Reduction Of Traffic Accidents Research Articles

A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety

Autonomous Vehicles (AV) are expected to bring considerable benefits to society, such as traffic optimization and accidents reduction. They rely heavily on advances in many Artificial Intelligence (AI) approaches and techniques. However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications. In this non-convergent context, this paper presents a systematic literature review to paint a clear picture of the state of the art of the literature in AI on AV safety. Based on an initial sample of 4870 retrieved papers, 59 studies were selected as the result of the selection criteria detailed in the paper. The shortlisted studies were then mapped into six categories to answer the proposed research questions. An AV system model was proposed and applied to orient the discussions about the SLR findings. As a main result, we have reinforced our preliminary observation about the necessity of considering a serious safety agenda for the future studies on AI-based AV systems.

The Smart City of Medellín, its achievements and potential risks

Abstract Medellín, a city in Colombia, is known for its resurrection from the status of the most dangerous city in the world to that of the most innovative one (awarded in 2013). The paper discusses the achievements of Medellín as a Smart City, which include, among others, the popularisation of Internet usage, optimisation of the urban transportation system with a reduction in traffic accidents, development of a mass transportation system with a cable car for a famous city in the developing world, improved security, together with an efficient crime reporting system and environmental risk monitoring. The potential risks involved in the implementation of ICT in city management are also discussed, related mostly to social exclusion and the actual distribution of the benefit coming from the Smart City. When compared with European cities, the additional barriers that the Colombian city needs to overcome are very high social inequalities, endemic crime, and topographic difficulties. This Latin American perspective can make clearer the difference between the Smart City in cities of the Global North vs Global South.

Review on V2X, I2X, and P2X Communications and Their Applications: A Comprehensive Analysis over Time.

Smart cities are ecosystems where novel ideas and emerging technologies meet to improve economy, environment, governance, living, and mobility. One of the pillars of smart cities is transport, with the improvement of mobility and the reduction of traffic accidents being some of the current key challenges. With this purpose, this manuscript reviews the state-of-the-art of communications and applications in which different actors of the road are involved. Thus, the objectives of this survey are intended to determine who, when, and about what is being researched around smart cities. Particularly, the goal is to situate the focus of scientific and industrial progress on V2X, I2X, and P2X communication to establish a taxonomy that reduces ambiguous acronyms around the communication between vehicles, infrastructure, and pedestrians, as well as to determine what the trends and future technologies are that will lead to more powerful applications. To this end, this literature review article presents a comprehensive study including a representative collection of the 100 most cited papers and patents published in the literature together with a statistical bibliometric analysis of 14,364 keywords over 3422 contributions between 1997 and 2018. As a result, this work provides a technological profile considering different dimensions along the paper, such as the type of communication, use case, country, organization, terminology, and year.

ICAFE: Intelligent Congestion Avoidance and Fast Emergency services

Abstract Content Centric Network (CCN) has been envisioned as a paradigm shift from client server architecture. In smart cities, transportation plays an important role where integrated services facilitate citizens through the ease of use, safety, and convenience. In this work, we propose an integrated CCN for intelligent Congestion Avoidance and Fast Emergency (iCAFE) services delivery at road side accidents. One of the significant contributions is a novel content-centric VANET-based protocol called iCAFE, an efficient traffic control algorithm and five unique packet headers for effective communications. In case of accident, emergency packets are broadcast to RSU wherein the forwarding information based (FIB) and pending interest table (PIT) are updated accordingly. The RSU broadcasts interest packets to hospital and sends a rescue message to the ambulance. The RSU also informs nearest RSUs and vehicles to evacuate the affected lane. After the rescue process is completed, the data packet is unicast from the hospital to the RSU and the PIT and FIB are updated. iCAFE achieves a high packet delivery ratio (PDR) with minimum rescue delay (R-Delay), high throughput, minimum network load, smaller collision probability, and minimum packet drop fraction. The iCAFE results are compared with the traffic accidents reduction strategy (TARS).

