Signal Violation Research Articles

Traffic violations and economic preferences: Evidence from full-time drivers of a large transportation network company in China

Safety has been a consistent issue with the rise of transportation network companies (TNCs), especially in China with annual revenue exceeding 1.5 trillion CNY. In this paper, we explore intrinsic factors that can influence the risky behavior of TNC drivers by investigating the link between their economic preference parameters and traffic violations. We measure the economic preferences of 160 full-time drivers on a large Chinese TNC platform and examine their violations over the previous 13 months. We have four major findings. First, more risk-averse drivers have less violations. Second, present bias and patience do not affect drivers' risky behavior except that more patient drivers commit more direction|sign violations, which may have been caused by the higher expectation of the gain from such a violation of patient drivers. Third, reciprocity reduces violations of all types. Drivers' belief of other people's pro-social inclination only affects dangerous violations with long duration, i.e., speeding, in which case they take advantage of other people's attentiveness. And finally, we find no evidence of driver fatigue. These results highlight how the advantage of TNC platforms in managing drivers' incentive can affect the negative externality drivers impose through risky driving behavior, and hence provide policy implications.

Traffic Signal Violation Detection System Using Computer Vision

Traffic Signal Violation Detection System Using Computer Vision

Field Evaluation of Yellow Change and Red Clearance Intervals with Subsequent Permissive Left-Turn Flashing Yellow Arrow Indication

The flashing yellow arrow (FYA) indication has become commonly used for communicating permissive left-turn operations to road users. A conventional signal phasing communicated to left-turning drivers consists of a leading protected phase followed by a permissive phase using a FYA indication, often referred to as protected-permissive. To transition from the protected to the permissive phase, change (steady yellow arrow) and clearance (steady red arrow, all-red) intervals, or only a change interval, may be used. There is no specific guidance on the use of clearance intervals for left turns with protected-permissive phase and FYA indication. In this study, field data were collected from different geographical regions in the United States to evaluate change and clearance intervals with the objective of developing guidance. Video data were recorded at 37 intersections during peak hours, for approximately 142 h, across eight states. Overall, 4,001 observations of vehicles turning left during the change or clearance interval were analyzed. Field observations were evaluated at the approach level to assess left-turn violation rate and violations per cycle as a function of change and clearance interval configuration. At the individual vehicle level, logistic regression was implemented to evaluate the effect of change interval and clearance interval duration, delayed onset of FYA, and regional variation. The results of the analysis at the approach and individual vehicle level were consistent and indicate that: (i) a clearance interval should be included, (ii) delaying the onset of FYA indication with an extension beyond the all-red clearance interval would reduce left-turn signal violations, and (iii) duration of change intervals has a marginal impact on left-turn signal violations.

THE APPLICATION OF TECHNOLOGY AND INFORMATION DEVELOPMENT IN ELECTRONIC TRAFFIC LAW ENFORCEMENT (ETLE) TO SHAPE PUBLIC AWARENESS

The legal system in Indonesia requires breakthroughs amidst the increasingly sophisticated technological developments today. Indonesia has Electronic Traffic Law Enforcement (ETLE) as one of the implemented technologies, which electronically records traffic violations. This is done due to limited human resources in traffic police and high legal needs. The use of electronic fines (E-Tilang) is also intended to address public complaints about the ineffectiveness of fines that enter the state treasury because the process of paying court tickets is often inefficient and time-consuming. The method used in this research applies a descriptive-qualitative method. The results of this study state that in practice, ETLE can only detect certain violations such as traffic sign violations. This shows how important it is to comply with traffic regulations and therefore, the ETLE system must be integrated with the national database, and to address these violations, a specific big data system must be created. Thus, it can be concluded that the enforcement of ETLE is still ineffective in addressing traffic violations on the roads in Indonesia.

