Traffic Light Cycle Research Articles

ANALISIS KINERJA SIMPANG BERSINYAL TANAH AJI – KOTA MATARAM DENGAN SOFTWARE PTV VISSIM

The Tanah Aji signalized intersection is one of the crossroads in Mataram City that links Jalan Sriwijaya with Jalan Majapahit and Jalan Airlangga with Jalan Gajah Mada . The Department of Transportation (DISHUB) officially reactivated the Tanah Aji signalized intersection (APILL) on Wednesday, December 14 2022. The aim of this research is to determine the performance of the Tanah Aji signalized intersection in Mataram City in its existing condition and provide solutions to improve performance. the signalized intersection. Primary and secondary data collecting was part of the research methodology. Secondary data is in the form of location map data obtained from Google Earth, traffic light cycles, and video recordings of intersections from the Mataram City Transportation Department (DISHUB). Next, analytical modeling of existing conditions is carried out. The results obtained show that the existing conditions produce a level of service E. The solution by modeling the flyover on Jalan Majapahit and Jalan Sriwijaya produces a level of service C. Comparison of the performance of the Tanah Aji intersection, Mataram City in the existing condition and the flyover solution from the results of the Vissim software analysis, is the existing condition, it was found that the length of the vehicle queue was 92,077 m Jl. Srivijaya; 231,275 m Jl. Gajah Mada; 177,973 m Jl. Majapahit and 157,783 m Jl. Airlangga. The results of the flyover solution analysis showed that the vehicle queue length was 54.09 m Jl. Srivijaya; 201.15 m Jl. Gajah Mada; 76.95 m Jl. Majapahit and 107.71 m Jl. Airlangga

Adaptive Traffic Control Using Cooperative Communication Through Visible Light

The study aims to create a Visible-Light Communication (VLC) system for secure vehicle management at intersections. This involves enabling communication between vehicles and infrastructure (V2V, V2I, and I2V) using headlights, streetlights, and traffic signals. Mobile optical receivers gather data, determine their location, and read transmitted information through joint transmission. An intersection manager coordinates traffic and communicates with vehicles through embedded Driver Agents. The system utilizes a "mesh/cellular" hybrid network configuration and encodes data into light signals emitted by transmitters. Optical sensors and filtering properties enable reception and decoding. The study demonstrates bidirectional communication, employing queue/request/response mechanisms and relative pose concepts for safe vehicle passage. A deep reinforcement learning model controls traffic light cycles, validated via simulation in a Simulation of Urban Mobility simulator. Results show that this adaptive traffic control system effectively collects detailed vehicle data and ensures secure communication within the short-range mesh network.

Organizational complexity and road safety: dialectical contradiction and its behavioural interpretation

The main organizational and technical idea implemented in recent years in Russia in the field of road safety is to reduce the conflict of traffic and pedestrian flows. This is realised through the use of multiphase traffic light cycle modes. The consequence of this is a sharp increase in the duration of the traffic light cycle (up to 180-200 sec) and a decrease in the capacity of the street and road network. However, more surprisingly, it does not lead to an increase in road safety. The article presents the author’s view on the non-obvious effectiveness of such attempts to reduce the conflict of traffic and pedestrian flows and the author’s reflections on the dialectical contradiction between the organizational complexity of traffic light cycles and the behaviour of road users.

Training and Applying Artificial Neural Networks in Traffic Light Control: Improving the Management and Safety of Road Traffic in Tyumen (Russia)

The article presents the initial experience (spring-summer 2023) of using artificial neural networks (ANN) to improve traffic management in the large Russian city of Tyumen. Using the example of one of the intersections of the city's road network, it is shown how much transport delays are reduced when the duration of the traffic light cycle phases is quickly adjusted to the actual traffic intensity when compared with the usual previously used traffic light predictive mode. For the specific intersection of Odesskaya and Kotovskogo streets in Tyumen, considered in this article, the traffic light control mode using an ANN can significantly (by 20.6 ... 22.4%) reduce the average delay time of vehicles. It is also important that the reduction in traffic delays, which is possible with the regulation of traffic using ANN, helps to reduce stress for road users and improve road safety. The article presents historical data illustrating the dynamics of changes in the field of traffic management and road safety in Tyumen. This information confirms the thesis about the dialectic of systemic development and the need for a gradual increase in the intellectual component of traffic management in large cities. The Applications (Appendix A and Appendix B) present the code of the auxiliary procedures and functions module and the code of the main data collection module used to optimize the traffic light control mode at the experimental intersection of the Tyumen road network. The main conclusion of the study is that the use of an ANN allows for taking into account a much larger number of factors and optimizing the control of the entire object, consisting of several intersections, which is not achievable using predictive modes and local adaptive control.

