Traffic Control Technology Research Articles

Density Based Traffic Signal Controller Using IoT

Every city in the world suffers from traffic congestion, which greatly disturbs the citizens. This problem is made worse by signal timing delays because modern traffic lights are not traffic condition-adaptive. An increasing number of people are in need of effective automatic traffic control technologies to address this. In this study, a density-based dynamic traffic signal control scheme is proposed. The system uses infrared sensors fixed on road poles and a Node MCU micro-controller to automatically modify signal timing according to traffic density at intersections. It is essential to go from fixed-time signaling to automated decision-making. Current fixed-timing systems become ineffective when imbalances in traffic flow arise. This study proposes a solution to a common urban problem by introducing an adaptive traffic light system to reduce congestion.

Artificial intelligence in operational applications of railway infrastructure manager

The main goal of this article is to present the possibility of using artificial intelligence in operational application of railway infrastructure manager. Railway 4.0 can be controlled fully digitally – operational applications based on the artificial intelligence can optimize the technology of railway traffic control. Thereafter, a wide range of equipment could be controlled by application through a secure interface.

Aircraft trajectory prediction and aviation safety in ADS-B failure conditions based on neural network

With the rapid expansion of transportation demand, the number of global flights has rapidly increased, which also poses challenges to air traffic management (ATM). Considering that the radar system in ATM can no longer meet the requirements of flight safety, a very promising next-generation air traffic control technology—Automatic Dependent Surveillance Broadcast (ADS-B) technology has been introduced. However, in the event of on-board equipment failure and local area signal interference, the ADS-B’s signal will disappear or be interrupted. This sudden situation can pose a danger to aviation safety. To solve this problem, this article proposes a bidirectional long short-term memory (Bi-LSTM) network prediction method combining historical ADS-B data to short-term predict the trajectory of aircraft, which can improve aviation safety in busy airspace. Firstly, the problem of frequent dynamic modeling of different types of aircraft was solved by utilizing historical ADS-B data as the data source. Secondly, the data cleansing method is proposed for ADS-B raw data. Furthermore, considering that the spatial trajectory of the aircraft is a complex time series with continuity and interactivity, a bidirectional LSTM based aircraft trajectory prediction framework is proposed to further improve prediction accuracy. Finally, a trajectory with frequent changes was selected for prediction, and compared with 7 prediction methods. The results showed that the proposed method had high prediction accuracy, thus also improving the aviation safety of the aircraft.

Построение распределенных микропроцессорных систем управления движением поездов

High material requirements of new relay systems make it impossible to modernize devices within existing areas and require the construction of new interlocking system buildings, which significantly affects the volume of capital investments. Transitioning to microelectronic and microprocessor electronic platforms allows for the design of more compact systems with expanded functional capabilities. In global practice, there is a trend towards widespread use of microprocessor-based interlocking system. However, there is a slow pace of device updates, mainly due to the high cost of microprocessor-based interlocking system, which exceeds by several times the cost of similar relay-based interlocking system. The high performance of computing resources and fiber-optic data transmission channels allows for the design of efficient structures for microprocessor-based interlocking system. The article presents a comparative analysis of the structures of microprocessor-based interlocking system. The implemented decentralized structures solve the issues of reducing investments for the design and construction of the station’s cable network. The advantages of using these systems from the point of view of controlling the transportation process are described, conclusions are drawn on the effective use of the capabilities of modern control systems with integrated subsystems in relation to field-based train traffic control technologies.

Satellite Attitude Determination Using ADS-B Receiver and MEMS Gyro

Automatic dependent surveillance-broadcast (ADS-B) is a very important communication and surveillance technology in air traffic control (ATC). In the future, more and more satellites will carry out ADS-B technology to perform a global coverage. In order to make full use of the resources in the satellite, this paper proposes a solution for satellite three-axis attitude determination using the ADS-B receiver. The principle of ADS-B-based attitude determination is presented first. On this basis, ADS-B-based methods are employed to solve the problem. To achieve a higher attitude determination precision, gyro is combined with the ADS-B receiver using a multiplicative extended Kalman filter (MEKF). Finally, a simulation is carried out and the result is presented.