E-Challan Based Intelligent Assistance System for Smart City

Traffic management and enforcement of road safety regulations have become increasingly crucial in modern urban environments, as the number of vehicles on the roads continues to surge. With the rise in traffic violations, particularly signal disobedience, there is a pressing need for innovative solutions that can efficiently detect and penalize offenders while reducing the burden on law enforcement personnel. The E-Challan System harnesses the power of cutting-edge computer vision techniques, most notably Automatic Number Plate Recognition (ANPR), to accurately capture and decipher vehicle number plates in real- time. High-resolution cameras strategically positioned at traffic junctions and signal intersections actively monitor passing vehicles, automatically detecting those that violate traffic signals. Upon successful identification of a signal violation, the E-Challan System promptly generates an electronic challan, or e-challan, containing detailed information about the violation, such as the date, time, and location of the incident. This comprehensive documentation serves as indisputable evidence of the offense and provides an essential legal foundation for imposing fines on violators. with an Auto Debit Fine mechanism.

Calculation of Dangerous Driving Index for Two-Wheeled Vehicles Using the Analytic Hierarchy Process

Given the high incidence of traffic accidents and fatalities on two-wheeled vehicles, there is a growing need for safety management. However, studies on evaluating two-wheeled vehicle driving in a quantitative and comprehensive form are insufficient. In this study, 11 items were defined for the first step to evaluate two-wheeled vehicle driving: signal violation, central line violation, helmet violation, pedestrian close driving, sidewalk driving, reverse lane driving, speed violation, rapid acceleration, rapid deceleration, rapid turn, and rapid lane change. The items were classified into three categories (traffic violation, pedestrian threat, and reckless driving), and their weights were derived using the AHP technique. For rapid acceleration, rapid deceleration, rapid turn, and rapid lane change, a high-performance driving simulator was used to establish risk criteria and calculate the weight based on the degree of risk. The calculated weight of each item indicates its importance in evaluating two-wheeled vehicle driving, with helmet violation (0.158), speed violation (0.124), and pedestrian close driving (0.122) having the highest weights. Finally, the dangerous driving index for two-wheeled vehicles was calculated by the weights of each evaluation item and applied to the driving trajectory data.

The Identification of Motorcyclist Safety Risk among University Students in Yogyakarta, Indonesia

Introduction: Traffic accidents are cases of concern both nationally and internationally. Their impact ranges from injuries to death. In Indonesia, traffic accidents are dominated by students who use motorcycles. With this in mind, this study is focused on identifying the driving attitudes that are responsible for traffic accidents among university students. Methods: The cross-sectional survey study was conducted from January 2023 to February 2023, located in the Special Region of Yogyakarta, Indonesia. Data was gathered using simple random sampling on 97 students based on experiences while driving such as safety attitude, frequencies on motorcycle inspections, and driving attitude. The next step is a comparison between results based on student experiences and risk assessment by experts. The expert assessment used two personnel of Police Resort from Yogyakarta and Purworejo, Indonesia. Results: Participants were divided into 81.4% men (N=79) and 18.6% women (N=18), with a mean age ± standard deviation of 21 ± 1.8 years. Awareness of safety attributes is demonstrated by the use of helmets by 92.78% of participants, and motorcycle inspections on rearview mirrors (85.57%), rims & tires (79.38%), and brakes (71.13%). In terms of road driving attitudes, students drive with fatigue (82.47%) and sick (61.86%), drive in bad weather (78.35%), and exceed the standard of speed (53.61%). The results of the risk assessment show that 7 variables have a high risk, namely helmet, inspection on the brake, driving in fatigued physical condition, driving in sick physical condition, using gadgets when driving, traffic sign violation, and overspeeding. Conclusion: Based on these results, it show that students' driving readiness is quite good with the attributes of vehicle safety and feasibility. This is shown by the use of helmets and break checks by students with the highest risk on the road. However, the need to be concerned is that the bad riding attitude includes physical health conditions, driving according to traffic safety standards, and paying attention to weather conditions. Improvements are needed especially by drivers to create safe and secure driving conditions.

Prevention of Traffic Signal Violation and Pedestrian Safety Using Retractable Electric Bollard

Prevention of Traffic Signal Violation and Pedestrian Safety Using Retractable Electric Bollard

Finding Infinities in Nanoconfined Geothermal Electrolyte Static Dielectric Properties and Implications on Ion Adsorption/Pairing.

