Traffic Regulation Research Articles

Criminal Sanctions in the Application of Electronic Ticketing Using CCTV (Closed Circuit Television) Recording by Satlantas Polda Maluku Utara

This study aims to determine how the criminal sanctions against electronic traffic ticket offenders using CCTV (Closed Circuit Television) recordings and what obstacles are experienced by the North Maluku Regional Police in the application of electronic ticket penalties using CCTV (Closed Circuit Television) recordings. The type of research used in this research is empirical normative research type. Location This research was conducted at the North Maluku Police Traffic Unit. In addition, researchers also conducted direct interviews with the community regarding the application of electronic ticketing by the North Maluku Police Traffic Unit which was recently implemented in Ternate City. Then, the data obtained were analyzed descriptively qualitatively. Based on the pre-research conducted by researchers, the e-ticket system used by the North Maluku Police Traffic Police is regulated in article 272 of Law number 22 of 2009 concerning road traffic and transportation, the application of e-ticketing through CCTV footage is not yet fully effective because it has only been implemented in one city out of 10 municipalities in North Maluku Province, namely Ternate City, and is still in the socialization period, but what researchers highlight is the application of e-ticketing penalties that have not been clearly regulated by the traffic law. How are the criminal sanctions applied by the North Maluku Police Traffic Unit, if the vehicle recorded by CCTV is not the legal owner listed on the vehicle registration documents (Vehicle Registration Certificate), how is the application of traffic penalties against vehicles or offenders who are sanctioned criminal. One of the principles of criminal law is that there is no crime without error, that a person can only be punished for his actions if there is an error in himself. Whether the offender driving the vehicle at that time, not the legal owner of the vehicle listed on the vehicle registration certificate, is given a criminal sanction. Or is it the owner of the vehicle who must be responsible for the negligence of the offender? The obstacle experienced by the North Maluku Police Traffic Unit is the absence of a traffic regulation that clearly regulates e-ticketing penalties

PEDESTRIAN CROSSING CONTROL ALGORITHMS

          The algorithm of adaptive control of an adjustable pedestrian crossing is considered in the article. This improves the efficiency of traffic regulation and the safety of pedestrian traffic, since pedestrians crossing the carriageway will be performed at times with the least traffic. At the same time traffic flows with high intensity will not be interrupted.

ОПТИМИЗАЦИЯ УПРАВЛЕНИЯ ГОРОДСКИМИ СВЕТОФОРАМИ С ПРИМЕНЕНИЕМ НЕЙРОННЫХ СЕТЕЙ

One of the most pressing problems of large cities is the problem of traffic management of vehicles. The reason for this problem is an imperfect way to manage traffic flows. Traffic light regulation is of particular importance in traffic management. Most modern traffic light control systems operate at set time intervals and are not able to cope with the constantly changing situation on the road. A promising direction for solving this problem is to optimize the system using artificial neural networks. The advantage of neural networks is self-learning, which allows the system to adapt to the changing situation on the road. Despite numerous attempts, it has not yet been possible to obtain a high-quality mathematical model of urban traffic management. This model should determine the functional dependence of transport flow parameters on control parameters. Nowadays, traffic flows are regulated everywhere by means of traffic lights. If we can get a fairly accurate mathematical model of traffic flows, we can determine the optimal duration of the traffic signal phases to achieve the maximum capacity of the road network node. A fairly accurate mathematical model of traffic management that works in predictive mode will display an estimate of the optimal control parameters, as well as make correct decisions in emergency situations. Well-known mathematical models of road traffic take into account only the average values of traffic flows, and not the exact number of cars on each road section at a particular time.

