scholarly journals Active lane management for intelligent connected vehicles in weaving areas of urban expressway

2021 ◽  
Vol 4 (2) ◽  
pp. 52-67
Author(s):  
Haijian Li ◽  
Junjie Zhang ◽  
Zihan Zhang ◽  
Zhufei Huang
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Group Behavior ◽  
Field Investigation ◽  
Driving Behavior ◽  
Management Control ◽  
Vehicle Group ◽  
Connected Vehicles ◽  
Content Type

Purpose This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future. Design/methodology/approach By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios. Findings The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases. Originality/value Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

scholarly journals Modeling and simulation of intersection quasi-moving block speed guidance based on connected vehicles

2020 ◽  
Vol 3 (2) ◽  
pp. 67-78
Author(s):  
Qing Xu ◽  
Jiangfeng Wang ◽  
Botong Wang ◽  
Xuedong Yan
Keyword(s):  
Traffic Congestion ◽  
High Speed ◽  
Connected Vehicles ◽  
Content Type ◽  
Communication Range ◽  
Proposed Model ◽  
Simulation Results ◽  
The Impact ◽  
Block Section ◽  
Guidance Model

Purpose This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency. By introducing the theory of moving block section for high-speed train control, a speed guidance model based on the quasi-moving block speed guidance (QMBSG) is proposed to direct platoon including human-driven vehicles and connected vehicles (CV) through the intersection coordinately. Design/methodology/approach In this model, the green time of the intersection is divided into multiple block intervals according to the minimal safety headway. Connected vehicles can pass through the intersection by following the block interval using the QMBSG model. The block interval is assigned dynamically according to the traveling relation of HV and CV, when entering the communication range of the intersection. To validate the comprehensive guidance effect of the proposed model, a general evaluation function (GEF) is established. Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Findings Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Also, compared to the single intersection speed guidance model, the GEF value of the QMBSG model improves over 17.1%. To further explore the guidance effect, the impact of sensitivity factors of the CVs’ environment, such as intersection environment, communication range and penetration rate (PR) is analyzed. When the PR reaches 75.0%, the GEF value will change suddenly and the model guidance effect will be significantly improved. This paper also analyzes the impact of the length of block interval under different PR and traffic demands. It is found that the proposed model has a better guidance effect when the length of the block section is 2 s, which facilitates traffic congestion alleviation of the intersection in practice. Originality/value Based on the aforementioned discussion, the contributions of this paper are three-fold. Based on the traveling information of HV/CV and the signal phase and timing plans, the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately, by following the block interval assigned dynamically. Considering comprehensively the indexes of mobility, safety and environment, a GEF is provided to evaluate the guidance effect of vehicles through the intersection. Sensitivity analysis is carried out on the QMBSG model. The key communication and traffic parameters of the CV environment are analyzed, such as path attenuation, PR, etc. Finally, the effect of the length of block interval is explored.

scholarly journals Integrated Traffic Control for Freeways using Variable Speed Limits and Lane Change Control Actions

2019 ◽  
Vol 2673 (9) ◽  
pp. 602-613 ◽  
Author(s):  
Vasileios Markantonakis ◽  
Dimitrios Ilias Skoufoulas ◽  
Ioannis Papamichail ◽  
Markos Papageorgiou
Keyword(s):  
Control Strategy ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Communication Systems ◽  
Feedforward Control ◽  
Control Strategies ◽  
Connected Vehicles ◽  
Variable Speed ◽  
Speed Limits ◽  
Variable Speed Limits

The wide deployment of vehicle automation and communication systems (VACS) in the next decade is expected to influence traffic performance on freeways. Apart from safety and comfort, one of the goals is the alleviation of traffic congestion which is a major and challenging problem for modern societies. The paper investigates the combined use of two feedback control strategies utilizing VACS at different penetration rates, aiming to maximize throughput at bottleneck locations. The first control strategy employs mainstream traffic flow control using appropriate variable speed limits as an actuator. The second control strategy delivers appropriate lane-changing actions to selected connected vehicles using a feedback-feedforward control law. Investigations of the proposed integrated scheme have been conducted using a microscopic simulation model for a hypothetical freeway featuring a lane-drop bottleneck. The results demonstrate significant improvements even for low penetration rates of connected vehicles.