INTERSECTION ARRANGEMENT DESIGN ON SULTAN HAMID II ROAD - GUSTI SITUT MAHMUD ROAD – 28 OKTOBER ROAD – SELAT PANJANG ROAD PONTIANAK DUE TO THE OPERATION OF THE LANDAK PARALLEL BRIDGE

The signalized intersection on Sultan Hamid II Road - Gusti Situt Mahmud Road – 28 Oktober Road – Selat Panjang Road is an intersection in Pontianak city with high traffic problems. The construction of the Landak parallel bridge initially aimed to reduce congestion, but this created an imbalance that caused congestion. This research analyses the performance of the intersection using the 1997 Indonesian Road Capacity Manual method and VISSIM software simulation. Data was collected in the form of intersection geometric data, traffic light cycle time, vehicle speed, and traffic volume taken for three days with a survey tool in the form of CCTV as a recorder at 06.00 - 18.00 WIB. Then, the data collected is processed into the basis of research to calculate the performance of the intersection in existing conditions and develop alternative improvement plans using MKJI 1997 and VISSIM software simulations. In the analysis with the MKJI 1997 method, the North road's service level is LOS C; the East road is LOS C; the South road is LOS B; the West road is LOS F, and the highest degree of saturation is 1.56. Analysis with VISSIM software simulation obtained the level of service of the intersection LOS C. After making alternative changes in cycle time, geometrics, and restrictions on the time of prohibition of passing obtained in alternative 15 with changes from signalized intersections to roundabouts and geometric changes.

Studies of Level of Service (LOS) at Signalized Intersection With Mix Traffic Flow

One of the signalized intersections with four approaches is the BPKP’s intersection at Banda Aceh. The intersection will be analyzed in the current condition and remodeled using the software SIDRA intersection 8.0. This Software can choose a predetermined minimum capacity for each little movement. Utilizing a video from a collected in the study area, the institute provided the information. Data from a video included vehicle volume, downstream distances, upstream distances, and negotiation distances, as well as transit time. in its current condition. The total flow of demand is 1060 pcu/h. degree of saturation is 1,406, and level of service is F. The remodel of this intersection is analyze the signalized intersection's traffic light cycle time. It is necessary to be able to handle the current that enters the intersection. Total flow of demand in remodel condition of BPKP's intersection at Banda Aceh is 1060 pcu/h, degree of saturation is 0,765, and level of service is C.

Application of Compatible Graph and Webster Methods for Traffic Light Arrangement in Jepara

The problem of congestion has become a common problem that is often found on the highways, especially at the crossroads, without exception in Jepara Regency. The Mayong-Jepara Highway intersection is classified as a busy intersection that is full of vehicles during every departure and return hours, which are dominated by factory employees. Congestion often occurs at these intersections even though there are traffic lights that regulate the movement of vehicles. So, This study aims to find the solutions to congestion problems at Mayong-Jepara Highway intersection through compatible graph modeling and optimizing traffic light cycle time using the Webster method. Compatible graphs are used to determine traffic flows that are worked to move simultaneously without causing collisions, and that are used to carry out the graph weighting to determine the number of phases. The variables used in this applied research are the data on the number of vehicles, road width, and traffic light duration that taken directly in the field. Because the traffic density in the morning and afternoon is different for each intersection arm. Thus, the cycle time is determined in 2 sessions namely the morning and the afternoon. From the modeling of the compatible graph that has been weighted, it is obtained that the morning and afternoon sessions have 3 phases as the total which are then used to determine the traffic light cycle time. As a result, the cycle times for the morning session are 98 seconds, and the afternoon session is 155 seconds. The results were then simulated with PTV Vissim software and assessed to be quite effective in dealing with congestion and heavy traffic at the Mayong-Jepara Highway intersection especially in the afternoon session.