Survey of Financial Literacy of Bank Customers on the Use of Electronic Banking and Reducing of Traffic Accidents

Introduction: One of the factors affecting the health of the society is economic factors, and financial literacy and familiarity in the field of electronic banking can affect the economics of individuals. The purpose of this study was to investigate the effect of financial literacy of bank customers on the use of electronic banking and the reduction of traffic accidents. Methods: This descriptive study was conducted in a researcher-made questionnaire using Cronbach's alpha = 0.87. The research community was Yazd banks' customers in 2017. The research sample was determined and 380 people were randomly selected. Data analysis was performed using structural equation modeling (SEM) with partial least squares (PLS) approach. Results: Data analysis showed that 73% of the samples were male and 38% of them were between the ages of 30-39 and 41% had a bachelor's degree. The value of the path coefficient (beta) of the customers’ financial literacy to the use of electronic banking is equal to (493/0). Conclusion: The results indicated a positive and significant impact of financial literacy and its domains on the use of electronic banking, which can indirectly reduce traffic and road accidents.

Impact of regulations to control alcohol consumption by drivers: An assessment of reduction in fatal traffic accident numbers in the Federal District, Brazil

In 2008 Brazil enacted Law n° 11.705, known as the Lei Seca (in Portuguese) or Dry Law, altering the National Traffic Code by establishing zero tolerance for the presence of alcohol in drivers’ bloodstreams and toughening punishment for offenders. In 2012 the New Dry Law, Law n° 12.760 came into force in an effort to correct for legal loopholes in the earlier version and make it feasible to produce alternative forms of proof of alcohol impediment against those drivers who refused to take the breath analysis test. Sanctions for offenders were made even more severe. Ten years after the advent of the first Lei Seca this study set out to make a quantitative assessment of the two laws’ impacts regarding the reduction of lethal traffic accidents in the Federal District, Brazil. Intervention Analysis of Time Series was the technique used and transfer functions enabled the incorporation of the effects of dummy exogenous variables to the Box and Jenkins ARIMA model. Results showed that while Law n° 11.705 had no significant impact, Law 12.760 did have a statistically significant impact in reducing lethal accidents. Such results underscore the need for ex post monitoring and evaluation of Laws and confirm the premise that legislation only successfully produces its effects when compliance can be enforced.

The Effect of Urban Safe Community Implementation on the Reduction of Traffic Accidents from 2004 to 2017 in the Municipality of Zarand

The Effect of Urban Safe Community Implementation on the Reduction of Traffic Accidents from 2004 to 2017 in the Municipality of Zarand

Autonomous vehicles implementation in Lebanon: Opportunities, challenges, and ethical decisions

The Autonomous Vehicle (AV) technology allows people to travel without intervening. The quick progress in this technology and the efforts of manufacturers companies to reach fully Autonomous Vehicles (AVs) using artificial intelligent, forecast a bright future. Researches have estimated that on average, one passenger in a vehicle traveling one kilometer in Lebanon costs about $ 48, including externality components of crashes, travel time, congestion and pollution. Thus, the main purpose of this research is to highlight the opportunities of implementing AVs in Lebanon, such as reduction in traffic accidents and congestion, improvement of accessibility, human health, economic and social life. Moreover, this paper highlight the barriers standing in front of implementing this technology, like the missing of Intelligent Transportation System (ITS) and the funds needed for its execution, and gives some policy recommendations. Finally, the authors present their statistics conducted in Lebanon about ethical decisions that AVs should take particularly in case of a crash in different scenarios through the participants’ responses.