Freight group behavior under freight traffic restriction policy

2017 ◽  
Vol 117 (10) ◽  
pp. 2287-2304 ◽  
Author(s):  
Haoxiong Yang ◽  
Lijun Sun ◽  
Shulin Lan ◽  
Chen Yang
Keyword(s):  
Distribution System ◽  
Traffic Congestion ◽  
Influence Factor ◽  
Simulation Method ◽  
Group Behavior ◽  
Negative Effects ◽  
Content Type ◽  
Freight Traffic ◽  
Restriction Policy ◽  
The Government

Purpose Many cities implement freight traffic restriction policy (FTRP) intending to reduce traffic congestion and air pollution. At the same time, city distribution had some negative effects. The purpose of this paper is therefore to study the freight group behavior under FTRP, and to provide some recommendations for the government. Design/methodology/approach This paper establishes a city distribution system model built by a simulation method of Agent, which includes the complex adaptability of freight individual, event of restriction policy, the influence factor of freight group behavior and its changes from the perspective of restriction policy. The rules of microscopic freight group behavior to macroscopic freight group behavior, the effects on freight group behavior exerted by restriction policy and the dynamic mechanism of freight group behavior are all studied. The model is also simulated with the traffic data of Beijing in China. Findings Theoretical results ensure that restriction of the passport is not the sole reason that may produce illegal trucks, and other measures need to be taken to solve the traffic problems. And in the long run, increasing fines has a greater effect than strengthening supervision frequency on illegal trucks reduction. Originality/value From city distribution perspective, this paper studied freight group behavior under FTRP. This paper also applied the Agent modeling method to build a model of urban distribution system in the FTRP.

scholarly journals Adaptive Traffic Management System using CNN (YOLO)

2021 ◽  
Vol 9 (VI) ◽  
pp. 3726-3732
Author(s):  
B. Sowmya
Keyword(s):  
Real Time ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Object Identification ◽  
Traffic Signal ◽  
Traffic Density ◽  
Loop Control ◽  
Control Framework

The huge number of vehicles on the roadways is making congestion a significant problem. The line longitudinal vehicle waiting to be processed at the crossroads increases quickly, and the traditionally used traffic signals are not able to program it properly. Manual traffic monitoring may be an onerous job since a number of cameras are deployed over the network in traffic management centers. The proactive decision-making of human operators, which would decrease the effect of events and recurring road congestion, might contribute to the easing of the strain of automation.The traffic control frameworks in India are now needed as it is an open-loop control framework, without any input or detection mechanism. Inductive loops and sensors employed in existing technology used to detect the number of passing vehicles. The way traffic lights are adapted is highly inefficient and costly in this existing technology. The aim was to build a traffic control framework by introducing a system for detection ,which gives an input to the existing system (closed loop control system) in order to adapt to the changing traffic density patterns and to provide the controller with a crucial indication for ongoing activities. By this technique, the improvement of the signals on street is extended and thus saves time by preventing traffic congestion. This study proposes an algorithm for real-time traffic signal control, depending on the traffic flow. In reality, the features of competitive traffic flow at the signposted road crossing are used by computer vision and by machine learning. This is done by the latest, real-time object identification, based on convolutional Neural Networks network called You Look Once (YOLO). Traffic signal phases are then improved by data acquired in order to allow more vehicles to pass safely over minimal wait times, particularly the line long and the time of waiting per vehicle.This adjustable traffic signal timer is used to calculate traffic density utilizing YOLO object identification using live pictures of cameras in intervals and adjusts the signal timers appropriately, therefore decreasing the road traffic congestion, ensuring speedier transit for persons, and reducing fuel consumption. The traffic conditions will improve enormously at a relatively modest cost. Inductive loops are a viable but costly approach. This method thereby cuts expenses and outcomes quickly.

scholarly journals Design and Development of Traffic Control System using Image Processing

2021 ◽  
Vol 9 (VI) ◽  
pp. 3247-3252
Author(s):  
G. Kalyan
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Red Light ◽  
Traffic Density ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

Traffic congestion is now a big issue. Although it seems to penetrate throughout the world, urban towns are the ones which are most effected. And it is expanding in nature that it is necessary to understand the density of roads in real time to better regulate signals and efficient management of transport. Various traffic congestions, such as limited capacity, unrestricted demand, huge Red Light waits might occur. While insufficient capacity and unlimited demand are somehow interconnected, their delay in lighting is difficult to encode and not traffic dependant. The necessity to simulate and optimise traffic controls therefore arises in order to better meet this growing demand. The traffic management of information, ramp metering, and updates in real-time has been frequently used in recent years for image processing and monitoring systems. An image processing can also be used for the traffic density estimation. This research describes the approach for the computation of real-time traffic density by image processing for using live picture feed from cameras. It focuses also on the algorithm for the transmission of traffic signals on the road according to the density of vehicles and therefore aims to reduce road congestion, which reduces the number of accidents.

scholarly journals Modeling and simulation of vehicle group lane-changing behaviors in upstream segment of ramp areas under a connected vehicle environment

2019 ◽  
Vol 1 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Haijian Li ◽  
Zhufei Huang ◽  
Lingqiao Qin ◽  
Shuo Zheng ◽  
Yanfang Yang
Keyword(s):  
Traffic Congestion ◽  
Road Safety ◽  
Design Methodology ◽  
Vehicle Group ◽  
Connected Vehicle ◽  
Lane Changing ◽  
Content Type ◽  
Traffic Capacity ◽  
Simulation Results ◽  
Vehicle Technologies

