Set Of Traffic Lights Research Articles

Map‐matching for cycling travel data in urban area

AbstractTo promote urban sustainability, many cities are adopting bicycle‐friendly policies, leveraging GPS trajectories as a vital data source. However, the inherent errors in GPS data necessitate a critical preprocessing step known as map‐matching. Due to GPS device malfunction, road network ambiguity for cyclists, and inaccuracies in publicly accessible streetmaps, existing map‐matching methods face challenges in accurately selecting the best‐mapped route. In urban settings, these challenges are exacerbated by high buildings, which tend to attenuate GPS accuracy, and by the increased complexity of the road network. To resolve this issue, this work introduces a map‐matching method tailored for cycling travel data in urban areas. The approach introduces two main innovations: a reliable classification of road availability for cyclists, with a particular focus on the main road network, and an extended multi‐objective map‐matching scoring system. This system integrates penalty, geometric, topology, and temporal scores to optimize the selection of mapped road segments, collectively forming a complete route. Rotterdam, the second‐largest city in the Netherlands, is selected as the case study city, and real‐world data is used for method implementation and evaluation. Hundred trajectories were manually labelled to assess the model performance and its sensitivity to parameter settings, GPS sampling interval, and travel time. The method is able to unveil variations in cyclist travel behavior, providing municipalities with insights to optimize cycling infrastructure and improve traffic management, such as by identifying high‐traffic areas for targeted infrastructure upgrades and optimizing traffic light settings based on cyclist waiting times.

Traffic Light Control in Vehicular Network Systems using Fuzzy Logic

Vehicular concentration is getting worse in big and developed cities as we approach the year 2020, creating a challenge. Accurate traffic signal management is a key to efficient free traffic movement and increasing transport security levels. It is thus important to have traffic lights that change with the traffic intensity information that is collected in real-time. Thus, the objective of this study is to design a viable traffic signal control algorithm that would cause minimal delay to drivers. Building on the basis of fuzzy logic, the approach sets input attributes like the volume of the street and the queue of vehicles to identify the right traffic light settings. Performance criteria for evaluation include the average waiting time of the vehicles, and the findings of simulations in this regard show 21.7 seconds, which is faster than the benchmark formula of 25 seconds. This improvement is attributed to the fact that the fuzzy control system is adjustable.

Research on traffic light setting based on single objective nonlinear programming

Research on traffic light setting based on single objective nonlinear programming

Application of graph theory and webster method in traffic light settings at the tulip intersection in kefamenanu city

Application of graph theory and webster method in traffic light settings at the tulip intersection in kefamenanu city

ANALISIS KINERJA SIMPANG TAK BERSINYAL PADA BUNDARAN MENGGUNAKAN SOFTWARE PTV VISSIM 9.0 DENGAN METODE MKJI 1997 (Studi kasus Bundaran Cunda Jalan Merdeka Timur, Jalan Medan-Banda Aceh)

Congestion and delays often occur in several sections and intersections of Lhokseumawe City roads. Currently the City of Lhokseumawe has implemented a regional traffic control system at several intersections, but at the Cunda roundabout, Jalan Merdeka Timur (direction out of town), Jalan Medan - Banda Aceh (National Cross Road), which does not yet have traffic control or signs. other warnings causing traffic jams. This research was conducted at the Cunda Roundabout in Lhokseumawe City with the aim of seeing the condition and performance of the roundabout. The data needed in this study include vehicle volume characteristics, road geometry and other secondary data. The method used for this research is the 1997 Indonesian Road Capacity Manual and a 3-dimensional simulation based on Vissim. The results of the analysis show that the peak hour on Monday at 17.00-18.00 WIB is 7616 vehicles/hour with a degree of saturation of 1.104, based on MKJI the DS value for roundabouts < 0.75, the roundabout performance is no longer able to accommodate traffic loads and long queues. , especially from Jalan Merdeka Timur and Jalan Medan – Banda Aceh. After re-planning the roundabout from unsignaled to signaled by adding traffic light settings, so that a better degree of saturation is obtained, which is 0.78. The obtained value of the degree of saturation indicates that the intersection is not close to saturation, and the performance is starting to stabilize with a value of DS is still smaller than 0.85 (the 1997 MKJI requirement for signalized intersections), so the roundabout performance becomes more effective.

