Enforcing Helmet Compliance Via WhatsApp using Clustering Algorithms

The rampant street racing activities in Tulungagung Regency raise concerns within the community. This paper discusses the law enforcement of street racing activities by the Tulungagung Police Department to realize road safety and traffic order (Kamseltibcarlantas), along with the influencing factors. The discussion encompasses the concepts of traffic, street racing, violation enforcement, and road safety. Qualitative methods employing data triangulation from primary, secondary, and tertiary sources involve data collection, reduction, presentation, and verification. The research findings indicate that law enforcement against street racing in the jurisdiction of the Tulungagung Police Department is carried out through a combination of non-penal (preventive and preemptive) and penal (repressive) approaches. Non-penal approaches include initiatives like "Police goes to school" and patrols, while penal measures involve law enforcement actions such as fines and criminal sanctions. Factors influencing traffic law enforcement against street racing include legal aspects, law enforcement agencies such as the Tulungagung Police Traffic Unit, infrastructure and facilities aiding law enforcement efforts, public response, and cultural alignment with regulations. The enforcement of traffic law against street racing activities in the Tulungagung Police Resort involves both non-penal and penal approaches. Factors such as laws, law enforcement officers, infrastructure, community, and culture influence its implementation.

Business Process Analysis and Optimization on Road Traffic Law Enforcement of the Beijing Intelligent Traffic Management

BackgroundIn 2021, there were an estimated 1.19 million road traffic deaths globally, which corresponds to a rate of 15 road traffic deaths per 100,000 population. Road traffic injury remains the...

Corruption has become a serious problem that hinders the development of various sectors, including traffic law enforcement. Corrupt practices in this sector not only harm the state, but also threaten the safety and comfort of society. Achieving transparency and accountability in traffic law enforcement is very important. This strategy must not only involve changes to regulations, but also requires increasing the capacity and integrity of law enforcement officials, as well as active involvement of the community in supervision. Preventing corruption in traffic law enforcement requires implementing these solutions in an integrated manner, so that it is hoped that traffic law enforcement in Indonesia can become more transparent, accountable and free from corruption. These efforts will not only improve the quality of law enforcement, but also increase public trust in law enforcement institutions, which will ultimately contribute to public safety and welfare.

The practice of law enforcement on traffic violations committed by law enforcement officers is currently not enough to satisfy the expectations of the community. Problems often occur in current law enforcement practices, including vulnerability to corruption and convoluted bureaucracy in dealing with the process of law enforcement, especially for traffic violations. The practice of law enforcement itself cannot only be shackled in the current legal rigidity, in this condition a legal breakthrough or legal progression is needed, so that our law can adjust to the times and demands of society. The E-TLE (Electronic Traffic Law Enforcement) system created by the Semarang Traffic Police Unit is a breakthrough in law in law enforcement practices that are applied to traffic violations in the City of Semarang in order to bring a fast, precise, clean and transparent law enforcement system. In this context, progressive legal theory is used to create a breakthrough in progressive law enforcement in the E-TLE Satlantas Polrestabes Semarang system against traffic violations in the city of Semarang.

Low- and middle-income countries have the highest proportions of road accident fatalities among vulnerable road users. This review established the effectiveness of road engineering and enforcement of traffic laws and regulation interventions to prevent injury (fatal and non-fatal) to vulnerable road users from low- and middle-income countries. We searched the following databases up to Jan 04, 2018: PubMed; OvidSP Medline, OvidSP Embase, OvidSP Transport, Cochrane Injuries Group Specialised Register, Cochrane Central Register of Controlled Trials, and Proquest ERIC database. In addition, road safety organizations’ databases and conference proceedings were hand searched to Jan 2018. Twenty-eight studies were matched to the study inclusion criteria of which we did not analyze six studies assessed as C grade for risk-of-bias. We estimated the effect-size of eighteen studies. Four of the studies presented a unique outcome or a study design; it was not possible to calculate a standardized effect-size. The risk-of-bias rating of the studies included for effect-size analysis ranged between A and B grade. There was no evidence that road engineering interventions were effective for road traffic death counts, the number of injuries, and road accident casualty outcomes. While the enforcement of mandatory helmet law was ineffective in reducing road traffic death counts, intervention efforts proved effective in decreasing injuries. Enforcement of mandatory helmet law, automated-enforcement-system (camera), and pedestrian signal interventions were effective in increasing road users’ compliance with road safety laws. Daytime running-headlight intervention reduced the number of road accident casualties. The quality of evidence for outcomes was ranked very low. Further research is needed to examine the effects of road engineering interventions on injury severity outcomes. Even though the evidence was of very low quality, traffic laws, and regulation interventions when combined with enforcement initiatives or with, other approaches proved effective in changing drivers’ behaviors. Research on road engineering interventions combined with automated-enforcement-systems must be explored in an LMIC setting. The review found evidence gaps on the effects of segregation of vulnerable road users from motorized vehicles, changes in intersections, and bicycle infrastructure interventions.

