Speed Violations Research Articles

Speeding Violation Type Prediction Based on Decision Tree Method: A Case Study in Wujiang, China

The speeding violation has become a key concern in the traffic safety management, as it increases the risk of traffic crashes, as well as the severity of these crashes. This uncivilized phenomenon is prominent and presents an increasing trend in Wujiang in recent years, which severely endangers the road traffic safety. This study is approved by the Traffic Police Brigade of Wujiang Public Security Bureau and aims to explore the characteristic of the speeding violation behaviour and attempt to make an effective prediction about it. This study proposes a speeding violation type (including type 1 and type 2) prediction method using electronic law enforcement data obtained from the public security administration of Wujiang. Before the prediction, a speeding violation influence factor analysis based on the binary logical regression model is proposed. The binary logical regression analysis identifies that the license plate, season, speeding area, position, and rainfall are the influence factors of Wujiang’s speeding violation. Then a decision tree method is used to predict the speeding violation type according to the influence factors, and from which the speeding violation situations can be determined. The prediction results demonstrate that under the hypothetical conditions, the high speeding violation level (i.e., type 2) tends to occur under high rainfall environment, and the foreign license plate and autumn present a larger probability of high speeding violation level than the local license plate and other seasons (i.e., spring, summer, and winter), respectively. Finally, a model comparison between the proposed method and other tree-based approaches is conducted. The comparison results show that the decision tree method outperforms other methods in prediction performance (including accuracy, precision, recall, and classification error), runtime, and ROC curve, which indicates that the decision tree method is feasible in predicting the speeding violation type of Wujiang. Based on the findings, the traffic managers can macroscopically grasp the speeding violation situation of the whole road networks, which can be referred for making the related polices and taking intervention measures.

Contrasting Crash- and Non-Crash-Involved Riders: Analysis of Data from the Motorcycle Crash Causation Study

Motorcycle crashes and fatalities remain a significant public health problem as fatality rates have increased substantially as compared to other vehicle types in the United States. Analysis of causal factors for motorcycle crashes is often challenging given a lack of reliable traffic volume data and the fact that such crashes comprise a relatively small portion of all traffic crashes. Given these limitations, on-scene crash investigations represent an ideal setting through which to investigate the precipitating factors for motorcycle-involved crashes. This study examines motorcycle crash risk factors by employing data recently made available from the Federal Highway Administration Motorcycle Crash Causation Study (MCCS). The MCCS represents a comprehensive investigative effort to determine the causes of motorcycle crashes and involved the collection of in-depth data from 351 crashes, as well as the collection of comparison data from 702 paired control observations in Orange County, California. This dataset provides a unique opportunity to understand how the risk of crash involvement varies across different segments of the riding population. Logistic regression models are estimated to identify the rider and vehicle attributes associated with motorcycle crashes. The results of the study suggest that motorcycle crash risks are related to rider age, physical status, and educational attainment. In addition to such factors outside of the rider’s control, several modifiable risk factors, which arguably affect the riders’ proclivity to take risks, were also found to be significantly associated with motorcycle crash risk, including motorcycle type, helmet coverage, motorcycle ownership, speed, trip destination, and traffic violation history.

Sustainable Development Goal 3.6 and road traffic injury surveillance, Nigeria West Africa,2013–2016