METHODOLOGY FOR USING A GENETIC ALGORITHM TO SOLVE URBAN PLANNING PROBLEMS

With the development of computer technology, algorithms for solving problems based on artificial intelligence are gaining popularity. The genetic algorithm is one of them. The article describes using of this algorithm in the context of urban planning problems. 
 The genetic algorithm is primarily created to search for extremes of complex functions, where the variable can be described as a vector. A significant number of urban planning problems can be represented as follows. The article describes the methodology for solving urban planning problems using this algorithm. The main advantage of the proposed algorithm is its relative ease of implementation and a wide range of issues that can be solved with its help. The main disadvantage of this algorithm is that it is obtained the result, with a certain probability, can reflect the local minimum of the function, as well as the need to change the parameters of the genetic algorithm individually for each individual task. 
 The article gives an example of using the proposed methodology to solve the problem of optimizing the location of work place. It is also proposed to apply a genetic algorithm to optimize the traffic light cycle, automate the process of building planning and develop traffic management schemes. 
 The implementation of the proposed methodology can significantly increase the quality of urban planning projects, as well as reduce the time spent on their implementation.

Enhancing Traffic Flow Using Computer Vision Based - Dynamic Traffic Light Control and Lane Management

Traffic congestion is a persistent problem in many metropolises worldwide. Despite the existence of traffic control systems, they are not always efficient enough to manage the ever-changing traffic density environment. The traditional approach of allocating specific times to each lane with the green light, regardless of the traffic situation, has not been very effective. In fact, it often can make the traffic congestion worse. Thus, the need for a more sophisticated system has emerged to simulate and optimize traffic control. This paper proposes the use of computer vision technology to develop a traffic control system that is based on periodic still photo feeds and compares different object detection models to find the best model for vehicle detection in our system . The system aims to enhance traffic flow by dynamically adjusting the traffic light cycles based on real-time traffic conditions.

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.

Modelling the parameters of accelerated move-ment of passenger cars in coordinated traffic

Problem. In order to fine-tune the coordination plan to the specific traffic conditions on the road network segment selected for coordination, it is necessary to determine the time for vehicles to travel between synchronized traffic lights. Such models should be based on accelerated rather than uniform moving, and a parameter estimation method should be developed to form them. Goal. Development of a new method for estimating the parameters of a linear model of decreasing acceleration, which allows estimating them in specific driving conditions based on knowledge of two quantities: the length of the link and the random time of its overcoming in free driving conditions. Methodology. Using the functional relationships between travel time, acceleration, speed, and distance, known from kinematics, we have moved to a new sequence of actions to select the type and estimate the parameters of the model that relates the acceleration and speed of a car. For this purpose, using the obtained analytical dependence between time and distance travelled, which contains unknown model parameters, it is possible to find the values of these coefficients by minimising the sum of squares of the difference between the calculated and actual lengths of the link. Results. Based on the search for the minimum square of deviations between the actual and calculated values of the link length, the method of estimating the parameters of the model of accelerated movement of cars at a start from a standstill, based on the results of observations in Kharkiv and Vinnitsa, led to coefficients similar to existing models. The average steady-state speed is estimated at 53.14 km/h. Originality. The presented methodology contains the new transition method from actual times of link passing to parameters of linearly decreasing acceleration model. Practical value. The developed method allows fine-tuning the offsets of the traffic light cycles in the coordination plan to the specific traffic conditions on the road network segment selected for coordination based on actual times of link passing.

Multi-Agent Reinforcement Learning for Traffic Signal Control: A Cooperative Approach

The rapid growth of urbanization and the constant demand for mobility have put a great strain on transportation systems in cities. One of the major challenges in these areas is traffic congestion, particularly at signalized intersections. This problem not only leads to longer travel times for commuters, but also results in a significant increase in local and global emissions. The fixed cycle of traffic lights at these intersections is one of the primary reasons for this issue. To address these challenges, applying reinforcement learning to coordinating traffic light controllers has become a highly researched topic in the field of transportation engineering. This paper focuses on the traffic signal control problem, proposing a solution using a multi-agent deep Q-learning algorithm. This study introduces a novel rewarding concept in the multi-agent environment, as the reward schemes have yet to evolve in the following years with the advancement of techniques. The goal of this study is to manage traffic networks in a more efficient manner, taking into account both sustainability and classic measures. The results of this study indicate that the proposed approach can bring about significant improvements in transportation systems. For instance, the proposed approach can reduce fuel consumption by 11% and average travel time by 13%. The results of this study demonstrate the potential of reinforcement learning in improving the coordination of traffic light controllers and reducing the negative impacts of traffic congestion in urban areas. The implementation of this proposed solution could contribute to a more sustainable and efficient transportation system in the future.