Assessing traveler compliance with the social optimum: A stated preference study

The development of Advanced Traveler Information Systems (ATIS) with en-route navigation systems has opened the door to new traffic regulation policies such as collective route guidance based on social costs, i.e. routes that minimize total travel time. However, a critical element for their efficiency is the compliance of travelers with route recommendations. It is well established that the social optimum is different from user equilibrium, where users drive on their shortest path. Thus, even when knowing that recommendations are for the common good, users may still choose not to follow the guidance given and drive as they wish. In this paper, we use a stated preference survey based on route choice situations from a real network to investigate traveler compliance for different levels of travel time sacrifice vs several social benefits. Two kinds of social benefits are considered: congestion alleviation and emission reduction. The data collected allows us to precisely quantify the travel time sacrifice that a given proportion of travelers would be ready to accept in order to take a different alternative that has a given level of social benefit. In line with the literature, our analysis confirms the decrease of compliance with the increase of sacrifice. Moreover, it suggests that the way the recommendation is intended could play a significant role in the level of compliance: the display of an advice message for the social path (in the congestion alleviation case) is shown to be more efficient than only showing additional information (in the emission reduction case).

Simulation model of the organization of technologicaltransport movement at a mining enterprise

The article presents a simulation model for organizing the movement of technological transport on the road network of a mining enterprise, the study of which will justify the use of technical means of traffic control and avoid emergencies. The simulation model of traffic management on the road network of the mining enterprise is designed to study the effectiveness of the road network and the traffic control system on it, including using automation tools, calculating the control parameters of traffic regulation and verifying the correct choice of their number and location on the ground. The simulation model has a block-modular structure. As the control program, the algorithm of the technical means for organizing traffic at the facility and section of the road is used. The developed simulation model makes it possible to take into account such parameters of the traffic flow as the type, speed of the vehicle, and time intervals between vehicles. During the simulation, situations of standard movement of vehicles along a road section, the occurrence of a traffic accident and accumulation of vehicles on a road section, as well as the maintenance, repair and reconstruction of roads and the functioning of traffic control equipment at the enterprise are set up.

Road Traffic Light in New Configuration

The three-color system containing signals of the same circular shape has been in existence for over a hundred years. Each traffic signal has been justifiably selected to have a special color light to correspond to human psychoemotional reaction (red – stop, yellow – caution, green – go) to a given color signal (British Standards, 2015) and to comply with the laws of physics (The Motivated Engineer, 2015) – Rayleigh’s scattering law (Banc SpaceTek, 2017). The main downsides of the traditional road traffic light include the following: • The uniform circular shape of light signals results in uncertainty and difficulties for road users with color blindness and visual impairments, resulting in the need for restrictions or bans on driving license issuance in some countries. This uncertainty becomes particularly acute in conditions of low visibility. • According to the concept of harmony of form and color (Itten, 1961), a green light alone corresponds to the circular (spherical-like) shape of the signal. Red and amber lights harmoniously combine with other geometrical shapes. • The uniform shape of light signals prevents the implementation of the original compact combined model of traffic lights. For example, during the day, colorblind people can tell which signal is which because there is a standard position assigned: top – bottom or right – left (Oliveira, Souza, Junior, Sales & Ferraz, 2015). This becomes problematic if the compact combined models of traffic lights are used. Engineers and inventors have been trying to solve these problems by introducing random changes in the light signal shape and complicating the traffic light design. For a long time there have been different proposals about how to eliminate the demerits of the existing traffic lights: from arbitrary changes in the signal shape (Patterson, 1988) to transformation of traffic lights into a single-section display panel (Kulichenko, 2011) which replaces among others stationary road signs. However, technical solutions like these deprive the traffic light of its signal uniformity and conciseness (simplicity, clarity and precision of its controlling effect), features which help safe traffic regulation in a busy and dynamic mode. Technical modernization of individual signal components has been going hand in hand with technological developments as light sources, diffusers, lenses, controllers, materials, control systems, timers, etc. are improved. However, adequate design and aesthetic proposals are considerably behind. The aim of this paper is to propose a concept of creating control signals of traffic light that harmonize color and form, and, as a result, to create a new model of traffic light that will be convenient for all road users.

