scholarly journals Junction Management for Connected and Automated Vehicles: Intersection or Roundabout?

2021 ◽  
Vol 13 (16) ◽  
pp. 9482
Author(s):  
Yuanyuan Wu ◽  
Feng Zhu
Keyword(s):  
Green Light ◽  
Traffic Signals ◽  
Signal Control ◽  
Automated Vehicles ◽  
Average Delay ◽  
Theoretical Derivation ◽  
Traffic Lights ◽  
Average Control ◽  
Vehicle Trajectory ◽  
Conventional Signal

The concept of signal-free management at road junctions is tailored for Connected and Automated Vehicles (CAVs), in which the conventional signal control is replaced by various right-of-way assignment policies. First-Come-First-Served (FCFS) is the most commonly used policy. In most proposed strategies, although the traffic signals are replaced, the organization of vehicle trajectory remains the same as that of traffic lights. As a naturally signal-free strategy, roundabout has not received enough attention. A key motivation of this study is to theoretically compare the performance of signalized intersection (I-Signal), intersection using FCFS policy (I-FCFS), roundabout using the typical major-minor priority pattern (R-MM), and roundabout adopting FCFS policy (R-FCFS) under pure CAVs environment. Queueing theory is applied to derive the theoretical formulas of the capacity and average delay of each strategy. M/G/1 model is used to model the three signal-free strategies, while M/M/1/setup model is used to capture the red-and-green light switch nature of signal control. The critical safety time gaps are the main variables and are assumed to be generally distributed in the theoretical derivation. Analytically, I-Signal has the largest capacity benefiting from the ability to separate conflict points in groups, but in some cases it will have higher delay. Among the other three signal-free strategies, R-FCFS has the highest capacity and the least average control delay, indicating that the optimization of signal-free management of CAVs based on roundabout setting is worthy of further study.

A Smooth Flow of Traffic Circle Model

2011 ◽  
Vol 50-51 ◽  
pp. 54-58
Author(s):  
Nan Ji ◽  
Jie Zhang ◽  
Yan Gao
Keyword(s):  
Delay Time ◽  
Green Light ◽  
Mathematic Model ◽  
Simulation Software ◽  
Signal Control ◽  
Average Delay ◽  
Smooth Flow ◽  
Set Up ◽  
Control Traffic ◽  
Circle Model

This article sets up mathematic model for the traffic circle to determine how best to control traffic flow. In order to make the traffic at the circle intersection smooth in maximum, this model figures out the largest traffic capacity through Wardrop’s formula. When the signal control is needed, a linkage time solving model is set up, which proves the number of seconds of every green light and work out the delay time. At last, the simulation software VISSIM is used for an example to work out the average delay time under the signal control. The result matches with this model.

Perancangan Sistem Kontrol Lampu Lalulintas Cerdas Dengan Menggunakan Mikrokontroler dan Kamera

Jurnal MIPA ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 200
Author(s):  
Tjerie Pangemanan ◽  
Arnold Rondonuwu
Keyword(s):  
Real Time ◽  
Digital Image ◽  
Red Light ◽  
Green Light ◽  
Processing Method ◽  
Traffic Lights ◽  
Traffic System ◽  
Road Users ◽  
Adjustment System ◽  
System Time

Masalah lalu lintas  merupakan salah satu  masalah yang sangat sulit diatasi dengan hanya menggunakan system waktu (timer). Oleh sebab itu diperlukan suatu system pengaturan otomatis yang bersifat real-time sehingga waktu pengaturan lampu lalu lintas dapat disesuaikan dnegan keadaan di lapangan. Penelitian ini bertujuan mengembangkan suatu simulasi sistem yang mampu mengestimasi panjang antrian kendaraan menggunakan metoda pengolahan citra digital hanya dengan menggunakan satu kamera untuk dijadikan parameter masukan  dalam menghitung lama waktu nyala lampu merah dan lampu hijau. Oleh karena itu, sistem lalulintas sangatlah diperlukan, sebagai sarana dan prasarana untuk menjadikan lalulintas lancar, aman, bahkan sebagai media pembelajaran disiplin bagi masyarakat pengguna jalan raya. Penelitian ini penulis menggunakan sistem pengontrolan berbasis citra digital dimana camera sebagai sensor. Untuk aplikasi dari  semua metode dalam penelitian ini digunakan Microcontroller AurdinoTraffic problems is one of the problems that is very difficult to overcome by only using the system time (timer). Therefore we need an automatic real-time adjustment system so that the time settings for traffic lights can be adjusted according to the conditions on the ground. This study aims to develop a system simulation that is able to estimate the length of the vehicle queue using a digital image processing method using only one camera to be used as input parameters in calculating the length of time the red light and green light. Therefore, the traffic system is very necessary, as a means and infrastructure to make traffic smooth, safe, even as a medium for disciplined learning for road users. In this study the authors used a digital image-based control system where the camera as a sensor. For the application of all methods in this study, Aurdino Microcontroller is used

scholarly journals An Optimization Model of Multi-Intersection Signal Control for Trunk Road under Collaborative Information

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xun Li ◽  
Zhengfan Zhao ◽  
Li Liu ◽  
Yao Liu ◽  
Pengfei Li
Keyword(s):  
Optimization Model ◽  
Delay Time ◽  
Traffic Simulation ◽  
Simulation Software ◽  
Transmission Model ◽  
Signal Control ◽  
Cell Transmission Model ◽  
Average Delay ◽  
Main Trunk ◽  
Average Delay Time