This study explores the law enforcement model for vehicle speed in Tshwane municipality of South Africa. South Africa has comparatively high road traffic crashes and casualty rates. Most of these crashes are associated with illegal speeding. This study was designed against the background of protracted road traffic crashes the triple causative factors as well as existing traffic law enforcement systems and processes aimed at managing illegal speeding. Data were collected from a sample of 28 senior law enforcement officials from the Tshwane Metropolitan Police Department (TMPD) traffic division, the Gauteng Traffic Police and the National Traffic Police. Qualitative data were analysed using thematic analysis’ open and axial coding processes on Atlas.ti.8. In its findings, the study developed a model that shows that illegal speeding and consequential road crashes were caused by an interaction of multiple factors. These were poor human behavioural elements as the main factor, road-environment factors and vehicle-related factors in the presence of inadequate and uncoordinated traffic law enforcement, weak penal systems for offenders, corruption, poor driver training and low road safety education.

The rapid advancement of digital technology has significantly changed traffic law enforcement in Indonesia, especially through the introduction of Electronic Traffic Law Enforcement (e-Ticket). This system aims to increase transparency and efficiency, as well as guarantee fairness and legal certainty in traffic law enforcement. However, there are still several challenges to be faced, especially related to personal data protection and the unevenness of technological infrastructure in various regions. This research aims to evaluate the effectiveness of e-Tilang in promoting justice and legal certainty and to identify obstacles related to personal data protection and infrastructure equity. Using a normative juridical approach, this research analyzes primary legal materials such as Law No. 27 of 2022 concerning Personal Data Protection and Law No. 22 of 2009 concerning Traffic and Road Transportation, supplemented by secondary materials from legal literature, journals, and expert opinions. Qualitative analysis shows that e-Tilang reduces direct interaction between law enforcement and the public, thereby increasing transparency. However, this research also identifies significant challenges, including weak personal data protection and uneven distribution of technological infrastructure throughout Indonesia. These findings have implications that provide valuable insights into the implementation of e-Tilang, highlighting areas that need improvement in the legal and policy framework to increase effectiveness and fairness.

Morocco is witnessing an alarming surge in road accidents. Automatic license plate recognition (ALPR) technology is vital in enhancing road safety. It en- ables applications like traffic management, law enforcement, and toll collection by automatically identifying vehicles on the roads. This paper integrated the ShuffleNet V2 architecture into the end-to-end YOLOv5 object detection sys- tem. The goal was to develop a model capable of accurately detecting Moroc- can license plates with an 87% accuracy rate. The proposed model was able to achieve high processing speeds of 60 frames per second (FPS) while maintain- ing a compact size of 1.3 megabytes and a limited computational requirement of 0.44 million floating-point operations. Compared to other models used in similar contexts, this model demonstrates superior performance and high com- patibility with embedded systems, making it a promising solution for addressing road safety challenges in Morocco.

Abstract: This article describes the research findings behind the implementation of ETLE in motorists’ understanding and the causes of motorists' non-compliance with the implementation of CCTV-based ETLE (Electronic Traffic Law Enforcement) in Bengkulu City. The qualitative method uses non-participant observation techniques, interviews, triangulation and secondary data in the data collection process. Informants were determined by purposive sampling. The research data were analyzed using Robert K. Merton's functional structural theory. The results showed that the application of ETLE in the understanding of motorists in Bengkulu city is that this system is less effective. They argue that ETLE tends to be a form of excessive surveillance that is inappropriate in law enforcement. Motorists are also concerned about potential technical errors in the system that could result in unfairness or confusion in the administrative process. Meanwhile, the causes of motorist non-compliance with ETLE (Electronic Traffic Law Enforcement) in Bengkulu City are the low understanding of motorists towards ETLE and the culture of neglect of motorists in ignoring this ETLE system. The importance of awareness and knowledge of the use of CCTV-based ETLE (Electronic Traffic Law Enforcement) for motorists is the main focus of this topic. In addition, policymakers and law enforcement officials can take strategic steps to increase the use of CCTV-based ETLE.