Control and allocation at an intersection with traffic lights

Managing road infrastructure in highly urbanized areas during the Industry 4.0 era poses a significant technological challenge for traffic engineers. Steadily growing traffic volume, both of motor vehicles and pedestrians, cyclists or scooters, necessitates the development of advanced traffic control algorithms and systems. Improvement of the efficiency and capacity of intersections without any intervention into the physical structure of roadways is one of the two aspects of today's traffic engineering. In this paper, however, emphasis is placed on the aspect of coordination of conflicting flows of motorized and pedestrian traffic. Consideration is given to ensuring that each traffic light phase at an intersection is maximally utilized while maintaining the required safety factor. The empirical part of the study consists in identifying inefficiencies in the traffic light cycle. The analysis of traffic phases has revealed that there were certain periods in the cycle during which pedestrians were given the right of way while, in fact, it was not necessary. The study proposes a solution to optimize the green signal timing for conflicting vehicular and pedestrian flows in real-time. By eliminating delays in traffic signal phases as a result of not having to give a green signal for pedestrians, the proposed solution will improve the efficiency of urban networks with respect to an aspect whose potential has not been exploited so far. Coordination and adaptation of each light phase to the most effective extent is a feasible answer to the needs and requirements of modern urban areas.

ОБЕСПЕЧЕНИЕ ЭФФЕКТИВНОСТИ ОРГАНИЗАЦИИ ДОРОЖНОГО ДВИЖЕНИЯ СОГЛАСОВАНИЕМ РАБОТЫ СВЕТОФОРНЫХ ОБЪЕКТОВ

Coordination of the work of traffic lights on the street and road network of cities leads to an increase in the efficiency of traffic management. Identification of transport problems was carried out on the basis of monitoring of traffic parameters and analysis of traffic accident statistics. The calculation of the parameters of the coordinated control was carried out using simulation mod-eling in the Avenue 2.0 program. The calculation of the optimal duration of the traffic light cycle was carried out on the basis of the total delay and average saturation of the cycle in the most satu-rated directions.

FACTORS AFFECTING THE CAPACITY OF THE ROAD NETWORK

Full-scale studies of the movement of vehicles on the street and road network of large cities have been carried out. It is revealed that a large number of realignments are observed during the movement of vehicles, as factors affecting the capacity of the road network. The quantitative characteristics of car rebuilds before relocations are determined. The dependence of the number of vehicle realignments on the number of traffic lanes and the location of the vehicle in a particular lane has been established. The obtained research results should be taken into account when determining the duration of traffic light regulation cycles at intersections.
 Purpose – determination of the number of realignments as factors affecting the capacity of the road network.
 Methodology statistical methods of processing a full-scale experiment were used in the work.
 Results: quantitative characteristics of realignments depending on the number of lanes and the composition of traffic flows are obtained.
 Practical implications it is advisable to apply the obtained results in the regulation of road traffic by technical means of traffic management.

The influence of the traffic light`s permissive signal share on the duration of traffic delays

Today, the motorization level and the value of traffic flow on the street-road network have increased. Often this leads to an excessive load on the existing traffic management system, highways, and roads. As a result, the number and duration of traffic delays are increasing, especially within populated areas. The consequence of this is the formation of traffic jams, increase of fuel and lubricants consumption, noise pollution, and emissions of exhaust gases. Another, no less critical consequence is an increase in traffic accidents, particularly at unsignalized intersections. Therefore, a traffic light control system is often implemented at street intersections to increase traffic safety and reduce the number of conflicting flows. In addition, this system should be optimized for signalized objects. The object of the study is a signalized intersection of multi-lane streets located in the city. The main problem that needs to be solved is the reduction of the vehicles` delay duration at the approaches to such intersections, in particular with the use of appropriate organizational measures and planning of the traffic light control system. According to the study's results, regularities were revealed regarding the change in the traffic's delay duration depending on the share of the permissive signal and the duration of the traffic light's cycle at the street intersection. At the same time, the received modulation results in the PTV Vissim software environment indicate an increase in delay values with an increase in the duration of the traffic light cycle. However, an equally important influence factor is the share of the permissive signal, as it reduces to a certain extent the duration of vehicles in standby mode at the approaches to the signalized intersection. The obtained results are recommended to be used in both developing new traffic organization schemes at signalized street intersections and improving existing ones.