Digital twins and 3D information modeling in a smart city for traffic controlling: A review

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

Improvement of Train Traffic Control Technology Based on Abstract Modelling of Operational Processes

Purpose. The main goal of the work is to improve the process of controlling transport units (trains) on the basis of abstract modelling of operational processes, which will allow the operational dispatching apparatus to respond in a timely manner to constantly changing train conditions. Methodology. In order to ensure the rhythmic and uniform movement of trains of all categories along railway lines, train dispatchers, based on their experience, together with locomotive dispatchers and train locomotive drivers, constantly monitor the operational train condition and develop a strategy for the movement of trains along railway sections. This approach is quite energy-consuming in terms of human resources due to excessive nervous tension. As a result of this shortcoming and mistakes made, there are unproductive downtime at railway stations and, in some cases, a significant reduction in sectional speed, which in turn directly affects the industry's profitability and the quality of passenger service, including high-speed traffic. The basis for making management decisions on operational train conditions is automated systems and personal experience of professionals. In this regard, it is advisable to form a model that will reproduce the optimal train operation plan by predicting the main indicators. Findings. In the course of the scientific and applied research, the predictor of collision of trains of different categories with station and inter-train intervals was determined, which can later become the basis of a powerful module of the operational decision support system. Originality. The paper proposes an approach to improving the process of managing transport units based on abstract modelling of operational processes, which, unlike existing approaches, allows the implementation of a high-speed intelligent decision support system for railway dispatching with the possibility of self-adaptation. Practical value. The implementation of the proposed approach in the form of an automated software system will further increase the profitability of the railway industry in the freight and passenger traffic sector.

Methodology of protection of self-driving from malfunctions of vehicles

To transfer vehicles to self-driving, not only automatic traffic control technologies are needed, but also technical measures to protect them from failures of components of self-driving vehicles. Such protection will be provided by the development of monitoring the performance of self-driving vehicles in combination with algorithms for using its results. The purpose of this work is to substantiate the technological possibilities of minimizing losses from disruptions in the performance of self-driving vehicles (AVs). Along with the development of control, it is proposed to automate the assessment of the reserve of operability of the AVs and the development of restrictions on the modes of operation and movement of the vehicle for the "emergency" control of the vehicle, minimizing the consequences of failures. Keywords: self-driving vehicle, control, algorithm, parameter, technical condition, significant functions, failure, malfunction, operability margin

Research on Comprehensive Traffic Safety Management and Control Technology for Operating High-speed Diseases in Mountainous Areas

Research on Comprehensive Traffic Safety Management and Control Technology for Operating High-speed Diseases in Mountainous Areas

Exploring reward efficacy in traffic management using deep reinforcement learning in intelligent transportation system

In the last decade, substantial progress has been achieved in intelligent traffic control technologies to overcome consistent difficulties of traffic congestion and its adverse effect on smart cities. Edge computing is one such advanced progress facilitating real-time data transmission among vehicles and roadside units to mitigate congestion. An edge computing-based deep reinforcement learning system is demonstrated in this study that appropriately designs a multiobjective reward function for optimizing different objectives. The system seeks to overcome the challenge of evaluating actions with a simple numerical reward. The selection of reward functions has a significant impact on agents' ability to acquire the ideal behavior for managing multiple traffic signals in a large-scale road network. To ascertain effective reward functions, the agent is trained withusing the proximal policy optimization method in several deep neural network models, including the state-of-the-art transformer network. The system is verified using both hypothetical scenarios and real-world traffic maps. The comprehensive simulation outcomes demonstrate the potency of the suggested reward functions.

