scholarly journals OPTIMIZATION OF INTERSECTION CONTROL SCHEME CONSIDERING PHASE-MOVEMENT-COMBINATION UNDER AUTOMATED VEHICLES ENVIRONMENT

Transport ◽  
2020 ◽  
Vol 0 (0) ◽  
pp. 1-17
Author(s):  
Wenbin Xiao ◽  
Shunying Zhu ◽  
Daobin Wang ◽  
Wei Liu
Keyword(s):  
Optimization Method ◽  
Discrete Mathematics ◽  
Signal Control ◽  
Optimal Timing ◽  
Automated Vehicles ◽  
Timing Model ◽  
Control Scheme ◽  
Vehicle Delay ◽  
Phase Combination ◽  
Intersection Control

For signal control intersection, the Phase-Movement-Combination (PMC) styles could directly impact the control performance of the signal scheme. Automated vehicles use mechatronics technology to drive autonomously and safely according to the predetermined lane trajectory, which caused the phase movement combination and Phase Combination (PC) schemes become more and more complicated. Therefore, this paper proposed a method to consider the extensive PMC styles by fractionalizing movement compatibility relationships, and used discrete mathematics to calculate overall Feasible Phase Combination (FPC) schemes according to the requirements of the signal phase. A corresponding optimal timing model was also established for FPC schemes by minimizing the average vehicle delay and maximizing the intersection capacity. Results were compared against the conventional PC schemes for a variety of demand scenarios. It was concluded that the proposed signal control optimization method was effective to optimize the intersection control scheme, depending on different demand scenarios.

scholarly journals Intersection signal timing optimization considering the travel safety of the elderly

2019 ◽  
Vol 11 (12) ◽  
pp. 168781401989721 ◽  
Author(s):  
Changxi Ma ◽  
Pengfei Liu
Keyword(s):  
Genetic Algorithm ◽  
Control Method ◽  
The Elderly ◽  
Calibration Method ◽  
Optimization Method ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Improved Genetic Algorithm ◽  
Signal Ratio ◽  
Vehicle Delay

With the rapid growth of the elderly population in China, the proportion of middle-aged and elderly pedestrians crossing streets at signalized intersections has been increasing gradually, mandating the consideration of the crossing characteristics and travel safety of the elderly in signal matching. This article proposes a new signal control parameter optimization method for intersections based on an improved genetic algorithm. According to the crossing characteristics and travel safety of the elderly, the average vehicle delay is used as the control objective, and the green signal ratio and cycle time are used as control variables. The improved genetic algorithm with an improved fitness calibration method and an adaptive cross-mutation function is used to solve the signal control model. Based on the optimization analysis of traffic signal control parameters at a traffic intersection, the study shows that the improved signal control method can effectively reduce the average vehicle delay compared to the Webster algorithm and the traditional genetic algorithm.

scholarly journals Research on Phase Combination and Signal Timing Based on Improved K-Medoids Algorithm for Intersection Signal Control

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Guojiang Shen ◽  
Xiangyu Zhu ◽  
Wei Xu ◽  
Longfeng Tang ◽  
Xiangjie Kong
Keyword(s):  
Programming Model ◽  
Signal Control ◽  
Signal Timing ◽  
Timing Optimization ◽  
Traffic Capacity ◽  
Intersection Signal Control ◽  
Vehicle Delay ◽  
Phase Combination ◽  
Bilevel Programming Model ◽  
Selection Of

Aiming at the problem of intersection signal control, a method of traffic phase combination and signal timing optimization based on the improved K-medoids algorithm is proposed. Firstly, the improvement of the traditional K-medoids algorithm embodies in two aspects, namely, the selection of the initial medoids and the parameter k, which will be applied to the cluster analysis of historical saturation data. The algorithm determines the initial medoids based on a set of probabilities calculated from the distance and determines the number of clusters k based on an exponential function, weight adjustment, and elbow ideas. Secondly, a phase combination model is established based on the saturation and green split data, and the signal timing is optimized through a bilevel programming model. Finally, the algorithm is evaluated over a certain intersection in Hangzhou, and results show that this algorithm can reduce the average vehicle delay and queue length and improve the traffic capacity of the intersection in the peak hour.

Dynamic combination control of phase movement at signal intersection under the automated vehicle environment

2020 ◽  
Vol 39 (3) ◽  
pp. 3647-3664
Author(s):  
Wenbin Xiao ◽  
Shunying Zhu
Keyword(s):  
Data Exchange ◽  
Control Method ◽  
Arrival Rate ◽  
Control Mode ◽  
Combination Method ◽  
Discrete Mathematics ◽  
Signal Control ◽  
Control Effectiveness ◽  
Intersection Signal Control ◽  
Phase Combination

With the continuous perfection of the technology of automated vehicles (AV), data exchange can be conveniently carried out between different vehicles and infrastructures, which makes it easier to collect different types of traffic parameters. Therefore, under AV environment, the vehicle status can be determined to obtain the periodic arrival rate of movements and a more efficient control strategy can be designed. The combination styles of phase movement (PM), an important factor of the signal control, will also become more complicated for intersection signal control. The current methods about the PM combination styles only considered two kinds of movement combination styles, and cannot get the extensive phase combination (PC) schemes in AV environment. This paper documents a new PM combination method by fractionalized movement compatibility relations, and uses discrete mathematics to calculate overall PC schemes. Then, a PM dynamic combination control method is proposed to optimize cyclically signal control. The analysis results of numerical tests showed that the average vehicle of the proposed method is reduced by 6.9 % and 14.5 % for 20 signal cycles, respectively, and the total throughput can be increased by 4.3% and 7.8%, respectively, compared with the dynamic timing control mode and the fixed control mode. Results show that the proposed method could significantly improve intersection control effectiveness.