ObjectiveThis study aimed to describe RTC characteristics and trends in Nigeria and determine progress towards halving RTC-related deaths/injuries by 2020 [i.e., Sustainable Development Goal (SDG) Target 3.6].IntroductionGlobally, road traffic crashes (RTCs) annually kill 1.3 million people and injure 20-50 million others. Nigeria accounts for an estimated 15% of RTC deaths in the WHO African Region.MethodsWe abstracted, cleaned, and analyzed RTC surveillance data routinely collected from crash scenes from 2013-2016. Federal Road Safety Corps (FRSC) is the lead agency for RTC surveillance and regularly collates data from the 6 geopolitical zones (which contain the 36 Nigerian States and the Federal Capital Territory). We defined road traffic injury as a fatal or non-fatal injury incurred from collision on a public road involving ≥1 moving vehicle(s). We calculated descriptive statistics, frequencies, and proportions to describe RTC characteristics and trends.ResultsFrom 2013-2016, 283,949 persons were involved in 42,813 RTCs, resulting in 23,412 deaths and 127,264 injuries. Twenty-eight percent of RTCs involved ≥1 fatality. Ninety percent of persons involved in RTCs were ≥18 years old, with a male-female ratio of 3:1. The same proportion was also found for RTC deaths and for injuries. Despite containing only 15% of the country’s population, the North-Central geopolitical zone accounted for 37% of RTCs. The most common cause of RTCs was speed violations (26%). From 2013-2016, there were reductions of 30% for RTCs, 22% for number of fatalities, and 25% for number of injuries.ConclusionsNigeria reduced RTC deaths/injuries and achieved modest progress toward SDG Target 3.6. To further progress, FRSC can help by enhancing enforcement of speed violations and by educating road users about road safety practices. Also, they could investigate why certain geographical areas had disproportionate amounts of RTCs, deaths, and injuries.

The Importance of Enforcing Road Safety Laws to Reduce Road Traffic Collision (RTC) Occurrence and Fatalities in Nigeria

Introduction:Road Traffic Crashes (RTC) are one of the most preventable causes of death worldwide, yet are the number one cause of death in Nigeria. In March 2010, the United Nations General Assembly launched “The Decade of Action for Road Safety (2011-2020)” to “reduce road traffic deaths and injuries by 50% by 2020.”Aim:To analyze trends in RTC and deaths in relation to current road safety laws in Nigeria, and possible future interventions.Methods:Annual reports from 2013-2017 were obtained from the Federal Road Safety Corps (FRSC) of Nigeria. These reports were analyzed for trends in RTC, deaths, and reported causes to find areas of possible improvement.Results:The number of RTC and deaths declined yearly from 2013-2017. Crashes decreased from 23.4% in 2013-2014 to 6.2% in 2015, to 0.4% in 2016, and then increased to 3.2% in 2017. Results showed that fatalities from RTC in 2013-2014 decreased by 8.4%, then by 9.3% in 2015, and by 7.1% in 2016, but had a 1.3% increase in fatalities from 2016-2017. Analysis showed that speed violations (SPV) were the top cause of RTC. These had a decrease in the number of crashes from 5,495 (32% of RTC) in 2013, to 3,496 (29%) in 2014, to 3,195 (26.5%) in 2015. They then increased to 3,848 (33.9%) in 2016 and to 4,840 (44.1%) in 2017. There was a decline in reports of RTC caused by driving under the influence (DAD) from 1% in 2013, to 0.8% in 2014, and 0.5% in 2015 and 2016.Discussion:Current road safety laws have been effective in decreasing the total number of RTC and deaths. While certain laws such as those regarding DAD have been effective, other laws such as speed limits have been less successful and may require further changes in legal codes and/or enforcement.

Do young insured drivers slow down after suffering an accident?

Being involved in an accident may modify the behavior of an insured at the wheel due to their having an aggravated perception of risk. Here, we analyze how the behavior of young drivers is modified after an accident by comparing percentage distances driven above posted speed limits before and after the event. The possibilities afforded by telematics, in terms of gathering information about such variables as speeding, undoubtedly constitute an important step forward in quantifying effects that hitherto have gone unanalyzed in the field of road safety and car insurance. Our results show a greater reduction in the speeding of young drivers that suffer severe bodily injuries, especially in the case of men and, particularly, among those that committed more frequent speed violations prior to the accident.