Abstract: The increasing number of vehicles has created challenges in traffic monitoring, law enforcement, and vehicle management. Manual identification of vehicle license plates is time consuming, prone to errors, and inefficient, especially in high-traffic areas. This project presents an Automatic Car Number Plate Recognition System that utilizes image processing and artificial intelligence techniques to detect and recognize vehicle registration numbers automatically. The system captures images or video frames of vehicles, preprocesses them to reduce noise and enhance relevant features, and identifies the license plate region using advanced detection algorithms. The alphanumeric characters on the plate are then segmented and recognized using Optical Character Recognition (OCR). The processed results are displayed or stored for further use in applications such as traffic monitoring, toll collection, parking management, and security surveillance. The proposed system is designed to operate in real-time with high accuracy, adaptability to different lighting conditions, and robustness against plate variations. By automating vehicle identification, it reduces human intervention, improves efficiency, and contributes to safer and smarter traffic management systems.

Aim: This study intends to assess drivers’ state of knowledge on the main causes and the best strategies capable of reducing road traffic accidents in the Bongo District of Ghana.
 Study Design: The study was a descriptive design.
 Place and Duration of Study: The study was conducted in the Bongo District of the Upper East Region of Ghana between July 2023 and August 2023.
 Methodology: The researcher conducted a survey involving 100 drivers who were randomly selected from a driver population of 120 in the Bongo District. The data were analyzed using Microsoft Excel [Version 19]. The results of the data analysis were presented as tables and charts.
 Results: The study found that the main causes of road traffic accidents emanate from human error such as low driving skills, excessive speeding, and poor vision of driver. Also, road conditions like bad road networks, no lane markings, and no speed limit signs were found as causal factors of road traffic accidents. Faulty vehicles with causative factors such as defective tyres, brakes, and lights were noted to be also responsible for road accidents. Nevertheless, the least factor was environmental conditions such as bad weather conditions and stray animals being enumerable as environmental conditions which cause road accidents. The study further found that the best strategies for curbing road traffic accidents were enforcement of traffic laws, education and training of drivers, obeying traffic rules by drivers, and maintaining vehicles well.
 Conclusion: The study, therefore, concluded that human factors play a central role in contributing to road accidents and curbing road traffic accidents. The research findings can be used to guide stakeholders in formulating and prioritizing interventions that are more human-centred for the curbing of road traffic accidents in the Bongo District of Ghana.

Alcohol prohibition and law enforcement deployment are important policies designed to increase traffic safety and reduce injury crashes. This study uses data on county-level law enforcement and injury crashes to analyze the effect of traffic law enforcement and alcohol prohibition. The analysis controls for other factors that affect injury crashes such as age groups, road factors, and behavioral factors including driving under the influence convictions and suspended licenses. Analysis is presented through a negative binomial regression methodology. Results indicate that both increasing law enforcement personnel and alcohol prohibition reduce the number of injury crashes within a county. Moreover, if policymakers' goals are to reduce the count of injury crashes to zero, law enforcement and alcohol prohibition are important combined factors in this goal.

The escalating global volume of vehicles on roadways necessitates innovative solutions for efficient traffic management, heightened security, and improved law enforcement. This research project centers on developing an Automated Car Plate Recognition System (ACPRS) to address these challenges. The ACPRS utilizes cutting-edge technologies in image processing, machine learning, and database integration for accurate and real-time license plate recognition. Beginning with an exploration of existing methodologies and technologies in the field, the research highlights their strengths and limitations. The conceptualization phase involves meticulous design, incorporating image preprocessing, license plate detection, character segmentation, optical character recognition (OCR), and database interaction. The research emphasizes the utilization of advanced image processing techniques, including deep learning algorithms, for robust license plate detection. Spectral analysis and character segmentation ensure reliable recognition in challenging conditions. OCR techniques enhance alphanumeric character interpretation, contributing to overall efficacy. The implementation phase involves software development, database setup, and integration with mobile applications for enhanced accessibility. Real-world applicability and scalability are pivotal considerations. The ACPRS is deployable in various contexts, such as parking management, security systems, and access control. Compatibility with mobile applications ensures widespread accessibility, broadening potential applications in diverse settings. Security and privacy measures include user authentication and data encryption to safeguard sensitive information. To validate the ACPRS’s effectiveness, comprehensive testing and evaluation use a diverse dataset. Real-world images, synthetic data, and publicly available datasets assess performance under different conditions. Evaluation metrics such as accuracy, speed, and robustness quantify capabilities and identify areas for improvement. In conclusion, this research project represents a significant contribution to automated vehicle identification. The proposed ACPRS, focusing on accuracy, real-time processing, and mobile accessibility, addresses critical challenges in traffic management, security, and law enforcement. Thorough exploration, design, implementation, and evaluation phases ensure understanding of the system’s capabilities and potential real-world applications. This work will be very significant to the developing country in managing their traffic and other related issues.

We present here novel image processing algorithms used to identify the license plate number of vehicles. The approach taken here was developed specifically for a wireless traffic control and law enforcement system. The particular requirements involved led to a different approach than traditionally taken in vehicle plate recognition.