Infinities should naturally occur in the dielectric responses of ionic solutions relevant to many geochemical, energy storage, and electrochemical applications at a strictly zero frequency. Using molecular dynamics simulations cross-referenced with coarse-grained Monte Carlo models, using nanoslit pore models at hydrothermal conditions, and treating confined mobile charges as polarization, we demonstrate the far reaching consequences. The dielectric permittivity profile perpendicular to the slit (ϵ⊥(z)) increases, not decreases, with ionic concentration, unlike in the more widely studied megahertz-to-gigahertz frequency range. In confined electrolytes, the divergences in ϵ⊥(z) correctly describe crossovers between bulk- and surface-dominated dielectric behavior. Nanoconfinement at low ionic concentrations changes monovalent ion energetics by 1-2 kJ/mol, but no dielectric property studied so far is universally correlated to ion adsorption or ion-ion interactions. We caution that infinities signal violation of the "electrical insulator" dielectric assumption.

Modeling pedestrian behavior at urban signalised intersections using statistical-ANN hybrid approach – Case study of New Delhi

Traffic crashes at intersections are major hazard all over the world. The victims of road crashes are mostly pedestrians. A large share of accidents can be related to unsafe crossing behavior by pedestrians. The accidents are mostly fatal for pedestrians especially if the unsafe act is signal violation. This study primarily focused on cognizing factors which are significantly affecting the signal violation behavior of pedestrians’ at urban signalised intersections. Data is collected at 11 signalised intersections in New Delhi, India using video recording technique. Significant variables are identified using conventional statistics. The variables are then used as input neuron for the Artificial Neural Network (ANN) for modeling signal violation behavior. Sensitivity analysis is performed to identify the relative importance of factors related to the pedestrian signal violation. Host of different factors such as pedestrian demographic, behavioral attributes, crossing state and mobile usage are notably influencing signal violations. Pedestrian crossing speed, crossing path and waiting time are the top three predictors of violation behavior. The accuracy of ANN to predict signal violation behaviour is found to be about 85% and is considerably higher than conventional binary logistic regression (BLR) model. The area under the receiver operating characteristic (ROC) curve (AUC) is found to be 0.753, suggesting good model performance. The results suggest that ANN is a robust alternative to conventional regression, for studying and modeling pedestrian behavior. The findings from this study would assist engineers and policy makers to take proactive measures for designing pedestrian friendly facilities to reduce signal violations. This would ultimately improve pedestrian safety at urban signalised intersections.

Traffic Signal Violation Detection System

Traffic Signal Violation Detection System

ЕТИЧНА ІНФРАСТРУКТУРА КУЛЬТУРНОГО ПРОСТОРУ КИЇВСЬКОГО НАЦІОНАЛЬНОГО УНІВЕРСИТЕТУ ІМЕНІ ТАРАСА ШЕВЧЕНКА: ВИКЛИКИ ЗАПРОВАДЖЕННЯ І ФУНКЦІОНУВАННЯ

The article deals with the ethical infrastructure of Taras Shevchenko Kyiv National University cultural space, the peculiarities of its implementation and its functioning due to the challenges facing higher education in Ukraine today. The relevance of studying the ethical provision of university life is driven by the inevitable value transformations that the university as a cultural institution is experiencing today. By the method of case study, the implementation and functioning of the ethical infrastructure at Taras Shevchenko National University of Kyiv is analyzed in the article as a real-time problematic situation. It is shown that the implementation of ethical infrastructure was demanded by the university community and has become a natural process. The thoughtfulness of this process was testified by the thoroughness of preparing the University community code of ethics, carrying out the procedures for its discussion and adoption, and preparing the work of the Standing Commission of the Academic Council on Ethics. It also testified to the moral maturity of the university community to comply with the provisions of the code of ethics, to signal violations of its norms and principles, and to seek the truth in the ethical commission. It is about the grassroots (democratic) way of the creation of the code of ethics. And the discussion, comments and proposals from the structural subdivisions are a kind of public examination of the ethical document. The code of ethics, thus adopted by the university community, has become an effective document that sets a coherent system of coordinates in the life of the university. The purpose of the ethical commission is to resolve controversial issues regarding compliance by members of the university community with the code of ethics. Its powers include advising on the usage of the code of ethics and applying its provisions in everyday university life.