Correlates of self-reported driving aberrations in Tehran: A study at the level of drivers and districts

There are relatively few comprehensive studies on driving errors and violations in Iran, a non-Western country with a high traffic fatality rate. In this study, 712 drivers completed a questionnaire at technical inspection centres and carwashes in Tehran, Iran. Respondents were asked about their demographic characteristics, accident involvement, traffic fines, and driving aberrations in the form of the Driver Behaviour Questionnaire (DBQ). The results of a principal component analysis of the DBQ showed a distinction between errors and two types of violations: speeding and non-speeding violations. Correlation analyses showed that DBQ violations were associated with a higher driving mileage, a higher education level (for DBQ speeding violations in particular), and younger age. DBQ errors were associated with risk perception, that is, the belief that one has a high probability of becoming involved in a car accident. Regression analyses showed that the DBQ speeding violations score was predictive of the number of speeding tickets and that the DBQ non-speeding violations score was predictive of involvement in minor accidents in the past three years. A correlation analysis at the level of municipal districts showed that drivers from districts with lower education and literacy levels and lower car ownership were more likely to report driving a low-cost car and had lower DBQ violations scores. These results can be interpreted as indicating that affluence enables deviant driving. We conclude that the error-violation distinction is of relevance to road safety in Tehran, both at the level of individual drivers and at the level of districts.

Towards secure and privacy preserving collision avoidance system in 5G fog based Internet of Vehicles

Current avoidance systems mainly focus on the safety of the car occupants. The surrounding entities including the pedestrians, the cyclists are assumed to use a different avoidance system for their safety. Vehicle speed is reported as one of the major factors that causes such severe road accidents that affect other entities on the road. In response, several solutions have been implemented to control the causalities of over speeding ranging from speed camera, speed detectors to car avoidance systems. However, those solutions have not significantly improved the rate of traffic accidents and their impact. Additionally, the current solutions do not ensure timely notification of all the road users (surrounding vehicle drivers, pedestrians or others) that can alleviate crash causalities in case of fatal traffic accidents. The fifth generation (5G) cellular network is predicted to overcome the current limitations of Internet-of-Vehicles (IoV) by offering fast, low latency and reliable connections to enable IoV based applications. Fog computing has also been proposed to complement IoV by bringing computational entities in nearby proximity of the vehicles. 5G based fog vehicular networks is a new paradigm that empower real-time and low latency services for Intelligent Transportation System (ITS). In this paper we proposed a secure and privacy-preserving collision avoidance system in 5G fog based IoV. The fog devices are used to collect speed violation report (TVR) sent by the vehicles’ speed sensors. The fog nodes aggregate multiple TVRs, verify the signatures on the TVRs and broadcast anonymous notifications to other entities in the vicinity. The protocol makes use of certificateless aggregate signcryption coupled with pseudonymous technique as the building blocks to ensure authentication, integrity, confidentiality and privacy preservation respectively. The batch verification technique is used by the fog devices to allow simultaneous TVRs signature verification for a timely response. The authorization of reporting speed sensors is both guaranteed by the location-based information along with the digital signature to discard all the bogus TVRs. The analysis of the protocol confirms its lightweightness and efficiency.

ФОРМУВАННЯ І АНАЛІЗ ІНФОРМАЦІЙНОЇ МОДЕЛІ ПРЕДМЕТНОЇ ОБЛАСТІ МОНІТОРИНГУ ПАРАМЕТРІВ ТАХОГРАФА І ТРЕКЕРА В СИСТЕМІ ТЕХНІЧНОГО СТАНУ ТРАНСПОРТНОГО ЗАСОБУ