Minimizing Intersection Waiting Time: Proposal of a Queue Network Model Using Kendall’s Notation in Panama City

The paper presents a proposed queuing model based on Kendall’s notation for the intersection of two streets in Panama City (53 East and 56 East). The proposed model is based on a set of traffic lights that controls the flow of vehicles at the intersection according to a predetermined schedule. The model analyzes the stability of the system and simulations are performed to evaluate its performance. The main objective of the paper is to optimize the vehicle flow by minimizing the waiting time for passage. In the study, it was observed that the current traffic light system on Calle 50 (50th Street) is unstable and oversaturated during weekdays, which generates large vehicle queues with no estimated exit times. It was proposed to increase the system capacity to 1300 vehicles per hour to achieve reasonable stability and provide a solution to improve traffic signal timing on 50th Street. The need to increase the system capacity has been demonstrated and an optimal value has been suggested. The evaluation of other models and the use of AI can further strengthen the system and improve the prediction accuracy in different traffic scenarios.

Optimization Models for Urban Traffic Management

The main control tool for traffic management in urban areas is traffic light settings. The goal is to decrease the queue lengths at intersections. Usually, the duration of the green light of the traffic light is used for control. The control approach is based on the so-called “store-and-forward” model. However, this model does not reflect the stochastic nature of traffic dynamics. This study presents a model with some probabilistic conditions approximating real traffic behavior. An additional contribution concerns the definition of a bi-level optimization model that simultaneously optimizes the green light and traffic light cycle duration of an urban network of four intersections. Three traffic management optimization problems are defined and solved. Their solutions are graphically illustrated and commented on. Bi-level optimization outperforms by giving lower values of queue lengths compared to classical and stochastic nonlinear optimization problems in the considered network.

An analytical model for a tandem of two traffic-light intersections under semi-actuated and fixed control

With increasing congestion in urban areas, it is important to characterise existing traffic control policies in terms of their performance and their optimal settings. In this paper, we propose a queueing model for traffic-light networks under fixed and semi-actuated control. In our model, we explicitly consider slow-departing vehicles in the beginning of a green period and the offsets between intersections. Our approach proves to be both accurate and fast compared to traffic microsimulation, allowing us to optimise the traffic-light settings and offsets.By analysing our model for two intersections in tandem, we show the important differences between semi-actuated and fixed controls. We observe that semi-actuated control is better for the average delay in comparison to fixed control when the main road has the same or a higher load than the crossing roads. If the loads are similar, the results of both types of control are close, and it may be advisable to use fixed control to avoid additional costs. The optimal traffic-light settings are shown to heavily depend on the type of control. For example, the effect of offsets in case of semi-actuated control is minor when the loads are relatively low, while the performance of fixed control may significantly vary depending on the offset between the intersections for any load.

Traffic Light Control System Design Using Omron PLC With Ladder Diagram Method

At this time, traffic congestion is a problem that many big cities face, especially at intersections. Traffic jams at intersections occur a lot because they are caused by the traffic light regulation system that is not in accordance with the traffic light settings which can be changed at any time. The design of the traffic light simulation control program is deviated by four. The program is made with 4 models, namely the all-light flashing model, the flashing yellow light model, and a different one-way model. The current traffic light regulation mostly uses a fixed time setting system where the lights are set to work on a fixed time basis, regardless of the ups and downs of traffic flow. Therefore, offered a detector system (traffic actuated) by utilizing PLC (programmeble logic controller) as a controller. This research is made a simulation tool with PLC Omron. The working process of this tool is in the form of sending input from sensors installed on the road, where this sensor detects the presence or absence of vehicles.