자율주행자동차 사고의 책임귀속과 교통법제의 정비

Self-driving cars will free humans from driving. Starting with the Level 4 self-driving ADS, is designed to control itself and drive even in emergency circumstances. From now on, the existing concept of a driver in charge of the dynamic driving task(DDT) of driving will be disappeared. The problem of attribution of responsibility for traffic accidents still remains, but the legal situation in Korea has not yet adequately prepared for the subjects or the scope of liability. At this point, the UK's new self-driving car law recommended in 2022 is worth considering. The UK government is investing heavily with the goal of commercializing Level 4 autonomous vehicles by 2025. A number of topics related to autonomous vehicles are dealed with this recommendation. The most remarkable thing in relation to the liability for accidents is that the two subjects of Level 4 autonomous driving vehicles. Depending on whether the person could engage in DDT, it is divided into a user-in-charge and NUIC operator, respectively, and each qualification and responsibility is different. The driver is exempted from driving-related matters in the event of an accident, and the responsibility rests with the manufacturer and operator. For the manufacturer(the developer ASDE) to be indemnified, it would have to be demonstrated by them that there were obviously other causes. It should be sought to fundamental changes in the traffic law system related to the driver's license system, signal violations, and the collection and storage of various traffic information.

Smart Traffic Signal Violation Detection System Based on IOT

Roads are primary route to transportation in each country, and they are frequently characterized by traffic congestion due to a lack of traffic management. It could be due to the big population, lack of technology, and violations committed by humans, the most serious of which is traffic rule infringement. It is extremely difficult for authorities to determine whether or not there is a traffic rule infringement, resulting in horrible scenarios that endanger not just drivers but pedestrians as well. To apprehend car owners who disregard traffic signal limits, the traffic police need a straightforward strategy. The administrators are currently checking the film that is being recorded near the traffic signal 24 hours a day, 7 days per week to see if anyone has disregarded the traffic light laws. After taking a picture of the license plate, they must report. Technology can play a big part in addressing these violations, which is why our work focuses on IoT and image processing-based methods. The suggested system's camera records a picture of the car, analyzes the video using the right image processing algorithm, and then records the license plate of the vehicle that violated the traffic laws and transmits it to the administrators. As a result, less manual work is required from police managers, and the video analysis takes place directly on the edge device.

Study on Red Signal Violations and Development of Prototype for Automated Enforcement System

Abstract: The violation of red signal are the major reasons for the occurrence of numerous accidents at intersections. An effort has been made to study the current rate of red signal violation in different road networks in Chennai which accounted for 18.27% and also to provide profile of red signal violation with various parameters. Road inventory survey was done at four selected intersections. The primary survey was conducted and 29743 samples were collected and analysed. The result of study provided scalable indicators for monitoring and evaluating road safety strategies to prevent red light violation in the country. The present research work also made an attempt to introduce an automatic traffic control system based on RFID technology and digital image processing. Then developed a prototype to identify red signal violation automatically with penalty system. These findings represent some useful reactions to improving road safety of urban functions in India and other developing countries. Keywords: Red signal violation, Traffic volume count, RFID, Road safety, Automatic traffic control system.

Analysis of Risk Factors Affecting Urban Truck Traffic Accident Severity in Korea

Due to increases in truck traffic, truck traffic safety has become an unavoidable societal issue in Korea. Truck traffic accidents were responsible for 24% of all traffic deaths in 2019, and the fatality rate was significantly higher than that of other forms of traffic. This study analyzes not only the driver and environmental factors, but also the traffic condition factors which are considered to contribute to the severity of truck traffic accidents, and presents practical truck safety solutions based on the findings. This study examines the fatal and serious injury truck traffic accidents in Incheon, which has large logistics facilities and the highest fatality rate (3.3) in Korea’s capital area. According to the regression analysis results, ‘Nighttime’, ‘Vehicle-single’, ‘Vehicle to Pedestrian’, ‘Lane violation’, and ‘Signal violation’ contribute to the severity of truck traffic accidents. Furthermore, truck traffic accidents in the logistics influencing area are more likely to be serious than in the non-influencing area. In terms of the traffic condition factors, the number of lanes, the maximum speed, and the number of road property-changing nodes were significant. The results of this study will provide useful data for establishing traffic safety policies in urban areas.

