Increase Road Safety Research Articles

Driver Drowsy and Yawn System Alert Using Deep Cascade Convolution Neural Network DCCNN

Driver fatigue and lethargy are widely acknowledged as significant contributors to the occurrence of vehicular accidents. During the preceding decade, there were a total of 66,000 motor vehicle accidents, resulting in 22,952 fatalities and 79,545 injuries. It is of the utmost importance to implement measures designed to notify drivers in order to prevent accidents and save lives. The purpose of this research was to develop and implement a Driving Drowsiness Detection System (DDDS) in order to increase road safety. The system employs eye and mouth movements as indicators in order to detect fatigue and reduce the likelihood of accidents. Using a high-resolution camera and Deep Cascaded Convolutional Neural Networks (DCCNN) to accomplish accurate drowsiness detection was the objective of this research. This study's methodology entails the analysis of driver behavior, with a particular emphasis on eye movements captured by a high-resolution camera. The facial region was identified using landmarks extracted from the Dlib toolset, and the "Eyes Aspect Ratio" metric was developed to quantify the level of fatigue. Deep Convolutional Neural Network (DCCNN) output triggers an alarm on the dashboard of the graphical user interface (GUI). The study utilized an image with 450x320 pixels and a frame rate of 60 frames per second. In ideal lighting conditions, drowsy detection accuracy exceeded 99.9%, while in less than ideal lighting conditions, it surpassed 99.8%. Compared to previous research, the present study demonstrated a higher level of accuracy in detecting drowsiness.

A neuroergonomics approach to driver’s cooperation with Lane Departure Warning Systems

Lane Departure Warning Systems (LDWS) are automation that warn drivers in case of immediate lane departure. While LDWS are associated with increased road safety, little is known about the neural aspects of the cooperation between an LDWS and the driver behind the wheel. The present study addresses this issue by combining fMRI and driving simulation for experienced and novice drivers. The results reveal brain areas activated immediately after warning: it involves areas linked to the alertness network (midbrain, thalamus, anterior cingulate cortex), to motor actions and planning (motor and premotor cortexes; BA4/6 -cerebellum) and to attentional redirection (superior frontal cortex; BA10). There were no differences between experienced and novice drivers in this network of cerebral areas. However, prior driving experience mediates the number of lane departures. The results allow for refining a model of cooperation proposed earlier in the literature, by adding a cerebral dimension.

A Deep-Learning-Based Secure Routing Protocol to Avoid Blackhole Attacks in VANETs.

Vehicle ad hoc networks (VANETs) are a vital part of intelligent transportation systems (ITS), offering a variety of advantages from reduced traffic to increased road safety. Despite their benefits, VANETs remain vulnerable to various security threats, including severe blackhole attacks. In this paper, we propose a deep-learning-based secure routing (DLSR) protocol using a deep-learning-based clustering (DLC) protocol to establish a secure route against blackhole attacks. The main features and contributions of this paper are as follows. First, the DLSR protocol utilizes deep learning (DL) at each node to choose secure routing or normal routing while establishing secure routes. Additionally, we can identify the behavior of malicious nodes to determine the best possible next hop based on its fitness function value. Second, the DLC protocol is considered an underlying structure to enhance connectivity between nodes and reduce control overhead. Third, we design a deep neural network (DNN) model to optimize the fitness function in both DLSR and DLC protocols. The DLSR protocol considers parameters such as remaining energy, distance, and hop count, while the DLC protocol considers cosine similarity, cosine distance, and the node's remaining energy. Finally, from the performance results, we evaluate the performance of the proposed routing and clustering protocol in the viewpoints of packet delivery ratio, routing delay, control overhead, packet loss ratio, and number of packet losses. Additionally, we also exploit the impact of the mobility model such as reference point group mobility (RPGM) and random waypoint (RWP) on the network metrics.

