Traffic Fines Research Articles

Road Traffic Enforcement: Using Technology Through Public-Private Partnerships (PPP)

The past two decades have seen a wide - ranging wave of privatizations in formerly government owned or - controlled activities. A government task or service which is funded and operated through a partnership between a public sector authority and private sector company based on guidelines and performance standards set by a public party is typically referred to as a Public Private Partnership (PPP). In most countries traffic enforcement cameras and other equipment are purchased, owned, and operated by government organisations. Back - offices, where violation data are processed, citations issued, and traffic fines collected, have traditionally been government - run activities. In a PPP model, a private party invests and installs enforcement equipment (e. g. speed or red - light cameras) and conducts back office processing, such as sending out violation notices and managing and confirming fine collection. The investment in equipment and related processing and support activities are funded by fine revenues collected from the motoring public over the contract term. Gaining public support, and ultimately acceptance, for the PPP model is crucial, which is why transparency, publicity and continuous communication are key factors for successful and sustainable implementation. Full service PPPs are often organised on a municipal level in close consultation with the local administration and police. Due to the high initial investment and gradual repayment, such PPPs are typically based on longer term contracts. Moreover, the regulatory environment may require some changes to allow involvement of a private party. One process that is difficult to outsource is the formal confirmation of a violation by a review of the photo or video evidence. Generally, this can only be validly performed by an authorised government official, such as a police officer. Depending on laws and regulations applicable to specific jurisdictions, there could be more issues that may limit the extent of the private party’s involvement in these PPPs. When properly implemented, PPP’s in traffic enforcement can considerably contribute to the reduction of casualties, injuries and crashes, as well as improve traffic flow, and increase quality of life with more safety, lower emissions and less noise pollution. Speed reduction also significantly benefits the safety of vulnerable road users such as pedestrians, and two - wheelers Personal injury and death on roadways also have a significant impact on the economy through medical costs, lost resources and wages and disability pay outs. These costs are significant and are estimated by the WHO to amount to an average of around 3% of a country’s GNP. This figure rises to 5% in some low - and middle - income countries

Playing politics with traffic fines: Sheriff elections and political cycles in traffic fines revenue

AbstractThe political budget cycle theory has extensively documented how politicians manipulate policies during election years to gain an electoral advantage. This paper focuses on county sheriffs, crucial but often neglected local officials, and investigates their opportunistic political behavior during elections. Using a panel data set covering 57 California county governments over four election cycles, we find compelling evidence of traffic enforcement policy manipulation by county sheriffs during election years. Specifically, a county's per capita traffic fines revenue is 30% lower in the election than in nonelection years. The magnitude of the political cycle intensifies when an incumbent sheriff runs for reelection or an election is competitive. Our findings contribute to the political budget cycle theory and provide timely insights into the ongoing debate surrounding law enforcement reform and local governments’ increasing reliance on fines and fees revenue.

How are traffic fines affected by the driver’s car price and the police officer’s discretion? A case study of Isfahan, Iran

How are traffic fines affected by the driver’s car price and the police officer’s discretion? A case study of Isfahan, Iran

Reimagining Traffic Fines and Fees

Reimagining Traffic Fines and Fees

Predation and the Disproportionate Risk of Driver’s License Suspensions in Economically and Racially Marginalized Communities

Millions of people have their driver’s licenses suspended each year when they do not pay traffic fines or appear in court, with significant and compounding consequences for their lives. The increased use of fines and fees has been likened to a predatory system that exploits the most vulnerable groups to fill state and local budget gaps. States have begun limiting suspensions for unpaid traffic tickets out of economic and racial equity concerns, but many still sanction drivers for failing to appear in court or comply with other regulations. Merging the full universe of New York Department of Motor Vehicles suspension records in 2017 with the American Community Survey at the zip code level, we find that Black, Hispanic, and economically disadvantaged communities were disproportionately impacted by both nonpayment and noncompliance suspensions. Predictive models suggest that reforms ending suspensions for both the failure to appear in traffic court and the failure to pay traffic tickets could substantially reduce these disparities.