Adolescent's perception of road risk on their routes to school in Makwanpur, Nepal; a qualitative study

BackgroundBusy and poor road infrastructure along routes to school poses high risk of traffic injury for children and adolescents. Ensuring every young person's safe journey to and from school is fundamental to achieving reductions in road injuries and Sustainable Development Goal 3.6. However, there is little evidence reporting adolescent's views about their school travel from low and middle income countries. This study aims to understand adolescent's perceptions of injury risks on their journey to school in Nepal. MethodsWe used Photo-Elicitation Interview (PEI) methods to collect data from fourteen purposively identified adolescents (12–16 years) who walk to Tribhuwan Secondary School along the East-West Highway which is known to be at high risk of crashes in Makwanpur, Nepal. The participants used a camera to record parts of their journey, which they perceived as dangerous or safe. Photographs were used as prompts during an interview afterwards. Interviews were audio-recorded, transcribed, translated and analysed thematically. ResultsThe identified themes were categorised as either environmental or behavioural factors. The adolescents were scared to walk on narrow roadsides because of speeding vehicles. They also found crossing the road dangerous because of the lack of designated pedestrian crossings and disregard shown by drivers. Poor visibility caused by random roadside parking and trees also increased the sense of road danger. ConclusionAdolescents expressed multiple concerns which made their journeys difficult and dangerous. They illustrated issues such as poor road condition, inadequate pedestrian crossings and traffic signs, narrow roadsides, vehicle speeding and overtaking, failing to obey traffic rules and regulation -providing evidence that could be shared with the authorities to improve road safety near schools.

Practical Descriptor Modeling of Traffic in Intersecting Metro Lines and Robust Controller Design for Train Synchronization at Transfer Stations

In this article, a discrete-event linear descriptor model for intersecting metro lines based on the deviations of train departure times from the nominal values is introduced. In intersecting metro lines, the delays are transmitted from one line to the other intersecting lines in transfer stations (TSs). Therefore, considering the effect of the TSs in traffic modeling leads to a more accurate model. The introduced model is an uncertain model, and we reformulate it as a linear uncertain descriptor model with additive uncertainty. A robust <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> controller is designed based on the bounded real lemma and linear matrix inequality to compensate the delays and regulate the time deviations in the presence of uncertainty. In addition to the aforementioned objective of the control system, another objective is synchronizing the trains at TSs of intersecting metro lines. The simulation results demonstrate the performance and effectiveness of the proposed automatic traffic regulation system using real data from two intersecting lines of the Tehran metro system.

Retracted: A smart transportation system in VANET based on vehicle geographical tracking and balanced routing protocol

SummaryIn present scenario, Vehicular Ad‐hoc Network (VANET) has obtained extensive attention because of its unique characteristics that handle high mobility of vehicles, reaping topological changes and frequent route breakages or failures. Hence, for providing smart transportation with enhanced traffic regulation and safety, a new position‐based routing protocol called Traffic Dynamism‐Balanced Routing Protocol (TDBRP) for VANET has been proposed in this paper. Moreover, the work concerns the instantaneous scenario of urban cities with the bidirectional and multilane roads. Efficient junction selection algorithm (EJSA) has been incorporated based on the traffic dynamism for establishing optimal route paths between nodes, hence, forwarding the data packets efficiently. Furthermore, the novel EJSP and the route framing between junctions are established on the basis of information gained from two‐hop neighbors, which tends to reduce end‐to‐end delay and enhances packet delivery ratio (PDR). The TDBRP has been implemented and evaluated in Network Simulator (NS 2.34). And the results are examined and compared with some existing protocols like Geographic Source Routing (GSR), Enhanced Greedy Traffic Aware Routing protocol (E‐GyTAR), and Anchor‐based Street and Traffic‐Aware Routing (A‐STAR). The outcomes outperform the existing works by minimizing the routing overhead and end‐to‐end delay by an average of 16% and 13%, respectively, and increase the PDR value by an average of 25% than others. The proposed protocol also evidences that the two‐hop neighbor information‐based packet forwarding provides better result and efficient routing than neighbor information.