State-of-Art Review of Traffic Light Synchronization for Intelligent Vehicles: Current Status, Challenges, and Emerging Trends

The effective control and management of traffic at intersections is a challenging issue in the transportation system. Various traffic signal management systems have been developed to improve the real-time traffic flow at junctions, but none of them have resulted in a smooth and continuous traffic flow for dealing with congestion at road intersections. Notwithstanding, the procedure of synchronizing traffic signals at nearby intersections is complicated due to numerous borders. In traditional systems, the direction of movement of vehicles, the variation in automobile traffic over time, accidents, the passing of emergency vehicles, and pedestrian crossings are not considered. Therefore, synchronizing the signals over the specific route cannot be addressed. This article explores the key role of real-time traffic signal control (TSC) technology in managing congestion at road junctions within smart cities. In addition, this article provides an insightful discussion on several traffic light synchronization research papers to highlight the practicability of networking of traffic signals of an area. It examines the benefits of synchronizing the traffic signals on various busy routes for the smooth flow of traffic at intersections.

Research on the influence of light source characteristics on traffic visual distance in foggy areas at night

Adverse weather such as fog will reduce drivers' visual recognition ability, and important visual information in the driving will be weakened and even lost, which brings risks to driving safety. This paper sets out to explore causes for the decline in driving visual ability in foggy sections at night based on drivers' visual recognition demand mechanism. The purpose is to study the influence of light source characteristics on visual distance under open traffic conditions. Through an outdoor visual recognition test, data were collected on the visual recognition distances of 12 car drivers to standard gray small targets, under different light source characteristics and meteorological visibility conditions. Results revealed that the latter conditions, along with illuminance and correlated color temperature affected drivers' visual recognition ability in low meteorological visibility sections at night. At the same illuminance and meteorological visibility, a light source with high correlated color temperature could improve visual distance. The multivariate power function model of meteorological visibility, illuminance at the target and driver's visual distance in foggy areas were obtained by fitting. The research methods and conclusions could provide technical reference for improving traffic visual distance at night, and thus help lay a foundation for road construction and traffic control technology in foggy areas.

Eco-Drive Technology, Human Factors, and Environmental and Economic Benefits

The objective of eco-drive technology is to reduce fuel consumption and resulting emissions using advances in communication and traffic control technologies with capability to support infrastructure-to-vehicle connection in a signalized network. On the human factors side, there is growing interest across the world in advising drivers to take eco-drive actions by effectively using the green phase of the signal cycle time to save fuel and reduce emissions. This paper describes a large-scale real-world research project in Ottawa (Ontario, Canada) on this subject. The technology and methods that support the green light optimized speed advisory (GLOSA) system were refined and all 1,178 traffic signals in the city were equipped to connect with a fleet of vehicles. Field study data were analyzed for speed trajectories, fuel consumption, and GLOSA compliance. Greenhouse emissions and fuel cost changes were computed. An anonymous questionnaire study investigated driver perception of the usefulness of the signal data displayed on an in-vehicle unit as advice on driving adjustment decisions made under prevailing traffic conditions. The over 65% compliance with GLOSA and the results of the driver questionnaire were mutually consistent. The fuel saving amounted to 7.6% but was adjusted to 5% because of uncertainties in daily vehicle travel. The reduction in carbon dioxide equivalent and fuel cost reported in the paper are based on a 5% adjustment. These results can be used for cost–benefit studies. Also, simulation-based research projects can verify their findings with the real-world experience reported in this paper.

Long-Term Safety Analysis of Hard Shoulder Running on Freeways in Germany

On freeways with high traffic demand, hard shoulder running (HSR) can be an effective traffic management measure to increase the capacity by providing an additional travel lane during peak hours. While the positive effects of HSR on traffic flow quality were documented in several studies, the implications of HSR on road safety are more ambiguous. This paper presents results of a study in which accident data for seven freeway sections with HSR on freeways in Germany were analyzed over a long period of 13 years. All investigated sections are equipped with variable speed limits. The evaluation of crash frequencies on the investigated freeway sections revealed a high safety level. By combining crash data and traffic data it is shown that crash occurrence depends on the prevailing traffic conditions, with congestion being the most critical traffic state in relation to safety. Therefore, safety improvements upstream of HSR segments can be related to the improved traffic flow and the reduction of congestion. In conclusion, the results of the investigation provide evidence that the implementation of HSR can improve road safety if state-of-the-art traffic control technology is applied and congestion can be relieved.