Predicting Damage Incidents, Fines, and Fuel Consumption from Truck Driver Data: A Study from the Netherlands

Trucks are disproportionately involved in fatal traffic accidents and contribute significantly to CO2 emissions. Gathering data from trucks presents a unique opportunity for estimating driver-specific costs associated with truck operation. Although research has been published on the predictive validity of driver data, such as in the contexts of pay-how-you-drive insurance and naturalistic driving studies, the investigation into how telematics data relate to the negative consequences of truck driving remains limited. In the present study, driving data from 180 truck drivers, collected over a 2-year period, were examined to predict damage incidents, traffic fines, and fuel consumption. Correlation analysis revealed that the number of fines and damage incidents could be predicted based on the number of harsh braking events per hour of driving, whereas fuel consumption was predicted by engine torque exceedances. Our analysis also sheds light on the impact of covariates, including the engine capacity of the truck operated and time of day, among others. We conclude that the damage incidents and fines incurred by truck drivers can be predicted not only from their number of harsh decelerations but also through driving demands that extend beyond the driver’s immediate control. It is recommended that transportation companies adopt a systemic approach to mitigating truck-driving-related expenses.

New Law Enforcement Impact on the Prevention of Road Accidents in Kosovo

The strengthening of law enforcement is one aspect of traffic accident prevention initiatives that is not to be overlooked. Studies have shown that increasing law enforcement can have an impact of up to 8% (a case study in Sweden). Since the Law on Traffic Safety was replaced in 2016 with the Law on Traffic Regulations, we have been examining the Kosovo instance to determine the effects of stepping up law enforcement. The impact will be measured using statistical data from prior years and the time frame after the new law's implementation. Only those traffic fines that were directly related to the causes of accidents were used in the analysis, which compared the increase and decline of these numbers over time. The objective is to determine the ultimate actions or modifications that will have the greatest impact by measuring the impact in real values. Given that the trend of accidents by causes may be tracked for all kinds of road accidents, the high number of traffic fines classified according to the causes of accidents is a new development in the field of studies on the relationship between measures and the number of accidents. Doi: 10.28991/CEJ-2023-09-12-011 Full Text: PDF

“Their lives don't matter to politicians”: The necropolitical ecology of Thailand's dangerous and unequal roads

Thailand is consistently ranked as having the worst road safety record in Asia, and one of the worst globally. Most deaths are of the rural poor, a function of necropolitical ecology. A primary factor is the materiality and design of the road system, built to increase mobility rather than improve safety, and lacking a hierarchical structure. Highways are poorly integrated into both rural areas and Thai cities, and ignore the needs of motorcycle drivers, who comprise most road users and victims. Traffic regulations are not enforced by poorly paid police officers, without adequate resources or ability to enforce traffic fines, and who engage in corrupt practices. This is compounded by inadequate driving education. These factors are complicated and caused by Thailand's fragmented and weak governance. A plethora of agencies do not cooperate and have overlapping mandates. No lead agency has been given sufficient power to improve governance of the system. The public blame drivers rather than the state. Political leadership, in favour of quick results, has attached little importance to this issue and consequently devoted insufficient resources to address it, an inaction, ignorance and urban bias that have contributed to unnecessarily high levels of rural injuries and mortality.

Road traffic mortality in Iran: longitudinal trend and seasonal analysis, March 2011-February 2020

Road traffic mortalities (RTMs) and injuries are among the leading causes of human fatalities worldwide, particularly in low-and middle-income countries like Iran. Using an interrupted time series analysis, we investigated three interventional points (two government-mandated fuel price increases and increased traffic ticket fines) for their potential relation to RTMs. Our findings showed that while the overall trend of RTMs was decreasing during the study period, multiple individual provinces showed smaller reductions in RTMs. We also found that both waves of government-mandated fuel price increases coincided with decreases in RTMs. However, the second wave coincided with RTM decreases in a smaller number of provinces than the first wave suggesting that the same type of intervention may not be as effective when repeated. Also, increased traffic ticket fines were only effective in a small number of provinces. Potential reasons and solutions for the findings are discussed in light of Iran’s Road Safety Strategic Plan.