ROAD TRAFFIC ACCIDENTS ATTITUDE AND BEHAVIOR IN AL-DIRIYAH, RIYADH 2016

Background: Road traffic accidents are a major health hazard in the world. Everyday thousands of people are killed and injured on our roads.&#x0D; Objective: Our study aimed to determine attitude and behaviour of road traffic accident among high school student in Riyadh.&#x0D; Methodology: school based cross sectional study sample size was 197 among high school students in Diriyah, Riyadh, Saudi Arabia. high school students of Diriyah province. Inclusion level was 29 and 30 year of high school students. Exclusion was female and staff. Sample Technique was systematic random. Data collection using pretested, preceded questioner and analysed using SPSS version 20. P-value of less than 0.05 was considered significant result.&#x0D; Results: 96.5% of participants showed a good level of knowledge toward traffic regulation. 83.25% of participants showed a good attitude. 53.8% of participants were fully aware of the traffic signs. 51.3% of participants had an accident before. 26.9% had driving license.&#x0D; Conclusion: The majority of our respondent showed good level of knowledge regarding of traffic regulation, the minority of participants has driving license, almost half of participants use mobile phone while driving, most of participants don't use seat belt.&#x0D; Keywords: Attitude, Behaviour, Accidents, Traffic.

Basic Methodology of Traffic Management for the Street and Road Network of a Large City with Traffic Lights Regulation

The objective of the article is to develop a system of principles and methods aimed at improving management of transport flows on the street and road network of a large city with traffic lights regulation. The suggested methodology is based on the methods used in Russia and abroad to improve road traffic safety and quality, results of a survey of experts in the field of road design and traffic management, monitoring at regulated crossings, and analysis of road accidents in the city of Volgograd. The primary customer property of a regulated crossing is road safety. Elimination of causes of road traffic accidents associated with road traffic, structural geometric, signalling, and technical conditions is the most important task regarding a regulated crossing. Enhancing road traffic quality at low levels of network load supposed considering demand for transportation, increase in travel comfort, coordination, and flexibility of traffic lights operation. High degree of network load supposes that more attention is paid to traffic capacity of the street and road network elements, restrained access of vehicles to areas of greater congestion, increased duration of a green light cycle (for more than 120 seconds, if this does not affect traffic safety and network congestion degree).

Transfer Urban Human Mobility via POI Embedding over Multiple Cities

Rapidly developing location acquisition technologies provide a powerful tool for understanding and predicting human mobility in cities, which is very significant for urban planning, traffic regulation, and emergency management. However, with the existing methodologies, it is still difficult to accurately predict millions of peoples’ mobility in a large urban area such as Tokyo, Shanghai, and Hong Kong, especially when collected data used for model training are often limited to a small portion of the total population. Obviously, human activities in city are closely linked with point-of-interest (POI) information, which can reflect the semantic meaning of human mobility. This motivates us to fuse human mobility data and city POI data to improve the prediction performance with limited training data, but current fusion technologies can hardly handle these two heterogeneous data. Therefore, we propose a unique POI-embedding mechanism, that aggregates the regional POIs by categories to generate an artificial POI-image for each urban grid and enriches each trajectory snippet to a four-dimensional tensor in an analogous manner to a short video. Then, we design a deep learning architecture combining CNN with LSTM to simultaneously capture both the spatiotemporal and geographical information from the enriched trajectories. Furthermore, transfer learning is employed to transfer mobility knowledge from one city to another, so that we can fully utilize other cities’ data to train a stronger model for the target city with only limited data available. Finally, we achieve satisfactory performance of human mobility prediction at the citywide level using a limited amount of trajectories as training data, which has been validated over five urban areas of different types and scales.