To date, work is underway at KSMA, NTU, and KHAHU on the further development of information software systems for vehicle monitoring to study the possibility of remotely obtaining information on vehicle operating parameters under ITS conditions. Known vehicle monitoring systems that were developed in KHAHU and NTU under the guidance of doctors of technical sciences Volkov V. P., Mateychik V. P. and Gritsuka I. V. allow identification of the vehicle, continuous automatic measurement of parameters characterizing the state of the vehicle, diagnosing, namely monitoring the health of the vehicle and its components, recognizing and preventing the development of failures in its operation and, ultimately, ensuring the functioning of the vehicle maintenance and repair system funds for technical condition. These systems are a complex set of onboard and stationary hardware and software. But for trouble-free operation of the vehicle, monitoring of these parameters is not enough. The vehicle monitoring information system with the installed tachograph and tracker is based on the system proposed by Y. Volkov, but the peculiarity of such a system is that, in addition to monitoring the vehicle’s parameters directly, it considers the features of remote control of driver’s work and rest modes, environmental indicators of the vehicle , speed violations, etc. in modern IPC in the process of determining the parameters of the technical condition of the vehicle. The article presents the features of the implementation of the formation of the information model of the subject area for monitoring the parameters of the tachograph and tracker in the technical condition of the vehicle. An analytical description of the semantics of the system is formed using Boolean adjacency matrices that describe the relations between the components of the subject area. The main sets of relations (relationships) between the components within the information model of the subject area of the vehicle are determined. As a result of the formation of a description of the subject area for monitoring the parameters of the tachograph and tracker in the vehicle’s technical condition system, information models are obtained that provide a stable unambiguous connection of system objects with information elements and with automation objects.

Trends in road traffic accidents in Anambra State, South Eastern Nigeria: need for targeted sensitization on safe roads.

IntroductionRoad traffic accidents are leading cause of injuries and deaths globally. Low income economies are the most affected. Most causes of RTA are predictable and preventable. This study describes trends and causes of road traffic accidents in Anambra State, South Eastern Nigeria.MethodsWe conducted a retrospective study of road traffic accidents from 2010 to 2014. Data were obtained from the Federal Road Safety Commission, Anambra State Command. Information extracted included sex, age, cause of accidents, number of people and type of vehicles involved. Cases were recorded as fatal if any victim died, serious if any victim was hospitalized for more than 24 hours and minor if any victim was hospitalized for less than 24 hours. Causes of accidents were classified into human, mechanical, and climatic factors. Univariate analysis to generate frequencies and proportions was conducted using Microsoft Office Excel 2007.ResultsA total of 1,141 road traffic accidents consisting 271 fatalities, 652 serious and 218 minor cases were recorded in Anambra State from 2010-2014. Seven thousand, four hundred and forty-four persons involving 1,816 vehicles were involved in RTA that resulted in 448 deaths and 2,785 injuries. More deaths 348 (77%) and injuries 2009 (72%) occurred more in males than females. Major causes of road traffic accidents were loss of vehicle control 256 (17%) and speed violation 207 (14%). There was an increased number of persons involved in RTA in 2014 (1,842) compared with 2010 (299). In all, 3,233 casualties (deaths and injuries) and crashes (fatal, serious and minor) were recorded out of which 900 (27.8%) casualties and 294 (9.1%) crashes occurred in 2013.ConclusionLeading causes of road traffic accidents are human factors; speed violation, loss of vehicle control and dangerous driving which are sadly preventable. Sensitization and enforcement of safe road principles among commercial vehicles and car drivers will help curb this menace. Government at all levels should implement strong policies aimed at reducing the speed of vehicles on roads.

Mining Characteristics of Speeding and Red Light Running Violations Using Association Rules

Mining Characteristics of Speeding and Red Light Running Violations Using Association Rules

Investigating trade‐offs between optimal mobile photo enforcement programme plans

AbstractAgencies that manage mobile photo enforcement (MPE) programmes must decide where and when to send their limited resources to monitor compliance with speed limits. Usually, the goal is to select locations based on a number of concerns (i.e., high collision sites, high speed violation sites, school zones, etc.), which, in most cases, is conflicting. If certain locations are given more MPE resources, then by definition, other locations will receive less attention, and vice versa. This paper aims to provide insights about such MPE programme trade‐offs. We present a systematic procedure for interpreting the results of a multiobjective MPE resource allocation problem. The procedure consists of three steps: (a) Pareto front (PF) generation, (b) front representation, and (c) trade‐off analysis. First, in generating a PF, we sequentially apply two well‐known scalar optimization methods to obtain a comprehensive set of Pareto‐optimal solutions. Second, the K‐medoids clustering algorithm and the silhouette index are adopted to partition the generated PF into similar‐sized clusters, in order to help MPE programme agencies choose from a reduced set of solutions on the PF. Third, we use the response surface method to determine trade‐off patterns on the PF. The results of the front generation analysis showed that applying two optimization methods together resulted in a nearly complete PF with a relatively uniform and dense spread of solutions. Consequently, the identified set of solutions (i.e., 13,210 cases) was further partitioned into 12 clusters by silhouette index and K‐medoids. With the aim of reducing decision fatigue for agencies, each cluster's representative solution is considered a possible MPE resource allocation candidate. The trade‐off analysis indicated how much one must sacrifice in the other objectives in order to increase attainment of one particular objective. Finally, the trade‐off rate and elasticity were used to explore the quantitative relationship between the considered objectives.