Real-Time Traffic Flow Controls at Signalised Intersections: A Case Study of the Said-Jawda intersection in Karbala

As the problem of urban traffic congestion increases, the need for advanced technology and equipment to be introduced for the improvement of traffic control also increases. Traffic problems have worsened last years due to significant increases in the number of vehicles on the roads and the limited availability of resources in the current infrastructure. The easiest way to control traffic lights is to use timer for each phase; however, another way is to use electronic sensors to detect vehicles to supply the required traffic signals for a given cycle. To enable effective traffic flow through a signalised intersection, this study proposes a system for controlling traffic lights that detects vehicles using videos and imaging techniques instead of electronic sensors embedded in the pavement. Four cameras were installed at a height of three metres on the four approaches to a set of traffic lights. The captured images were then analysed using digital image processing based on Python to facilitate vehicle detection and traffic condition analysis. The work is thus divided into two segments: data collection and traffic control solution generation. The results indicated that using the proposed automated system could produce more effective traffic control as compared to SIDRA fixed-time controls, with delay reduced within the range 40 to 90% and cycle length reduced by 30 to 65%.

Application of Webster's Method to Optimizing Traffic Lights at the Intersection of Bantul - Nasional III Street, Yogyakarta

Indonesia is a developing country with the fourth largest population in the world. Population in one of the provinces in Indonesia, namely Yogyakarta Special Region. Based on data from the Badan Pusat Statistik (BPS), the Special Region of Yogyakarta reached 3.8 million people in 2018. Of this number, almost one third (1.2 million people) are residents of Sleman. While the region with the next largest population is Bantul with 1 million inhabitants. Increasing population causes the need to move and other needs, as well as activities in the education, office and trade sectors also increase. This increase will also affect transportation by increasing the number of vehicles, but this increase is not in line with the existing traffic light updates. As a result, the capacity of the street section has decreased and caused congestion, for example at the APILL intersection on Bantul-Nasional III Street, Yogyakarta. This shows that the existing traffic light settings are not optimal. Therefore, it is necessary to evaluate the duration of the traffic lights to minimize congestion. This research was conducted to analyze the traffic light system at the APILL intersection on Bantul-Nasional III Street, Yogyakarta using the Webster method. The results of calculations using this method obtained results for the Bantul Street (north), the duration of the green light 30 seconds, yellow 3 seconds and red 28 seconds. For Nasional III Street (East), the duration of the green light is 24 seconds, yellow is 3 seconds and red is 34 seconds. For Bantul Street (south), the duration of the green light is 30 seconds, yellow is 3 seconds and red is 28 seconds. For Nasional III Street (West), the duration of the green light is 24 seconds, yellow is 3 seconds and red is 34 seconds. These results look more optimal than those on the field today.

Implementasi Fuzzy Mamdani Pada Lampu Lalu Lintas Secara Adaptif Untuk Meminimalkan Waktu Tunggu Pengguna Jalan

Pengaturan nyala lampu lalu lintas merupakan salah satu upaya yang digunakan untuk dapat mengatur laju kendaraan di jalan raya. Pada kenyataannya volume kendaraan semakin meningkat, dan kemacetan tidak dapat terelakan. Pengaturan lampu lalu lintas berdasarkan fase waktu yang bersifat tetap/statis, kurang mampu berfungsi secara baik dalam mengurai kemacetan, mengingat setiap sudut jalan memiliki kepadatan kendaraan yang berubah-ubah. Maka perlu adanya optimasi terhadap pengaturan nyala lampu lalu lintas di persimpangan jalan raya agar dapat meminimalisasi waktu tunggu pengguna jalan. Dalam makalah ini dibahas pembuatan simulasi sistem kontrol yang dapat menentukan durasi nyala lampu lalu lintas secara adaptif pada persimpangan jalan raya menggunakan algoritma fuzzy mamdani. Penentuan nyala lampu lalu lintas ditentukan oleh parameter jumlah kendaraan mobil, motor, dan lebar jalan. Dari hasil pengujian dengan kondisi parameter yang berbeda dapat diperoleh nyala lampu merah yang berubah secara adaptif menyesuaikan kondisi yang terjadi pada jalan raya.