Optimization of adaptive traffic light control modes based on machine vision

Urbanization leads to a significant increase in traffic density in large cities. The growing transport concentration is accompanied by an increase in traffic congestion and emissions of harmful substances. The policies and decisions developed by the authorities, such as the expansion of existing roads and construction of new roads, as well as increase in transport taxes, no longer make it possible to maintain the adequate mobility of the population. One of the solutions is to increase the efficiency of road infrastructure utilization by forecasting the traffic situation and using the adaptive adjustment of traffic lights operation. With dynamic collection and interpretation of traffic flow data from traffic monitoring cameras, it will be possible to use the dynamic parameters of vehicles as indicators for the adaptive adjustment of traffic light regulation. The first part of the paper describes the use of machine vision and a neural network (YOLOv4) in tracking the parameters of traffic flows on road sections in front of intersections. The second part of the paper presents a methodology based on the dynamic regulation of traffic lights cycles and their duration, taking into account the current and forecast parameters of the traffic flow. The algorithm for the adaptive adjustment of traffic lights regulation considers the following parameters: the number and dynamic dimensions of vehicles moving towards the intersection; the number of vehicles in the queue in front of the stop line and their acceleration at the start of the movement. We determined the relationship of the intersection capacity when driving straight ahead with the dynamic dimensions of vehicles and the formation of a queue in front of the stop line, waiting for the green light. The study resulted in the development of an algorithm for setting the duration of both a particular phase and the entire traffic lights cycle in the tasks of eliminating or minimizing the possibility of congestion.

DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction

Predicting the density and flow of the crowd or traffic at a citywide level becomes possible by using the big data and cutting-edge AI technologies. It has been a very significant research topic with high social impact, which can be widely applied to emergency management, traffic regulation, and urban planning. In particular, by meshing a large urban area to a number of fine-grained mesh-grids, citywide crowd and traffic information in a continuous time period can be represented with 4D tensor (Timestep, Height, Width, Channel). Based on this idea, a series of methods have been proposed to address grid-based prediction for citywide crowd and traffic. In this study, we revisit the density and in-out flow prediction problem and publish a new aggregated human mobility dataset generated from a real-world smartphone application. Comparing with the existing ones, our dataset holds several advantages including large mesh-grid number, fine-grained mesh size, and high user sample. Towards this large-scale crowd dataset, we propose a novel deep learning model called DeepCrowd by designing pyramid architectures and high-dimensional attention mechanism based on Convolutional LSTM. Lastly, thorough and comprehensive performance evaluations are conducted to demonstrate the superiority of the proposed DeepCrowd comparing to multiple state-of-the-art methods.

Strategy Management of Telematics Systems in the Transport Sector with Regard to Safety

Transport has an impact on the daily lives of the population. Currently once more people use daily mode of transport on the roads. It is the increase of participants that creates a higher risk of crisis occurrence in transport. Security has long been one of the most felt human needs, and it is in transport that needs to be given particular attention. Different road systems can be used to increase safety. These include telematics systems. They are an important tool for traffic management and regulation, which ultimately affects safety itself. In the article, we focused on their use with a view to reducing the likelihood of crisis phenomena in transport. We focused on their positive impact in increasing the transport safety and flow. The use of these systems reduces the occurrence of crisis phenomena and, in the event of emerging crisis phenomena, contributes to a more effective solution.

Определение пропускной способности полосы движения кольцевой части кольцевого пересечения со светофорным регулированием и прорезанным центральным островком

The capacity of a road (street) is the maximum number of cars that a section of a road (street) can pass per unit of time in one or two directions in the considered road and weather and climatic conditions. In science, there are several approaches to determine the capacity: models based on dynamic models of traffic flow, the model of Birul A. K., Silyanov V. V., Tribunsky V. M., Khomyak Ya. V., Bilyatinsky A. A. and etc. In a practical way, they divide: theoretical, practical and maximum throughput. In the Russian Federation, there are a large number of guidelines for its determination. However, for a circular intersection with traffic light regulation and a cut-through central island (hereinafter referred to as KPSRPTSO), no such recommendations have been presented. After analyzing this traffic organization scheme, it was for the first time proposed to determine the capacity of the traffic lane of the KPSRPTSO half-ring. The purpose of the study is to improve the efficiency of the KPSRPTSO by determining the theoretical bandwidth of the traffic lane of a semi-ring of a traffic intersection. The article hypothesizes that the investigated theoretical throughput depends on two factors: the diameter of the traffic junction ring and the effective duration of regulation for the main road. To substantiate the adequacy of the calculations, the simulation method was used in the Aimsun software package (micromodeling). On the basis of data from field surveys of sections of the road network, a simulation model was created with a high degree of reliability, reflecting the current situation at regulated intersections, and the effectiveness of design solutions when organizing the KPSRPTSO was assessed. The relationship between the theoretical bandwidth of the KPSRPTSO half-ring and the diameter of the ring and the effective duration of regulation for the main road has been established. Comparison of the experimental data with the calculated values performed according to the recommendations of the methodological literature shows a discrepancy from 1% to 13%, which shows the qualitative convergence of the data. Further research involves the development of a methodology for calculating the parameters of the KPSRPTSO.