Factors influencing the outcome of the Medical-Psychological Assessment of speed-affine drivers in Germany

In Germany, offenders with severe or repeated violations of traffic rules are required to pass a Medical-Psychological Assessment (MPA) to regain their driving licence. The most common offence is speeding. The present research analysed 104 MPA files from speeding offenders in order to determine whether delinquency-related variables or characteristics of the driver's behaviour change process predicts the MPA outcome (positive or negative relapse risk). The results show that characteristics of the offences themselves (e.g. the number of speed violations) do not serve as valid predictors. However, whether the offenders had voluntarily participated in a driver improvement program prior to the MPA did predict the MPA outcome. Moreover, the most suitable predictors were problem awareness and self-criticism demonstrated in the psychological assessment. Furthermore, the results underpin the suitability and utility of the MPA as a measure to evaluate relapse risks. Keywords: speeding; repeat offender; Medical-Psychological Assessment, MPA; relapse risk

Impact of automated photo enforcement of vehicle speed in school zones: interrupted time series analysis

ObjectiveMeasure the impact of automated photo speed enforcement in school zones on motorist speed and speeding violation rates during school travel.MethodsAutomated enforcement cameras, active during school commuting hours, were installed...

Gender and age distribution of motorcycle crashes in Spain

This study analysed motorcycle crashes in Spain. Ninety-nine thousand three hundred and four motorcycle crash reports filed in the years 2006–2011 were extracted from the Directorate General of Traffic database of crashes with victims. These data were analysed in terms of gender, age groups, trip purpose, type of crash, speed violation, day of the week, harm caused, use of helmet and psychophysical conditions of the driver to study the characteristics of motorcycle crashes in Spain and to assess the differences between male and female motorcycle drivers in these crashes. Significant differences were found in all the variables considered in the study, which implies gender differences in the profile of the injured motorcycle driver. The severity of motorcycle crashes suffered by male drivers is higher than that of women. These results corroborate the need to develop measures differentiated by gender, based on their profile.

Design and implementation of lightweight vehicle license plate recognition module utilizing open CV and Tesseract OCR library

Background/Objectives: In order to recognize the license plates automatically, we design and implement a vehicle license plate recognition module that extracts characters of license plate area using open source OpenCV and Terreract OCR library.Methods/Statistical analysis: The static image was binarized using OpenCV 's banalization function. After binarizing the image by adjusting the pixel values between adjacent pixels, the candidate region judged a license plate was derived. The final candidate was derived according to the proposed algorithm in the candidate region. The extracted plate area was analyzed by using the Tesseract OCR library, and characters were extracted as a character string.Findings: The vehicle license plate recognition module relates to character recognition in the field of computer vision. In this paper, we designed and implemented a module that recognizes a license plate by using open source, applying a proposed algorithm to a moving object as a static image. The proposed module is a relatively lightweight software module and can be used in other applications. It is possible to install the camera at the entrance of the apartment and can read the license plate to identify whether it is a resident or not. When speeding and traffic violations occur on the highway, the vehicle numbers can be automatically stored and managed in the database. In addition, there is an advantage that it can be applied to various character recognition applications through modification of a slight algorithm in the module.Improvements/Applications: In addition to character recognition, the OpenCV library can be applied to various fields such as pattern recognition, object tracking, and motion recognition. Therefore, we will be able to create technologies corresponding to various services that are becoming automated and unmanned.