A micro-economic model of the market uptake of truck platooning

Truck platooning is a technology allowing trucks to travel in convoy formation using wireless communications and advanced driver assistance systems. This technology is expected to increase road safety and capacity, and to decrease fuel consumption and GHG emissions; it comes with apparently important financial benefits and positive externalities. However, forecasting the market uptake of platooning is a complex economic issue, requiring a dedicated methodology.From a micro-economic standpoint, several features of truck platooning are important. First, forming a platoon implies a coordination cost. Second, platooning requires trucks with specific and costly equipment. That makes platooning a two-layer problem. Third, the decision of one carrier depends on those of other carriers: truck platooning, as a market, is characterized with network externalities. Fourth, road freight transportation is a heterogeneous system: different vehicles follow different operation patterns.This paper submits a micro-economic model of the uptake of platooning which accounts for all of the above points. First, a conditional sub-model of platoon formation is designed, where two trucks decide whether to form a platoon or not based on the net monetary benefits of doing so. Then, platoon formation is modeled in a simplified, single road context, as a Markov chain. At that stage, the share of platoonable trucks entering the market is obtained with a numerical, dynamic model. Upgrading conventional trucks to become compatible with platooning is assumed impossible.The paper concludes that due to the positive feedback loop of network externalities, market uptake is very sensitive to the economic assumptions. In addition, due to the equipment and coordination costs induced by platooning, the overall financial benefits for carriers are much lower than what they would initially appear to be; third, energy savings can be significant on the long run if the technology spreads widely.

Cycling-related cranio-spinal injuries admitted to a Major Trauma Centre in the cycling capital of the UK

Background The increased popularity of cycling is leading to an anticipated increase in cycling-related traffic accidents and a need to better understand the demographics and epidemiology of craniospinal injuries in this vulnerable road user group. This study aims to systematically investigate and characterise cycling-related head and spine injuries seen in the Major Trauma Centre for the Eastern region, which has the highest cycling rates in the UK. Methods We performed a retrospective cohort study comparing the incidence, patterns, and severity of head and spine injuries in pedal cyclists presenting to the Major Trauma Centre in Cambridge between January 2012 and December 2020. Comparisons of injury patterns, characteristics, and associations were made according to mechanism of injury, helmet use, patient age and gender. Results A total of 851 patients were admitted after being involved in cycling-related collisions over the study period, with 454 (53%) sustaining head or spine injuries. The majority of victims (80%) were male and in mid-adulthood (median age 46 years). Head injuries were more common than spine injuries, with the most common head injuries being intracranial bleeds (29%), followed by skull fractures (12%), and cerebral contusions (10%). The most common spine injuries were cervical segment fractures, particularly C6 (9%), C7 (9%), and C2 (8%). Motorised collisions had a higher prevalence of spine fractures at each segment (p < 0.001) and were associated with a higher proportion of multi-vertebral fractures (p < 0.001). These collisions were also associated with impaired consciousness at the scene and more severe systemic injuries, including a lower Glasgow coma scale (R = −0.23, p < 0.001), higher injury severity score (R = 0.24, p < 0.001), and longer length of stay (R = 0.21, p < 0.001). Helmet use data showed that lack of head protection was associated with more severe injuries and poorer outcomes. Conclusion As cycling rates continue to increase, healthcare providers may expect to see an increase in bicycle-related injuries in their practice. The insights gained from this study can inform the treatment of these injuries while highlighting the need for future initiatives aimed at increasing road safety and accident prevention.

Spatial Analysis of the Impact of Motor Vehicle Fires on the Urban Environment using the Example of Warsaw

Abstract This scientific article is dedicated to the analysis of the impact of vehicle fires on the urban environment. In the context of the dynamic processes of urbanization and societal mobilization, understanding the consequences of vehicle fires becomes exceedingly important for ensuring sustainable urban development and improving residents’ quality of life. The article presents the results of spatial analyses of vehicle fires that occurred within the Warsaw area between 2010 and 2021. In the analytical section, an attempt was made to identify the parts of the city where residents were most exposed to the emission of toxic substances. According to the presented calculations, almost 3 tons of toxic substances are released into the atmosphere every year as a result of vehicle fires in Warsaw. The article also provides information about the materials used in motor vehicles and assesses their environmental impact through the emission of hazardous substances in the event of a vehicle fire. Proposed changes that could minimize the number of vehicle fires in the future are also indicated in the article, thereby contributing to increased road safety levels in the city and positively influencing the environment.