Robust Signal Control of Exit Lanes for Left-Turn Intersections With the Consideration of Traffic Fluctuation

Traffic throughput at intersections can be improved by using exit lanes for left-turning (EFL), tidal flow lanes near an intersection, which has been recently introduced. This paper considers the operational robustness of the EFL intersection in relation to the control scheme applied to the traffic light setting. For safety and efficiency, it is important that the tidal lanes are emptied before traffic in the opposing direction uses these lanes. Hence, the signal control should not only be optimized for the mean value but be robust for all kinds of fluctuations. This paper formulates a traffic control scheme using robust optimization, i.e. an optimization scheme which explicitly accounts for extreme events. The fluctuation of traffic is considered from three aspects: the distribution of traffic demand, the distribution of base saturation flow rate, and the distribution of actual travel speed. Via a case study and extensive numerical analysis, we find that the established robust optimization method produces an efficient design of signal control and design speed at the EFL intersection under traffic demand and supply fluctuations. Though the optimization method is now applied to intersections with an EFL, it is considered useful for all intersections with high fluctuation of traffic demand and saturation flow rate.

Traffic control optimization on isolated intersection using fuzzy neural network and modified particle swarm optimization

Traffic density in big cities due to congestion problems in various points of the city. This problem will occur worse at crucial times such as when rush hours and active working hours. The existence of a traffic light system as a traffic signalling device is a solution to overcome traffic congestion. Appropriate traffic light settings can minimize vehicle waiting times at intersections. The aim of this study is to optimize an adaptive traffic control that can adjust the conditions of traffic flow on certain road segments at isolated intersections. In this study optimization uses methods of Fuzzy Neural Network (FNN) and Modified Particle Swarm Optimization (MPSO). The optimization results will be compared with a regular method of Adaptive Neural Fuzzy Inference System without using MPSO. The simulation results show that the efficiency and adaptability of the combination method of FNN and MPSO are better than the Neural Fuzzy Controller without MPSO. A better result is also indicated by the value of Mean Squared Error (MSE) that decreased from 6.3299 becomes 2.065.

Application of graf coloring for optimization of traffic light settings in Medan

Traffic congestion is a problem faced by various cities in Indonesia. One solution is to use traffic light. The existence of a traffic light lamp is very helpful to discipline road users, but in many cases, it is less optimal, related to determining which currents must be red or green and how long each one is. To overcome this problem, a graph approach is used with point coloring application as a scheduling problem. The purpose of this study was to determine the application of the graph at the intersection using the Recursive Large First Algorithm to optimize traffic light settings in the city of Medan and simulation of traffic light settings using Microsoft Visual Basic 6.0. The research method consisted of several stages, namely collecting data, transforming road intersections and their currents into graph shapes, coloring each node on the graph using the Recursive Large first Algorithm, determining the alternative completion of the green light duration and the flashing red light with a certain time cycle, designing simulations and withdrawals conclusion. From the analysis results obtained the calculation results showed that there is a more optimal level of effectiveness from the total duration of secondary data traffic light settings with primary data at the intersection of Gatot Subroto round about and aksara in Medan city.

An urban traffic controller using the MECA cognitive architecture

Abstract In this paper, we present a Cognitive Manager for urban traffic control, built using MECA, the Multipurpose Enhanced Cognitive Architecture, a cognitive architecture developed by our research group and implemented in the Java language. The Cognitive Manager controls a set of traffic lights in a junction of roads based on information collected from sensors installed on the many lanes feeding the junction. We tested our Junction Manager in 4 different test topologies using the SUMO traffic simulator, and with different traffic loads. The junction manager seeks to optimize the average waiting times for all the cars crossing the junction, while at the same time being able to provide preference to special cars (police cars or firefighters), called Smart Cars, and equipped with special devices that grant them special treatment during the phase allocation policies provided by the architecture. Simulation results provide evidence for an enhanced behavior while compared to fixed-time policies.