Purpose The purpose of this study is to effectively optimize vehicle lane-changing behavior and alleviate traffic congestion in ramp area through the study of vehicle lane-changing behaviors in upstream segment of ramp areas. Design/methodology/approach In the upstream segment of ramp areas under a connected vehicle environment, different strategies of vehicle group lane-changing behaviors are modeled to obtain the best group lane-changing strategy. The traffic capacity of roads can be improved by controlling group lane-changing behavior and continuously optimizing lane-changing strategy through connected vehicle technologies. This paper constructs vehicle group lane-changing strategies in upstream segment of ramp areas under a connected vehicle environment. The proposed strategies are simulated by VISSIM. Findings The results show that different lane-changing strategies are modeled through vehicle group in the upstream segment of ramp areas, which can greatly reduce the delay of ramp areas. Originality/value The simulation results verify the validity and rationality of the corresponding vehicle group lane-changing behavior model strategies, effectively standardize the driver's lane-changing behavior, and improve road safety and capacity.

scholarly journals Design on Highway Information Publishing System and Benefit Analysis of Traffic Control System

2011 ◽  
Vol 1 ◽  
pp. 343-347
Author(s):  
Wei Li ◽  
Guo Dong Han
Keyword(s):  
Control System ◽  
Public Transportation ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Information Control ◽  
Control Center ◽  
Shared Information ◽  
Traffic Control System ◽  
Information Publishing

With the purpose of offering dynamic information services for road users, the information publishing scheme is proposed based on variable message sign and variable speed limit sign. And the information publishing system shared information control center with public transportation service system is established. The economic benefit of intelligent traffic control system is quantitatively studied by radar map method for the first time. Research shows that intelligent traffic control system has reached ideal-steady state. The research results reduce traffic congestion and improve the highway utilization and traffic management efficiency.

scholarly journals Iot based Smart Traffic Control using IR Sensors

2020 ◽  
Vol 9 (7) ◽  
pp. 486-489
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Smartphone Application ◽  
Video Data ◽  
Software Application ◽  
Road Planning ◽  
Key Issues ◽  
Infrared Cameras ◽  
Smart Traffic

Traffic Congestion is a major problem in many cities in India and other countries. Signal failure, lax regulation and traffic management have contributed to congestion of traffic. Some of the key issues with Indian cities is that the new network cannot be expanded further and that thus the only option left is better management and living standards It is therefore high time the issue of traffic congestion is to be dealt effectively Traffic control approaches include video data processing, infrared cameras, inductive loop tracking, wireless sensor network, etc. In our study, we use an infrared sensor that can be paired with the existing signaling network that can act as a portal to intelligent traffic management. Additionally, a smartphone application is connected to a centralized system that communicates with the local rescue department about a fire explosion site for further action. There's also a software application to provide the smart city's higher authorities with valuable information in graphic formats, which is helpful in future road planning. Automated traffic control and surveillance are essential for the use and maintenance of the highways.

scholarly journals Free Signal Management in Cities Using Density and Average Speed

2020 ◽  
Vol 16 ◽  
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Heavy Traffic ◽  
Road Transport ◽  
Light Signaling ◽  
Dynamic Traffic ◽  
The Czech Republic ◽  
Signaling Device ◽  
Near Future

The article focuses on the issue of congested roads in cities. The problems of heavy traffic both large and smaller towns. Some towns in the Czech Republic do not have built bypasses and so there is a heavy traffic congestion at favorite times. Road transport has become one of the most popular forms of transport. This trend is unlikely to change in the near future. The current market offers dynamic traffic management but not with the appropriate effect. Our proposed method belongs to dynamic traffic control based on real traffic control. The proposed method works in real time with the light signaling device behind the monitoring sections. The function of the proposed method is to extend the free passage of the light-signaling device.

scholarly journals Ubiquitous Vehicular Ad-Hoc Network Computing Using Deep Neural Network with IoT-Based Bat Agents for Traffic Management

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 785
Author(s):  
Srihari Kannan ◽  
Gaurav Dhiman ◽  
Yuvaraj Natarajan ◽  
Ashutosh Sharma ◽  
Sachi Nandan Mohanty ◽  
...  
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Ad Hoc ◽  
Packet Error Rate ◽  
Delivery Ratio ◽  
Network Computing ◽  
Network Nodes ◽  
Real Time Traffic ◽  
Enhance Efficiency

In this paper, Deep Neural Networks (DNN) with Bat Algorithms (BA) offer a dynamic form of traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles across highly congested paths to enhance efficiency, with a lower average latency. The latter is combined with the Internet of Things (IoT) and it moves across the VANETs to analyze the traffic congestion status between the network nodes. The experimental analysis tests the effectiveness of DNN-IoT-BA in various machine or deep learning algorithms in VANETs. DNN-IoT-BA is validated through various network metrics, like packet delivery ratio, latency and packet error rate. The simulation results show that the proposed method provides lower energy consumption and latency than conventional methods to support real-time traffic conditions.

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