Analysis and classification of the road traffic health and safety mobile apps based on the Haddon’s matrix

Background: Road traffic accidents have been one of the main causes of death worldwide. However, most of the crashes are both predictable and preventable. With the widespread use, mobile phone is considered as a major road safety risk. However, varieties of apps have recently been developed for improving the road traffic health and safety. Despite an increasing trend of these apps, there is no comprehensive analysis of their features and no taxonomy or classification of them based on the traffic safety theories or frameworks. The aim of this study was to explore characteristics of available mobile apps on the road traffic health and safety and classify them based on the Haddon’s Matrix. Methods: To conduct this research, a comprehensive and systematic review of the mobile applications developed for the road traffic health and safety was carried out through using the qualitative content analysis. Google Play was searched through using a combination of the keywords to retrieve the road traffic apps. In order to extract the app features, their description was examined, and their content was analyzed. Then they were classified in four main categories including Road Traffic Health & safety, Road Traffic Training, Road traffic Navigation, and Other Road Traffic apps. Finally, the Haddon’s matrix was applied to analyze and classify those mobile apps residing in two main categories of the traffic health & safety, and the traffic training. Haddon’s matrix is a relevant framework for structured analyses of traffic injury events. In the Haddon’s matrix, the contributions of human, vehicle/equipment and environmental factors to the injuries in the three phases pre-crash, crash and post-crash has been presented. Results: In this study, 916 mobile apps met the inclusion criteria and were included in the final analysis.19 subcategories were identified for classifying the included apps based on their features and functionalities. In total, 620 of the mobile apps were grouped on the basis of Haddon’s matrix. About 61.76% of these apps were categorized as the traffic health & safety group. Among the subcategories of the traffic health & safety group, the highest number of apps (194) was the real-time traffic alerting apps. Behavior based feed-backing subcategory was ranked the second among the traffic health and safety apps with 75 apps. When the researchers applied factors and phases of Haddon’s framework for analyzing the apps, it was found that the Haddon’s factors have been taken into account in the apps grouped into two main categories of the apps including traffic training and traffic health & safety applications. The highest percentage of Haddon’s matrix factor considered for the intervention through the apps was related to the physical & social environment (23.69%) in the traffic training category. The features of 259 apps were classified in the Event/ Driving phase of Haddon’s matrix. Most of the apps in this phase was related to the real-time traffic alerting subgroup. These apps performed in real time while driving. The lowest number of the apps in driving phase was observed in the behavior based feed backing subcategory, which inform drivers about their driving behavior in real-time. Sixteen apps had features that categorized them in both Pre-event / Pre-driving and Event / Driving phases. In addition, 20 apps were found to have feature for intervening in both Event / Driving and Post-event / Post –driving phases. All 235 apps in the traffic training category were in pre-event/ pre-driving phase, which requires users to use these apps before driving. Conclusion: Applying Haddon’s matrix on analyzing and classifying the traffic health and safety apps revealed strengths and weaknesses of the existing related mobile apps in terms of the factors that must be considered for intervention toward prevention and reduction of road traffic accidents as the main public health issue.

Model Predictive Control for Autonomous Vehicles with Speed Profile Shaping

Abstract In recent years, automatic driving has been widely studied which is expected to promote reduction of traffic accidents. Focusing on velocity control, it is sometimes required to decelerate greatly to prevent collision with other vehicles. On the other hand, excessive acceleration or deceleration is undesirable to provide comfortable ride for passengers. This paper presents a novel method to reshape the profile of vehicle velocity based on model predictive control. Introducing combined hard and soft constraints, excessive and sudden acceleration is suppressed while a collision with other vehicles is prevented. The advantage of the proposed method is verified through a numerical simulation supposing a practical situation where an another vehicle cuts in the front space of the controlled vehicle. It is shown that the proposed method properly shapes the acceleration profile so that it adapts to such situations.