Accurate and Reliable Detection of Traffic Lights Using Multiclass Learning and Multiobject Tracking

Automatic detection of traffic lights has great importance to road safety. This paper presents a novel approach that combines computer vision and machine learning techniques for accurate detection and classification of different types of traffic lights, including green and red lights both in circular and arrow forms. Initially, color extraction and blob detection are employed to locate the candidates. Subsequently, a pretrained PCA network is used as a multiclass classifier to obtain frame-by-frame results. Furthermore, an online multiobject tracking technique is applied to overcome occasional misses and a forecasting method is used to filter out false positives. Several additional optimization techniques are employed to improve the detector performance and handle the traffic light transitions. When evaluated using the test video sequences, the proposed system can successfully detect the traffic lights on the scene with high accuracy and stable results. Considering hardware acceleration, the proposed technique is ready to be integrated into advanced driver assistance systems or self-driving vehicles. We build our own data set of traffic lights from recorded driving videos, including circular lights and arrow lights in different directions. Our experimental data set is available at http://computing.wpi.edu/Dataset.html.

Supervised learning from human performance at the computationally hard problem of optimal traffic signal control on a network of junctions.

Optimal switching of traffic lights on a network of junctions is a computationally intractable problem. In this research, road traffic networks containing signallized junctions are simulated. A computer game interface is used to enable a human ‘player’ to control the traffic light settings on the junctions within the simulation. A supervised learning approach, based on simple neural network classifiers can be used to capture human player's strategies in the game and thus develop a human-trained machine control (HuTMaC) system that approaches human levels of performance. Experiments conducted within the simulation compare the performance of HuTMaC to two well-established traffic-responsive control systems that are widely deployed in the developed world and also to a temporal difference learning-based control method. In all experiments, HuTMaC outperforms the other control methods in terms of average delay and variance over delay. The conclusion is that these results add weight to the suggestion that HuTMaC may be a viable alternative, or supplemental method, to approximate optimization for some practical engineering control problems where the optimal strategy is computationally intractable.

Modeling and optimizing traffic light settings in road networks

We discuss continuous traffic flow network models including traffic lights. A mathematical model for traffic light settings within a macroscopic continuous traffic flow network is presented, and theoretical properties are investigated. The switching of the traffic light states is modeled as a discrete decision and is subject to optimization. A numerical approach for the optimization of switching points as a function of time based upon the macroscopic traffic flow model is proposed. The numerical discussion relies on an equivalent reformulation of the original problem as well as a mixed-integer discretization of the flow dynamics. The large-scale optimization problem is solved using derived heuristics within the optimization process. Numerical experiments are presented for a single intersection as well as for a road network.

TLR: A Traffic-Light-Based Intelligent Routing Strategy for NGEO Satellite IP Networks

We present TLR, a traffic-light-based intelligent routing strategy for NGEO satellite IP networks. In TLR, a set of traffic lights are used to indicate the congestion status at both the current node and the next node. When a packet travels along a pre-calculated route to the destination, it may adjust the route dynamically, according to the real-time color of traffic lights at each intermediate node. Through the combination of preliminary planning and real-time adjustment, each packet can eventually get an approximately optimal transmission path. The multi-path routing mechanism in TLR can help achieve a good distribution of traffics when the network traffic increases. The Public Waiting Queue scheme in TLR can fully utilize free spaces of the buffer queues and lower the packet drop rate. While the concept of TLR has many advantages, it may result in endless-loop of routing. To eliminate this phenomenon, a defense scheme is incorporated in the design of TLR. A set of simulations are conducted using the Network Simulator (version 2) to verify the good performance of TLR, in terms of lower packet drop rate, better distribution of traffics and higher throughput, over the entire satellite constellation.