Molecular Dynamics Characteristics and Model of Vehicle-Following Behavior

The vehicle-following behavior is a self-organizing behavior that restores dynamic balance under the stimulation of external environmental factors. In fact, there are asymmetric problems in the process of acceleration and deceleration of drivers. The existing traditional models ignored the differences between acceleration and deceleration of vehicles. In order to solve this problem, the vehicles driving on the road are compared to interacting molecules. Vehicle-following characteristics are studied, and the molecular following model is established based on molecular dynamics. The model parameters under different conditions are calibrated considering the required safety distance by the vehicle and the reaction time of the driver. With the help of the vehicle running track graphs, speed, and acceleration graphs, the numerical simulations of the molecular following model and the classical optimal speed vehicle-following model are carried out. The results of the comparative analysis show that the acceleration in the process of acceleration and deceleration is not constant but more sensitive to the deceleration of the preceding vehicle than to the acceleration and more sensitive to the acceleration/deceleration of the short-distance vehicle than to the acceleration/deceleration of the long-distance vehicle. Therefore, the molecular following model can better describe the vehicle-following behavior, and the research results can provide a theoretical basis and a technical reference for the analysis of traffic flow dynamic characteristics and adaptive cruise control technology.

Automatic Traffic Control Technologies for Remote Monitoring Of Unmanned Railway Gates

Continuous researches are done to improve technologies for developing effective, economical and productive solutions for preventing fatalities in the railway gates that are unmanned. Several solutions in this research field have been suggested but none of them are sufficiently effective to deploy them at the automated level crossings and fully eradicate human presence. Surveying the current methodologies and the pitfalls in them the paper has developed an efficient and cost effective remote monitoring for unmanned railway gates, enabling automated traffic control technologies and the wireless sensors. The paper scope in developing an automated traffic control in the unmanned railway gates in India.

Traffic Control System and Technologies: A Survey

Traffic Control System and Technologies: A Survey

Controlling walking in Stockholm during the inter-war period

AbstractThis article offers an analysis of different approaches to control walking in Stockholm in the inter-war period. Various social actors engaged in controlling pedestrians through legislation, police monitoring, educational campaigns and traffic control technologies. But the police, municipal engineers, local politicians and road user organizations differed in their aspirations to privilege motorists over pedestrians. While the inter-war period saw a shifting balance between pedestrians and motorists in Stockholm, the transition in terms of legitimate use of city streets was incomplete. Moreover, taking pedestrians’ viewpoints into consideration, what many observers and motorists understood as rebellion against traffic rules or simply bad manners, many pedestrians found to be the safest way to cross the street.

Ontology-Based Approach for Human Competency Gap Analysis in Air Traffic Management

Abstract The Global Air Navigation Plan (GANP) is a flexible global engineering approach that allows all States to advance their Air Navigation capacities based on their specific operational requirements. Aviation professionals have an essential role in the transition to, and successful implementation of the GANP. The development of new air traffic control technology requires new competencies from operational and maintenance personnel under the circumstances. And this, in turn, requires new education curricula for initial, vocational and advanced training in this area. The paper is focused on the creation of methodology for the partial automation of the comparison of existing and required competences of Air Traffic Management (ATM) personal and synthesis of training courses and modules, using a formal, ontology-based approach as a tool to solve these problems. One of the problems in the implementation of the GANP is that, on the one hand, there are currently no unified requirements for all categories of ATM personnel, and on the other hand, the development of ATM technologies is far ahead of the pace of training of personnel of appropriate qualifications. This problem becomes even more noticeable in countries that have just started an active modernization of ATC systems and do not have enough experience in this field. The paper describes the general methodological approach based on the education ontology modelling for human competency gap analysis in ATM and for gap analysis between the university curricula outcomes and the ATM requirements. The ontology of key personnel competencies issues for the design and integration of large-scale future ATM programmes is proposed.

Investigation of ultimate boundedness conditions of mechanical systems via decomposition

The reported study was supported by the Russian Foundation for Basic Research (grant N 19-01-00146-a), by the Saint Petersburg State University (project Id: 37569826), by the National Natural Science Foundation of China (grant N 61803007) and by the Rail Transit Joint Funds of Beijing Natural Science Foundation and Traffic Control Technology (grant N L171001).