Methodology and trends for an intelligent transport system in developing countries

Increasingly, the technologies that are used in telecommunications contribute to improve intelligent transport systems. These technologies are systems that offer several concepts like vehicular ad hoc networks, which allow reduction of traffic accidents, traffic congestion and consequently increase road safety and the comfort of road users. Developing countries in general and those of sub-Sahara in particular do not have telecommunication infrastructures, even road infrastructures for the implementation of an intelligent transport system. Moreover, with the serious increase in vehicles in these countries, the problem of traffic regulation arise especially in the inter-urban context. One of the consequences of this problem is the high rate of road traffic accidents. Several models of traffic regulation as well as modeling systems of urban transport networks are presented in the literature. Unfortunately these models are intended for developed countries. The aim of this paper is to present, firstly the problems of the implementation of intelligent transport systems in developing countries like sub-Saharan Africa. Secondly, we present a survey of a road traffic model and an urban transport network models. Finally, we propose solutions, which provide methodologies for the modeling of a system and monitor traffic on inter-urban road transport networks in developing countries.

Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS)

Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to develop a protocol to avoid or prevent traffic accidents at the extreme level in order to reduce human loss. The aim of this research is to develop a new protocol, named as the Traffic Accidents Reduction Strategy (TARS), for Vehicular Ad-hoc NETworks (VANETs) to minimize the number of road accidents, decrease the death rate caused by road accidents, and for the successful deployment of the Intelligent Transportation System (ITS). We have run multiple simulations and the results showed that our proposed scheme has outperformed DBSR and POVRP routing protocols in terms of the Message Delivery Ratio (MDR), Message Loss Ratio (MLR), Average Delay, and Basic Safety Message.

Change in the profile of traumatic spinal cord injury over 15\xa0years in Spain

BackgroundTraumatic spinal cord injury remains a serious public health and social problem. Although incidence rates are decreasing in our environment, it is a high cost condition that is associated with great disability. The objective of this study was to describe the epidemiological and demographic characteristics of traumatic spinal cord injury and to analyse its epidemiological changes.MethodsThis study was an observational study with prospective monitoring of all traumatic spinal cord injury patients in the Canary Islands, Spain (2.1 million inhabitants) between 2001 and 2015.ResultsOver the specified period of the study, 282 patients suffered a traumatic spinal cord injury. The crude incidence rate was 9.3 cases per million people/year. The patients’ mean age increased from 38 years (2001–2005) to 48 years (2011–2015) (p < 0.05). Overall, 80.1% of patients were males. The trauma mechanisms of spinal cord injury were falls in 44%, traffic accidents in 36.5%, diving accidents in 8.9% and others in 10.7%. While traffic accidents decreased, falls increased, particularly in the elderly (p < 0.05). The most frequently affected level was the cervical spine (50.9%), and incomplete tetraplegia was the most prevalent group (29.8%). A total of 76.6% of all patients suffered a vertebral fracture, and 91.6% of these required surgery. Among 282 patients, 12.5% were transferred to residences. The patients transferred increased from 8.5% in the first period to 20.0% (p < 0.05) in the last period. Such cases were related to age, cervical level injuries and injuries associated with poor functionality (p < 0.05).ConclusionsThe rise in the number of falls among the older population, as well as the reduction in traffic accidents, decreased the incidence of traumatic spinal cord injury in our environment. This change in the profile of new traumatic spinal cord injuries led us to reformulate the functional objectives planned for these patients upon admission to specialized units, to plan destination-upon-discharge in advance and to promote campaigns to prevent spinal cord injury in older adults.

Not all silver lining? The Great Recession and road traffic accidents

We provide new evidence on the impact of recessions on traffic accidents by exploiting the case of Spain, where the effects of the 2008 economic crisis have been among the strongest in the developed world. We exploit differences in the incidence of the recession across Spanish provinces due to the unequal evolution of the real estate bubble across the country. We use a unique dataset on the universe of traffic accidents in Spain between 2004 and 2011. We first follow the literature on the topic and examine the impact of the economic crisis on the probability of having a traffic accident. However, we also go one step further, as we are able to identify any changes in the composition of both victims and driving behaviors as a result of the crisis. First, our results show that the Great Recession reduced traffic accidents in Spain. Second, regarding the compositional effects, we observe decreased probabilities of dying or reporting a serious injury. More important, we also detect an increase in the probability that people involved in an accident abused alcohol and drugs. Our results are robust to different measures of the crisis and the use of a spatial fixed effects model and are not biased by anticipatory effects. Finally, we show that our findings are driven by less-populated areas. Thus, we suggest that alcohol and drug control measures be reinforced during recessions and that more attention should be devoted to rural areas to strengthen the reduction in road traffic accidents.

