phase to produce as output, so the cumulative vehicle time can be minimized, i.e. delay time of vehicles at any instance is reduced. The machine learning model will predict which phase to change to, and the reinforcement learning algorithm will determine if the output has resulted in a desirable condition and provide arbitrary rewards as output. Implementing the DQN algorithm in place of the round-robin algorithm has reduced the cumulative vehicle delay time which is the time taken to reach a given destination and vehicle queue length.