Utilizing MRBQ to investigate risky rider behavior in Chinese young riders: combining the effect of Big Five personality and sensation seeking

The motorcycle rider behavior questionnaire (MRBQ) is one of the most extensively used questionnaires to explore risky rider behavior worldwide. However, whether previous research adopted other scales or other versions of MRBQ, neither of them fully cover the typicality of the risky behavior in Chinese motorcyclists. Moreover, past research investigated the MRBQ while combining the joint effect of Big Five personality (BFP) and sensation seeking lacks. Our study aims to revise the Chinese version of MRBQ in young riders and explore the relationship among BFP, sensation seeking, MRBQ, and self-reported traffic violations. 278 online participants filled out the Big Five Inventory measuring BFP, the sensation seeking scale, MRBQ items selected from previous versions in other countries, and self-reported traffic violations from the traffic management system (crashes, traffic violation frequency, penalty points, and fines). Exploratory factor analysis suggested 7 factors (safety equipment, traffic errors, speed violations, control errors, stunts, traffic violations, and safety violations), and the internal consistency reliability ranged from 0.58–0.91. The hierarchical linear regression analysis showed that agreeableness and conscientiousness in BFP negatively predicted the total MRBQ score, while openness in BFP and sensation seeking positively predicted the total MRBQ score. In addition, the Poisson regression analysis suggested that all kinds of self-reported traffic violations could be positively predicted by the total MRBQ score. Path analysis suggested the fully mediating role of sensation seeking. In conclusion, the Chinese version of the MRBQ is useful for future studies and the sensation seeking plays a mediating role between the Big Five personality and MRBQ.

The effectiveness of pricing goods and services in the financial policy of public the United Arab Emirates (( analytical study for the period (2010-2019) ))

The pricing of public goods and services is one of the strategies with a significant impact on achieving a certain level of public revenue. This research explores the impact of pricing public goods and services on generating public revenues in the UAE government. By using a scientific approach that includes theoretical review, then quantitative and inductive analysis, the research examines the hypothesis that there is a relationship between fiscal policy and the pricing of public goods and services. The results show that the contribution of pricing (selected categories, customs fees, trademarks and traffic fines) is ineffective in generating public revenues. The proportions of this contribution are small and do not adequately cover public expenditures or contribute significantly to GDP. These results support the hypothesis that indicates a link between fiscal policy and the pricing of public goods and services. In addition, the research concludes by providing some insights into fiscal policy that can help government agencies in enhancing sources of financing public revenues, through the mechanism of pricing public goods and services to achieve Economic growth and development. The UAE government must make price decisions that are in line with fiscal policy, taking into account economic and social variables.

AITIA-PM: Discovering the true causes of events in a process mining context

Process mining is a research area that enables businesses to analyze and improve their processes by deriving knowledge from event logs. While pinpointing the causes of, for instance, a negative case outcome can provide valuable insights for business users, only a limited amount of research has been done to uncover causal relations within the process mining field while actively distinguishing between correlation and causality. The AITIA-PM algorithm is one of these research projects. This article updates the AITIA-PM method, which uses causality theory to measure cause-and-effect relationships in event logs. The system uses probabilistic temporal logic (PTL) to formulate hypotheses explicitly and then automatically checks them for causality using available data. More precisely, AITIA-PM is designed for process mining since it operates directly on event logs, giving users access to the information stored there, and increasing the scope for meaningful causal analysis in a process mining setting. With this addition, PTL is emphasized more as a crucial algorithmic component, and the method to control for false discovery rates (FDR) is adjusted for increased practical use. The case study shows that after the domain expert provides the search space of hypotheses, the AITIA-PM algorithm can extract valuable cause–effect insights from an event log. The search space can be flexibly defined, making AITIA-PM a powerful tool for business users. An evaluation on artificial data proves AITIA-PM is capable of extracting the causal relationships, while a demonstration on the Road Traffic Fines Management dataset shows the applicability of the algorithm on real data.

Sighted-Helmet Detection and E-Challan Application

Abstract: Helmet detection is a technology that uses computer vision algorithms to automatically detect and identify individuals who are not wearing helmets while riding a two-wheeled vehicle. This technology is often used in conjunction with e-challan systems, which are electronic systems for issuing traffic violations and fines. By combining helmet detection with e-challan, law enforcement officials can more effectively enforce helmet laws and reduce the number of injuries and deaths caused by head injuries in motorcycle accidents. The technology can be used in various forms like CCTV cameras, drones, etc. The Helmet detection algorithm uses deep learning techniques like CNN, YOLOv8 etc to detect and classify the helmets in real-time video feed. We have developed an application “Sighted”, which is used to track the current active challans issued in the name of the owner and easy payment of the fines. The main objective of the system is to identify riders without helmet and issue a challan with an application providing services to track the challan status and payment.