Spotting of over Speeding Vehicles and Controlling the Speed in Highways using MEMS Sensor

This Paper describes about the spotting of an over speed of a vehicle in highway and controlling the speed of a vehicle whenever there is an uneven Condition Occurred. And alert the speed offence to control room and toll gate, the devices like Controller, RFID reader, MEMS sensor, GSM&LCD are used. The System are controlled by a microcontroller, The Micro-Controller plays an important role to do a desired task. The controller obtains the MEMS sensor, which is used to sense speed of the vehicle, Vehicle has RFID tag when speed violation take place where RFID reader reads the tag and identify the vehicle and send the information through GSM module. We design a project in such a manner that it gives an alert signal to the driver if he does not react to that, than two condition occurred first speed is been controlled and other speed offence fine is send control room and toll gate whenever vehicle crossing its maximum speed limit.

AN ALGORITHM FOR SPEED ESTIMATION AND SPEED VIOLATION DETECTION OF A VEHICLE USING COMPUTER VISION

Vehicle speed detection and violation detection is in automated way is very useful task for intelligent traffic surveillance system. Vehicle tracking in a precise way is critical task for the process of estimating the speed using only video data. This paper proposes an algorithm to estimate the speed and detecting the violation in precise way. The proposed approach gives the method which contains the optical flow algorithm with corner detection for tracking the vehicle. Proposed algorithm results the better tracking accuracy and better accuracy for speed detection. Also less computation complexity as optical flow is calculated for only corner points.

Taxi driver speeding: Who, when, where and how? A comparative study between Shanghai and New York City

ABSTRACTObjective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?)Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.

The driver behaviour questionnaire in South-East Europe countries: Bulgaria, Romania and Serbia

Using data from three samples and more than 1000 participants, this study have examined the psychometric properties of the Driver Behaviour Questionnaire (DBQ) in three countries from South-East Europe. Differences in driving behaviour between countries were also investigated. Exploratory factor analysis results supported the distinction between errors and violations in all three countries. Furthermore, the positive associations of both errors and violations with self-reported traffic accidents were also consistent in all three samples. In terms of differences in driving behaviour, Romanian drivers scored higher on many error and violation items in comparison to the other two countries. Also, speeding violations were the most common violations in all three countries. Overall, our results provide further support for using the DBQ to measure aberrant (i.e. errors and violations) driver behaviour.

Опыт апробации модели диагностики водителей, склонных к рискованному вождению (эстонская и российская выборки)

The article presents the results of approbation of the questionnaire, that allows evaluating drivers’ inclinations to taking various risks while driving. This questionnaire was developed at NPO Estonian Traffic Behaviour Development Centre, basing on PhD thesis “Evaluation of the effectiveness of a primary preventive program “Clear Picture…!?” to increase traffic safety” by G. Meinhard. Translation of the questions into Russian was performed for Russian-speaking Estonian citizens. The underlying diagnostic model of the questionnaire was implemented into a state program for preventive work with traffic offenders in Estonia in 2014. In the research AUDIT (as a part of the questionnaire) aimed at investigation of attitude towards alcohol consump tion was first used with the Russian sample. The sample included 635 drivers: 465 were Estonian citizens (15,5% females, 84,5% males) and 170 Russian citizens (38,8% females, 61,2% males). All the research participants had the history of multiple speed violations, as well as the other traffic rules violation. Some of the participants underwent medical checks for drunk driving. The results showed that the questionnaire scales, used in this diagnostic model, are highly consistent: Cronbach’s alpha ranges from 0,75 to 0,90 that proves reliability of this instrument. The exception is “Evaluation of driving threats and risks” that has Cronbach’s alpha in the range from 0,54 for the Russian sample. The article provides the first publications of the results of using this questionnaire with the Russian sample. These results can be applied to further investigations of inclination towards unsafe driving among Russian drivers as well as for implementing the underlying diagnostic model into the practice of screening and psychological counselling to prevent traffic accidents in Russia.