Change of Traffic Parameters when Introduced Adaptive Method of Traffic Light Object Control

The article is devoted to improving the quality of life in cities by implementing the concept of an “intelligent” city and developing an automated transport infrastructure. The following factors are considered in the work: the traffic intensity of vehicles and the mode of operation of traffic signal regulation. In work, the mode of operation of a traffic light is determined by an adaptive method. The main tool for increasing the capacity is the choice of the optimal ratio of phase coefficients and the optimal cycle time. Considered the influence of capacity on the parameters of road traffic, the environmental load from automobile transport. The dependence of the traffic parameters for different cycle times is established. A change in fuel consumption and in the content of harmful emissions for various traffic light modes is given. The justification is given for the necessity to change the traffic light mode after increasing the number of lanes in the street road network.

Optimization of railway stations operation in the context of the introduction of modern systems of train traffic interval regulation at the eastern polygon

Optimization of railway stations operation in the context of the introduction of modern systems of train traffic interval regulation at the eastern polygon

Assessment of the Traffic Enforcement Strategies Impact on Emission Reduction and Air Quality

The World Health Organization (WHO) reported that globally 3.7 million deaths were attributable to ambient air pollution (AAP) in 2012. Traffic congestion is one of the significant sources of air pollutants Intelligent Transportation Systems (ITS) are advanced technologies that have been used widely in large cities. They have a potential impact on reducing traffic congestion and then improving environmental quality. Many countries have targeted urban policy traffic enforcement strategies that are ITS-based on improving traffic emission and air quality. Because each strategy has a different impact level, the strategy that positively impacts location and traffic conditions might negatively impact under different conditions. Also, the authorities that take the decision which strategies could be implemented. Therefore, this paper aims to evaluate the potential impact of traffic enforcement strategies on reducing traffic emissions and improving air quality. In our study, three typical traffic enforcement strategies were evaluated: a traffic management regulation for speed limit changes, route changing, and fleet composition changes. The impact of these strategies on air quality was evaluated through evaluating the traffic air quality changes brought by these strategies against a baseline (Base Case) scenario. The results indicate that the impact of these strategies on increasing environmental quality is not always positive. The reduction of CO was the highest in the speed restriction scenario (25.6%) than other scenarios. While reducing the reduction of PM10 was less in speed restriction scenario (25.6%) than other scenarios. The findings can help the decision makers implement the best strategy to reduce traffic emission under different situations.

Survey on Big Data Techniques in Intelligent Transportation System (ITS)

Big Data is an evolving exemplar moreover, particularly within in the transportation system, has now become a powerful enticement of global interest. On the basis, Big Data is often seen intact undertaking whereas transit system fore efficiently handle utterly the information needed by aforementioned part to provide secure, unstained including reliable modes of transit, and to create custom the recipient's transport experience. By having access to centralized services, a smart city enhances the effectiveness of its inhabitants. Intelligent Transportation Systems (ITS) play an essential role in the transformation of a cosmopolitan environment into a digital city. With the last two decennary, numerous ITS technologies have been deployed, such as city-wide traffic regulation control, smart parking, general transport information assistance (transit vehicle, rail, compact, air, etc.), shipping, legitimate traffic, measuring of highway speed restrictions, etc. Most subsequent Data Analytics insight is needed for transport and movability industry, ITS implementations, threshold instances, areas and use cases, including the routing, planning, ability to track of infrastructure, platform architecture, and more, are examined in this article. Finally, the paper tackles some open problems in ITS with the use of big data analytics.