Optimal Model Reference Control Scheme Design for Nonlinear Strict-Feedback Systems

2020 ◽  
Vol 38 (9A) ◽  
pp. 1342-1351
Author(s):  
Musadaq A. Hadi ◽  
Hazem I. Ali
Keyword(s):  
Reference Model ◽  
Feedback System ◽  
Optimization Method ◽  
Feedback Systems ◽  
Model Reference ◽  
Scheme Design ◽  
Model Reference Control ◽  
Control Scheme ◽  
Lyapunov Stability Analysis ◽  
Strict Feedback

In this paper, a new design of the model reference control scheme is proposed in a class of nonlinear strict-feedback system. First, the system is analyzed using Lyapunov stability analysis. Next, a model reference is used to improve system performance. Then, the Integral Square Error (ISE) is considered as a cost function to drive the error between the reference model and the system to zero. After that, a powerful metaheuristic optimization method is used to optimize the parameters of the proposed controller. Finally, the results show that the proposed controller can effectively compensate for the strictly-feedback nonlinear system with more desirable performance.

Development and Evaluation of Cooperative Intersection Management Algorithm under Connected and Automated Vehicles Environment

2021 ◽  
pp. 036119812199458
Author(s):  
Slobodan Gutesa ◽  
Joyoung Lee ◽  
Dejan Besenski
Keyword(s):  
Travel Time ◽  
Information Exchange ◽  
Fixed Time ◽  
Optimization Method ◽  
Time Signal ◽  
Market Penetration ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Concept Evaluation ◽  
Intersection Management

Recent technological advancements in the automotive and transportation industry established a firm foundation for development and implementation of various connected and automated vehicle solutions around the globe. Wireless communication technologies such as the dedicated short-range communication protocol are enabling information exchange between vehicles and infrastructure. This research paper introduces an intersection management strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method. Trajectory-Driven Optimization for Automated Driving provides an optimal trajectory for automated vehicles based on current vehicle position, prevailing traffic, and signal status on the corridor. All inputs are used by the control algorithm to provide optimal trajectories for automated vehicles, resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. The concept evaluation through microsimulation reveals that, even with low market penetration (i.e., less than 10%), the technology reduces overall travel time of the corridor by 2%. Further increase in market penetration produces travel time and fuel consumption reductions of up to 19.5% and 22.5%, respectively.

scholarly journals Investigating the Applicability of Upstream Detection Strategy at Pedestrian Signalised Crossings

2017 ◽  
Vol 29 (5) ◽  
pp. 503-510 ◽  
Author(s):  
Sitti A Hassan ◽  
Nick B Hounsell ◽  
Birendra P Shrestha
Keyword(s):  
Traffic Control ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Traffic Flows ◽  
Detection Strategy ◽  
Vehicle Delay ◽  
Simulation Results ◽  
The Uk ◽  
User Friendly

In the UK, the Puffin crossing has provision to extend pedestrian green time for those who take longer to cross. However, even at such a pedestrian friendly facility, the traffic signal control is usually designed to minimise vehicle delay while providing the crossing facility. This situation is rather contrary to the current policies to encourage walking. It is this inequity that has prompted the need to re-examine the traffic control of signalised crossings to provide more benefit to both pedestrians and vehicles. In this context, this paper explores the possibility of implementing an Upstream Detection strategy at a Puffin crossing to provide a user friendly crossing. The study has been carried out by simulating a mid-block Puffin crossing for various detector distances and a number of combinations of pedestrian and traffic flows. This paper presents the simulation results and recommends the situations at which Upstream Detection would be suitable.

Application of Connected and Automated Vehicles in a Large-Scale Network by Considering Vehicle-to-Vehicle and Vehicle-to-Infrastructure Technology

2020 ◽  
pp. 036119812096310
Author(s):  
Md Hasibur Rahman ◽  
Mohamed Abdel-Aty
Keyword(s):  
Traffic Safety ◽  
Control Algorithm ◽  
Large Scale ◽  
Signal Control ◽  
Market Penetration ◽  
Automated Vehicles ◽  
Large Scale Network ◽  
Vehicle To Vehicle ◽  
Scale Network ◽  
Vehicle To Infrastructure

Application of connected and automated vehicles (CAVs) is expected to have a significant impact on traffic safety and mobility. Although several studies evaluated the effectiveness of CAVs in a small roadway segment, there is a lack of studies analyzing the impact of CAVs in a large-scale network by considering both freeways and arterials. Therefore, the objective of this study is to analyze the effectiveness of CAVs at the network level by utilizing both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. Also, the study proposed a new signal control algorithm through V2I technology to elevate the performance of CAVs at intersections. A car-following model named cooperative adaptive cruise control was utilized to approximate the driving behavior of CAVs in the Aimsun Next microsimulation environment. For the testbed, the research team selected Orlando central business district area in Florida, U.S. To this end, the impacts of CAVs were evaluated based on traffic efficiency (e.g., travel time rate [TTR], speed, and average approach delay, etc.) and safety surrogates (e.g., standard deviation of speed, real-time crash-risk models for freeways and arterials, time exposed time-to-collision). The results showed that the application of CAVs reduced TTR significantly compared with the base condition even with the low market penetration level. Also, the proposed signal control algorithm reduced the approach delay for 94% of the total intersections present in the network. Moreover, safety evaluation results showed a significant improvement of traffic safety in the freeways and arterials under CAV conditions with different market penetration rates.

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