Automatic Traffic Red-Light Violation Detection Using AI

Our research is the design of a traffic signal violation detection system using machine learning that learns to prevent the increasing number of road accidents. The system is optimized in terms of accuracy by using the region of interest and location of the vehicle with a red-signal state. By modifying some parameters in the YOLOV5s and re-training the COCO dataset, we can create a model which can be predicted with a high accuracy of 82% for vehicle identification, 90% for traffic signal status change and up to 86% for violation detection. This can be used for red light violation detection which will help the traffic police on traffic management.

Multistate Pilot Study Evaluating the Short-Term Efficacy of a Smartphone-Based Older Driver Support System on Modifying Risky Driving Behaviors

Older drivers are most at risk of serious and fatal injury in crashes per vehicle mile driven compared with other age groups owing to a combination of cognitive decline and increased fragility. A smartphone coaching application targeting risky driving behaviors (e.g., speeding, hard braking), was iteratively designed to ensure older driver acceptance and usability. A 12-week field operational test examined driving performance of 28 drivers aged 65 to 78 from Kansas and Minnesota using the RoadCoach app and an ABA reversal design. Participants’ baseline driving behaviors were recorded for 3 weeks, followed by a 6-week experimental phase of real-time app coaching, and concluded with a 3-week baseline phase with no feedback provided. Compared with the pretreatment phase, there was a significant reduction in the rates of hard braking and stop sign violations associated with system use. A protection effect was observed through the posttreatment phase. Excessive speeding violations were not significantly different across the phases; however, there were modest declines in the proportion of miles traveled 15 mph above the speed limit in the posttreatment phase compared with the prior two phases. No significant effect was found for excessive acceleration and aggressive turning measures posttreatment, despite an observed increase in both rates during the treatment phase compared with pretreatment. Overall, the results indicate that the RoachCoach app may be an effective intervention to reduce several risky driving behaviors while in use and may result in prolonged behavior changes (i.e., reduced hard braking and stop sign violations) after treatment cessation.

Hazard-based duration approach for understanding pedestrian crossing risk exposure at signalised intersection crosswalks – A case study of Kolkata, India

Pedestrian signal violation is a significant concern among policymakers and traffic engineers as this leads to a pedestrian-vehicle crash. The waiting time for a pedestrian at intersections is crucial in street-crossing decision-making. Once pedestrians terminate their waiting behaviour during the red-light period, they would cross in the red light and put themselves in danger. A total of 2089 red-light arriving pedestrian observations were made at eight intersection crosswalks across Kolkata city (India). With the help of hazard-based duration models, the waiting duration till signal violation has been analysed. Kaplan–Meier curve has been plotted to understand the survival probabilities. A semi-parametric Cox Proportional Hazard model was used to understand the different factors influencing signal violation behaviour. However, the proportional hazard assumption was not satisfied. Therefore, a parametric Accelerated Failure Time (AFT) model was used to understand the various covariates that affect the waiting duration. The results highlighted that 49.5% of pedestrians crossed immediately after arriving at the intersection in the red-light phase. A pedestrian’s probability of crossing the road when it is unsafe, i.e., motor vehicles still have green or yellow, varies with the waiting time. As waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at an increased risk of being struck by a motor vehicle. The covariate analysis using the AFT model showed that pedestrian glance/looking behaviour, different types of distractions, signal cycle length, carrying luggage, and traffic plying on the road impacted signal violation behaviour. Signal modifications by reducing red-light phase length for pedestrians might be the most efficient means of reducing the likelihood of signal violation and being hit by a motor vehicle.

Pedestrian red-light violation at signalised intersection crosswalks: Influence of social and non-social factors

The present study aims to investigate the impact of social information on pedestrians’ red-light violation compared to non-social information. The binary logistic regression model predicting signal violation behaviour highlighted that crossing speed, waiting time for safe crossing, and signal cycle length significantly influence the signal violation behaviour. According to the social information estimates, the more pedestrians waiting at the intersection, the more it reduces the likelihood of an oncoming pedestrian’s signal violation. Interestingly, an oncoming pedestrian is more likely to cross in the red light signal when neighbours were doing the same. These results provide insightful information for planners and policymakers. Practical implications such as adjusting the red-light duration and information dissemination on the “positive value of social control” through community campaigns could eventually encourage people to obey traffic light rules.