Driving Fine and its Relationship with Dangerous Driving Behaviour Among Heavy Vehicle Drivers.

There is a significant difference between actual and existing statistics of traffic fines; since some invisible fines and most of the visible traffic violations cannot be recorded by traffic officers. Therefore, dealing with driving fines and road fatalities is considered an important issue in social and public management worldwide. Explore the factors associated with unsafe behaviors and getting traffic fines among a sample of Iranian heavy-vehicle professional drivers. The present cross-sectional study was conducted in Iran, from February 2019 to September 2020. This study used the driver behavior questionnaire (DBQ), demographic and driving characteristics, the number of fines, and structural equation modeling. Also, in this study 320 professional drivers participated. This article used structural equation modeling for Statistical analysis. The results of structural equation modeling analysis indicated that the data fit well with the theoretical model proposed in this study. The number of fines was directly predicted by both demographic and driving characteristics and risky driving behaviors. A significant relationship was observed between, driving hours, driving experience, and smoking, respectively, with a mistake, slip, and risky violation. There was a negative correlation between education and all four sub-scales of risky driving behaviors. In order to reduce traffic fines, training courses on increasing attention and precision in drivers' observations and judgments are useful. The courses can decrease traffic violations by trying to change beliefs, attitudes, and social norms. It is therefore helpful to understand the ways to change the drivers' attitudes.

A Clustering Approach to Identify High-Risk Taxi Drivers Based on Self-Reported Driving Behavior

This study aimed to evaluate the driving behavior of taxi drivers in Isfahan, Iran, and assess the probability of a driver being among the high-risk taxi drivers. To identify risky driving behaviors among taxi drivers, the Driver Behavior Questionnaire (DBQ) was used. By collecting data from 548 taxi drivers, exploratory factor analysis identified the significant components of DBQ including “Inattention errors,” “Inexperience errors,” “Lapses,” “Ordinary violations,” and “Aggressive violations.” K-means clustering was conducted to cluster taxi drivers into three risk groups of low-risk, medium-risk, and high-risk taxi drivers based on their self-reported annual traffic crashes and fines. In addition, logistic regressions identified the extent to which drivers’ crashes and traffic fines are related to their driving behavior, and therefore, what aberrant driving behaviors are more important in explaining the presence of taxi drivers in the high-risk cluster. The results revealed that the majority of participants (66.78%) were low-risk taxi drivers. Aggressive violations and ordinary violations were significant predictors of taxi drivers being in the high-risk group, while inattention errors and aggressive violations were significant predictors of being in the medium/high-risk cluster. The findings from this study are valuable resources for developing safety measures and training for new drivers in the taxi industry.

Costs and Consequences of Traffic Fines and Fees in Nevada

Traffic stops and traffic tickets often have far-reaching consequences for poor and marginalized communities, yet resulting fines and fees increasingly fund local court systems. This study critically explores who bears the brunt of traffic fines and fees in Nevada, historically one of the fastest growing and increasingly diverse states in the nation. Nevada is one of thirteen US states to prosecute minor traffic violations as criminal misdemeanors rather than civil infractions. Drawing on legislative histories, we find that state legislators in Nevada increased fines and fees to raise revenues. Using descriptive statistics, we analyzed 2012–2020 open arrest warrant data extracted from the Las Vegas Municipal Court and found that 83.3% of all open bench warrants were issued for traffic charges. 58.6% were for administrative infractions – vehicle registration and maintenance, no or expired license, plates, or insurance – as opposed to only 24.7% for behavioral violations such as speeding, reckless driving, and DUI. Those issued warrants for failure to pay monetary sanctions are disproportionately people who are Black and from the poorest areas in the region. Ultimately, the Nevada system of fines and fees criminalizes poverty and reinforces racial disparities.

Assessing Risk Perception over Recidivist Traffic Offenders from a Multi-group Approach: How Gendered Could It Be?