Usefulness of hair analysis and psychological tests for identification of alcohol and drugs of abuse consumption in driving license regranting

The implementation of the points-based driving license helps to change the drivers’ behavior and is related to a reduction of traffic accidents and fatalities. In Spain, when a driver loses all points, the driving license is revoked, so the driver must enroll on a Driver Awareness and Re-education (DARE) course. However, at the moment offenders are not submitted to any test to confirm absence of alcohol or drugs of abuse consumption, even when 9% of Spanish drivers lose their driving license for driving under the influence (DUI). The objective of this pilot study was the comparison of the usefulness of psychological tests and hair analysis to identify those individuals with a chronic consumption of alcohol and drugs of abuse among drivers performing DARE courses. Volunteers were submitted to the AUDIT and DAST-10 tests. Also a hair sample was collected and analyzed for ethylglucuronide (EtG) (LOQ 5pg/mg) and 35 licit and illicit drugs (LOQ 5–50pg/mg) by LC–MS/MS. Sixty-one participants with a mean age of 37.2±11.6years, and mainly men (90.2%), were recruited and performed AUDIT and DAST-10 tests. All hair samples were analyzed for EtG and 17 samples for licit and illicit drugs. Mean AUDIT score was 9.6 (SD=7.5), showing a value ≥8 (indicator of hazardous and harmful alcohol use) in 52.4% of cases. Mean DAST-10 score was 2.9 (SD=3.3), but a score ≥6 was detected in 21.3% of cases (indicating drug abuse or dependence). Twenty-two samples were positive for EtG, 8 for drugs of abuse (8 cocaine, 2 opioids, 1 amphetamines, 1 cannabis), and 3 for medicines. EtG concentration (20.7–1254.1pg/mg) was higher than the Society of Hair Testing (SoHT) cut-off for chronic alcohol consumption (≥30pg/mg) in 21 cases. All positive cases for methadone and cannabis, and half of positive cases for opioids and cocaine presented higher concentrations than SoHT cut-offs for chronic consumption. Higher AUDIT score and higher EtG concentration in hair were statistically associated with declaration of alcohol consumption ≥4 times/month and with previous fine for DUI of alcohol. In addition, AUDIT scores and EtG concentration in hair had a moderate but significant Spearman correlation (r=0.331, p<0.05). The combination of psychological tests and hair analysis seems to be a promising tool to identify individuals with chronic and problematic consumption of alcohol and drugs of abuse. Moreover, their application during driving license regranting procedures could increase the effectiveness of DARE courses, reduce recidivism and improve road safety.

Optimization of the Allowable Speed on Iran’s Freeways to Reduce Violations and Accidents, Using Zero-Truncated Poisson Regression Model

Countries from all over the world including Iran, consider different maximum allowable speeds to control and maintain traffic safety on their freeways, but these actions have not been successful even with the police surveillance. Even though speeding is not the only cause of accidents, past studies indicate that speed plays a vital role in such events. Since respecting the speed limits have not prevented driving violations and traffic accidents, there’s doubt among decision-makers, about the applicability and safety of these legal speed limits in different weather and traffic conditions. They think perhaps there is a need for an optimized and safe speed after doing required studies. Even in the police instructions and notifications in unfavorable weather conditions, the word “safe speed” is used more than the “legal speed” and its limit is not mentioned and its determination is assigned to drivers according to their mental and physical conditions, type of vehicle, and the weather condition. This matter leads to uncertainty for drivers in selecting the right speed.This research is intended to achieve a safe and optimized speed for freeways in Iran, by considering a reasonable adjustment which is acceptable by the drivers so that a substantial decrease in driving violations and accidents could be observed. This work is done by using models developed for predicting violations and accidents on Iran’s freeways. The results indicate that by reducing the allowable speed of freeways from 125km/h to 105km/h, a 48% and 23% reduction of violations and traffic accidents could be achieved.