We proposed a signal control optimization model for urban main trunk line intersections. Four-phase intersection was analyzed and modeled based on the Cell Transmission Model (CTM). CTM and signal control model in our study had both been improved for multi-intersections by three-phase theory and information-exchanging. To achieve a real-time application, an improved genetic algorithm (GA) was proposed finally, the DISCO traffic simulation software was used for numerical simulation experiment, and comparisons with the standard GA and CTM were reported in this paper. Experimental results indicate that our searching time is less than that of SGA by 38%, and our method needs only 1/3 iteration time of SGA. According to our DISCO traffic simulation processing, compared with SGA, if the input traffic flow is changed from free phase to synchronized phase, for example, less than 900 vel/h, the delay time can reduce to 87.99% by our method, and the minimum delay time is 77.76% of existing method. Furthermore, if input traffic volume is increased to 1200 vel/h or more at the synchronized phase, the summary and minimum values of average delay time are reduced to 81.16% and 75.83%, respectively, and the average delay time is reduced to 17.72 seconds.

DETECTION OF TRAFFIC SIGNALS USING COLOR SEGMENTATION AND A RADIAL SYMMETRY DETECTOR

2021 ◽  
pp. 25-33
Author(s):  
Р.М. Шакирзянов
Keyword(s):  
Traffic Signals ◽  
Radial Symmetry ◽  
Unmanned Vehicles ◽  
Color Segmentation ◽  
Morphological Operations ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Lights ◽  
Emergency Situations ◽  
Road Signs

В настоящее время широкое распространение получают беспилотные системы управления различными транспортными средствами, в том числе автомобилями. Управление беспилотным автомобилем предполагает решение задач, связанных с распознаванием объектов дорожной обстановки: пешеходов, автомобилей, препятствий (в виде ям, кочек, столбов, деревьев, зданий и т.д.), дорожных знаков, разметки, светофоров. Предложен алгоритм решения задачи обнаружения и распознавания сигналов светофоров круглой формы. Для решения этой задачи задействованы: быстрое преобразование радиальной симметрии, цветовая сегментация, морфологические операции. Особенностью алгоритма является то, что области расположения световых сигналов предварительно определяются по цветовому признаку с последующим уточнением формы и положения объектов на изображении. На основе предложенного метода было разработано программное обеспечение для обнаружения сигналов светофоров на фотоснимках. Программное обеспечение было протестировано на общедоступной базе изображений, содержащей светофоры. Предлагаемый алгоритм показал работоспособность, он может быть расширен в части типов распознаваемых сигналов и применён в составе систем управления беспилотными транспортными средствами, а также в составе систем помощи водителю для решения задач по предупреждению опасных и аварийных ситуаций на транспорте Currently, unmanned systems for controlling various vehicles, including cars, are becoming widespread. Driving an unmanned vehicle involves solving problems related to the recognition of traffic objects: pedestrians, cars, obstacles (in the form of holes, bumps, poles, trees, buildings, etc.), road signs, markings, traffic lights. An algorithm for solving the problem of detecting and recognizing circular traffic signals is proposed. To solve this problem, the following are involved: rapid transformation of radial symmetry, color segmentation, morphological operations. A feature of the algorithm is that the areas of the location of the light signals are preliminarily determined by color, followed by the refinement of the shape and position of objects in the image. Based on the proposed method, software was developed for detecting traffic signals in photographs. The software was tested on a publicly available database of images containing traffic lights. The proposed algorithm has shown its efficiency, it can be expanded in terms of the types of signals recognized and used as part of control systems for unmanned vehicles, as well as part of driver assistance systems for solving problems to prevent dangerous and emergency situations

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.

scholarly journals Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

2020 ◽  
Vol 14 (02) ◽  
pp. 196 ◽  
Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Aberrahim Hasbi
Keyword(s):  
Road Traffic ◽  
Green Light ◽  
Optimal Solution ◽  
Ant Colony ◽  
Traffic Data ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.

scholarly journals Urban Traffic Signal Control Based on Multiobjective Joint Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yongrong Wu ◽  
Yijie Zhou ◽  
Yanming Feng ◽  
Yutian Xiao ◽  
Shaojie He ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing Algorithm ◽  
Urban Traffic ◽  
Joint Optimization ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Signal Timing ◽  
Timing Optimization ◽  
Average Delay ◽  
Annealing Algorithm

This paper proposes two algorithms for signal timing optimization of single intersections, namely, microbial genetic algorithm and simulated annealing algorithm. The basis of the optimization of these two algorithms is the original timing scheme of the SCATS, and the optimized parameters are the average delay of vehicles and the capacity. Experiments verify that these two algorithms are, respectively, improved by 67.47% and 46.88%, based on the original timing scheme.

scholarly journals Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gerardo Hernandez-Oregon ◽  
Mario E. Rivero-Angeles ◽  
Juan C. Chimal-Eguía ◽  
Arturo Campos-Fentanes ◽  
Jorge G. Jimenez-Gallardo ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Low Cost ◽  
Red Light ◽  
Green Light ◽  
Mathematical Expression ◽  
Traffic Light ◽  
Safe Driving ◽  
Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

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