Objective: The core aim of this study was to examine the predictive role of demographic, psychosocial and driving features of Spanish drivers on their risk perception over recidivist traffic offenders, focusing on gender as a key differentiating factor. Method: For this cross-sectional study, it was analyzed the data gathered from a nationwide sample of 1,711 licensed drivers from the 17 regions of Spain (49% females, 51% males) with a mean age of 40.07 years, responding to a telephone-based interview on road safety issues. Demographic, driving-related and psychosocial factors were comparatively analyzed through robust tests and a bias-corrected MGSEM (Multi-Group Structural Equation Modeling) approach.Results: The findings of this study indicate that drivers’ age, driving exposure, traffic law knowledge, their assessment of both enforcement and reeducation, and the number of traffic fines they have received, explain the risk perceived in recidivist traffic offenders. Secondly, and in regard to structural differences, three study variables, i.e., driving exposure, need for enforcement and traffic law knowledge, have shown to exert a differential influence on risk perception according to drivers’ gender.Conclusion: The findings of this study suggest that both psychosocial and driving-related features differentially predict drivers’ risk perception over recidivist traffic offenders between male and female drivers. This research supports the need of fostering the emphasis on gender, in order to strengthen driving education, re-education, and training processes aimed at facing and preventing recidivism in the field of traffic and mobility.

Analysis of traffic rule violations among bike riders. A structural equation model

Bikes are becoming an increasingly popular and reliable mode of transportation in developing countries because of their efficiency and ability to navigate through rough terrain and narrow roadways. Bikes are more vulnerable to road accidents and their riders’ safety is the main concern at present days. Hence, it is essential to reduce the possibility of accidents caused by bike riders. The main reason for bike accidents is bike rider behaviours in the form of traffic rules violations. The paper’s main aim is to categorize the importance of seven attributes on traffic rules violations, including bike rider behaviours, road features, ambient conditions, driving skills, type of license, bike age/tenure and riding without a safety device (helmet). Bike riders’ violations that can lead to an accident and the impact of attributes have been analyzed using the structural equation modelling (SEM) technique. To analyze these attributes, 450 bike riders have been interviewed in Bhubaneswar, India. It has been concluded that bike rider behaviours are the most significant attribute of violations. Since most bike riders are young, with low income and education, paying more attention to their training and education before issuing a driving license is necessary. In addition, those who do not use safety devices (helmets) are more susceptible to committing violations. This relates to the lack of enough control and enforcement in developing cities. Also, it shows that the current traffic fines for not using safety devices (helmets) are not enforced enough. Finally, considering this research’s outcomes can help minimize traffic rules violations among bike riders, which is a step towards safer roads.

A Critical evaluation of the impacts of “Wasta” on employees and organizations in Qatar

Wasta is an Arabic word (واسطة), with a similar meaning to nepotism in English, which means using someone’s connections or influence to achieve multiple benefits, for example securing a job, speeding up access to government services, gaining exemption from taxes, pushing for fees reduction, favoring transfers and promotions of public servants, and even waiving of traffic fines. It has become deeply rooted in the Middle East culture, especially in Qatar. This study argues that wasta has become a cultural paradox that intersects with classes as a social construction, reinforcing racism, class privilege, and social inequalities among employees in Qatar. This paper is critical as it addresses this threatening issue that has severe consequences on the country’s progress, highlights its root cause, and examines the impact of this social phenomenon. This paper is the first step forward to face the wasta phenomenon in Qatar.

Costs and Consequences of Traffic Fines and Fees: A Case Study of Open Warrants in Las Vegas, Nevada

Traffic stops and tickets often have far-reaching consequences for poor and marginalized communities, yet resulting fines and fees increasingly fund local court systems. This paper critically explores who bears the brunt of traffic fines and fees in Nevada, historically one of the fastest growing and increasingly diverse states in the nation, and one of thirteen US states to prosecute minor traffic violations as criminal misdemeanors rather than civil infractions. Drawing on legislative histories, we find that state legislators in Nevada increased fines and fees to raise revenues. Using descriptive statistics to analyze the 2012–2020 open arrest warrants extracted from the Las Vegas Municipal Court, we find that 58.6% of all open warrants are from failure to pay tickets owing to administrative-related offenses—vehicle registration and maintenance, no license or plates, or no insurance. Those issued warrants for failure to pay are disproportionately for people who are Black and from the poorest areas in the region. Ultimately, the Nevada system of monetary traffic sanctions criminalizes poverty and reinforces racial disparities.