Analysis of Traffic Accident Reduction Effects considering Monitoring Direction of Traffic Camera

Analysis of Traffic Accident Reduction Effects considering Monitoring Direction of Traffic Camera

Extraction and Recognition of Speed Limit Signs in Night-scene Videos

Road signs provide important information that guide and regulate the behavior of drivers and pedestrians to make their travel safer and more comfortable. However, failure to recognize road signs compromises their safety. The rate of accidental death due to speed limit violation is extremely high at night. To address this problem, automatic video extraction and recognition of road signs can be utilized to contribute to a reduction in traffic accidents. In this paper, we propose an extraction method focusing on the outlines of signs, and a recognition method focusing on the numerical symbols on signs in a night-scene video.

Not All Silver Lining? The Great Recession and Road Traffic Accidents

We provide new evidence on the impact of recessions on traffic accidents, by exploiting the case of Spain, where the effects of the 2008 economic crisis have been among the strongest in the developed world. We exploit differences in the incidence of the recession across Spanish provinces due to the unequal evolution of the real estate bubble across the territory. We use a unique dataset on the universe of traffic accidents in Spain between 2004 and 2011. We first follow the literature on the topic and examine the impact of the economic crisis on the probability of having a traffic accident. However, we also go one step further, as we are able to identify any changes in the composition of both victims and driving behaviors as a result of the crisis. First, our results show that the Great Recession reduced traffic accidents in Spain. Second, for the compositional effects, we report decreased probabilities of dying or reporting a serious injury. More importantly, we also detect an increase in the probability that people involved in an accident abuse alcohol and drugs. Our results are robust to different measures of the treatment (i.e., employment in the construction sector) and the use of a spatial fixed effects model and are not biased by anticipatory effects. Finally, we show that our findings are driven by less-populated areas. Thus, we suggest that alcohol and drug control measures be reinforced during recessions and more attention should be devoted to rural areas to to strengthen the reduction of road traffic accidents.

Identifying the influences of demographic characteristics and personality of inveterate drunk drivers on the likelihood of driving under the influence of alcohol (DUIA) recurrence

ABSTRACTDriving under the influence of alcohol (DUIA) is one of the main factors that cause severe traffic crashes and is considered a grave offence under the law. As shown by existing research and statistics, one of the characteristics associated with DUIA is that DUIA offenders are more likely to be rearrested for DUIA conviction. This means that in order to eradicate DUIA, the personal, psychological, and socio-cultural characteristics of habitual drunk drivers should be examined and intensive efforts are required to manage these types of offenders. This study aims to identify how the personality traits of DUIA recidivists influence the likelihood of DUIA recurrence on urban roads. The personalities of the drivers were divided into four dimensions – psychoticism, extroversion, neuroticism, and lie – based on the Korean version of the Eysenck personality test. Four additional attributes related to drivers’ information were included: gender, blood alcohol concentration (BAC), drinking frequency, and educational background. From the analysis results, six variables were found to be significant and five variables except for educational background had a positive correlation with the possibility of DUIA recurrence. Regarding drivers’ personality traits, drivers with a higher psychoticism (P) and lie (L) had a 118% and 102% higher possibility of DUIA recurrence, respectively. The results of this study are expected to contribute to a reduction in DUIA-related traffic accidents by preventing DUIA recidivism through follow-up management such as a continuous monitoring for drivers with a higher propensity for DUIA recurrence and by establishing regulations that can administer strong punishments for DUIA recidivists.