Nature-Inspired Cloud–Crowd Computing for Intelligent Transportation System

Nowadays, it is crucial to have effective road traffic signal timing, especially in an ideal traffic light cycle. This problem can be resolved with modern technologies such as artificial intelligence, cloud and crowd computing. We hereby present a functional model named Cloud–Crowd Computing-based Intelligent Transportation System (CCCITS). This model aims to organize traffic by changing the phase of traffic lights in real-time based on road conditions and incidental crowdsourcing sentiment. Crowd computing is responsible for fine-tuning the system with feedback. In contrast, the cloud is responsible for the computation, which can use AI to secure efficient and effective paths for users. As a result of its installation, traffic management becomes more efficient, and traffic lights change dynamically depending on the traffic volume at the junction. The cloud medium collects updates about mishaps through the crowd computing system and incorporates updates to refine the model. It is observed that nature-inspired algorithms are very useful in solving complex transportation problems and can deal with NP-hard situations efficiently. To establish the feasibility of CCCITS, the SUMO simulation environment was used with nature-inspired algorithms (NIA), namely, Particle Swarm Optimization (PSO), Ant Colony Optimization and Genetic Algorithm (GA), and found satisfactory results.

SmartLight: A smart efficient traffic light scheduling algorithm for green road intersections

Traveling vehicles participate in emphasizing the global warming problem due to the gases produced by them. The exponential increase in the number of daily traveling vehicles has exaggerated the world pollution problem threatening the life on the planet. This encourages several environmental organizations to look for designing green vehicles. Moreover, several countries have forced green driving rules and technologies. Road intersections are considered high fuel consumption areas over the road network. This is due to the required power to stop moving vehicles and restart stopped vehicles at these intersections. This work introduces an efficient traffic light scheduling algorithm (SmartLight) that controls the competing traffic flows at the road intersections. It is designed to reduce the total consumed fuel of vehicles and thus it reduces their produced gases. The topology of the road intersection, the context of the competing traffic flows, and the real-time traffic characteristics of each flow are mainly considered to schedule the phases of each located traffic light. The phases of the traffic light cycle are primly set to allow emergency vehicles to pass through the intersection without stopping. Then, the traffic flow that contains heavy vehicles or has the highest weight among the competing traffic flows is assigned the highest priority to pass through the signalized intersection. Finally, the average waiting delay time of each flow on the signalized intersection should not exceed a pre-determined threshold to guarantee fair sharing of the signalized intersection. The scheduling time of each phase is set based on the lengths of platoons of vehicles that are scheduled during that phase from different un-conflicted traffic flows. An experimental study has evaluated the performance of the proposed algorithm (SmartLight) compared to previous traffic light scheduling algorithms in terms of total fuel consumption, gas emission, the average queuing delay time of vehicles, and the throughput of the road intersection.

Ambulance detection for smart traffic light applications with fuzzy controller

<p>In the development of intelligent cities, the automation of vehicular mobility is one of the strong points of research, where intelligent traffic lights stand out. It is essential in this field to prioritize emergency vehicles that can help save lives, where every second counts in favor of the transfer of a patient or injured person. This paper presents an artificial intelligence algorithm based on two stages, one is the recognition of emergency vehicles through a ResNet-50 and the other is a fuzzy inference system for timing control of a traffic light, both lead to an intelligent traffic light. An application of traffic light vehicular flow control for automatic preemption when detecting emergency vehicles, specifically ambulances, is oriented. The training parameters of the network, which achieves 100% accuracy with confidence levels between 65% with vehicle occlusion and 99% in direct view, are presented. The traffic light cycles are able to extend the green time of the traffic light with almost 50% in favor of the road that must yield the priority, in relation to not using the fuzzy inference system.</p>

Ensuring the environmental safety of the intersection left-turn by adaptive section control

The method of field observations of the movement and maneuvers of vehicles and pedestrians at the intersection of Leninsky Prospekt and Brusilov Street in the city of Voronezh was used. The reasons for the creation of dangerous and emergency traffic situations have been established. Identified shortcomings in the organization of the left turn from the street. Brusilov in the direction of Leninsky Prospekt. It is proposed to pre-calculate the cycle of traffic light regulation at the intersection in the Excel program in order to determine the maximum permissible traffic intensity for the subsequent calculation of the cycle using the Webster formula for off-peak periods of intensity. A program for calculating the cycle of traffic signaling at the intersection in Microsoft Visual Studio 2007 was written for the proposed calculation of the cycle using the Webster formula. Keywords: intersection, left turn, vehicle, traffic light regulation cycle calculation, traffic safety