DIGITAL ENTITIES COMMUNICATION WITHIN A BLOCKCHAIN-ENABLED INTELLIGENT TRANSPORT SYSTEM

Nowadays the blockchain is considered to be an integral part of intelligent transport systems. Intelligence of a transport systems allows to increase road safety, wisely utilize systems’ resources and provide additional services to participants. However, blockchain implementations for intelligent transport systems must be adopted to the peculiarities of such systems. This work analyzes existing blockchain solutions, their features, advantages, drawbacks, and presents a consortium type blockchain implementation for an intelligent transport system. This implementation includes a two-layered architecture of digital entities interaction, consideration for digital entities distribution over the layers, consensus mechanism selection and its implementation, trust model considerations, and a block structure for the proposed blockchain implementation. The article also brings the solution to the single point of failure vulnerability of the proposed blockchain system. Thus, the paper covers key aspects of a blockchain design for an intelligent transport system.

Road Safety as an Essential Need of Aged Population: A Case of Tabriz City, Iran

Objectives: To investigate and determine the hotspot points of traffic accidents in the Tabriz metropolis during 2020-2021. Design: Cross-sectional descriptive study. Setting(s): Tabriz, Capital of East Azarbaijan province in northwest Iran. Participants: The patients were injured in traffic accidents and transferred to hospitals with the prehospital system in Tabriz in 2020 and 2021. Interventions: Prehospital ambulances. Outcome measures: The data included the number of traffic accidents, demographic variables of patients, vital signs, the severity of the accident, the type of vehicle involved in the accident, and the location of each accident based on the division of the municipal area. Results: In this study, the ratio of male to female was 3:1, and the mean age of patients was 35±15 years. In 2020, there were 5423 traffic accidents, of which 17.6% occurred in the 7th municipal region, 16.9% in the 4th municipal region, and 12.2% in the 6th municipal region of Tabriz. In 2021, 6611 missions were carried out, 16.6% of which occurred in the 4th and 7th municipal regions, while 12.6% occurred in the 6th municipal region of Tabriz city. Conclusions: Based on the results of this study, regions 7, 4, and 6 are among the Road Traffic Accident Black Regions (RTABRs) in the Tabriz metropolis; therefore, it is necessary to review and investigate the causes of traffic accidents and carry out interventions to increase road safety.

Increasing the Safety of the Car

Road safety has improved significantly in recent years thanks to effective action taken at European and national level with changes in legislation related to improving driver and road training. As a result, EU roads are some of the safest in the world. The EU has introduced mandatory fitment of electronic stability control systems on all vehicles and advanced emergency braking and lane departure warning systems, contributing to a reduction in fatalities. Modern active safety technologies are increasingly being implemented in vehicles. The purpose of this report is to present a complex of systems, their functionality, benefit and significance for increasing road safety.

IMPROVING ROAD SAFETY ON THE NATIONAL ROAD NETWORK IN ROMANIA THROUGH PILOT SOLUTIONS

In recognition of outstanding work in the field of road safety, especially for the implementation of road safety pilot projects, N.C.R.I.A.-S.A. was declared the winner. The road safety pilot projects that have attracted the attention of the IRF, being a model to follow for all road administrations are: Roller Barriers; Impact attenuators; Road sector 2+1; Cable Road barriers; Illumination of dangerous sectors with light assemblies; Projects to increase road safety by creating elevated road crossings. The International Road Federation (IRF) encourages all companies and organizations in the road development sector to get involved in the awards program it grants, because by promoting innovative ideas a positive and motivating influence can be created. The National Company for Road Infrastructure Administration S.A, Traffic Safety Service participated in the "Find a Way Global Road Safety Award" organized by IRF. In this article, the road safety projects are presented, with their results and the road safety measures implemented by the national roads and highways administrator in Romania, so that other road administrations to be encouraged to implement as many road safety measures as possible.

Active and passive safety systems (not only) for senior citizens : Systems to increase road safety

Due to a constantly increasing life expectancy and the need to stay mobile at a high age, the proportion of over 65-year-olds in traffic accidents is increasing from year to year. In order to identify potentials for increasing the safety of seniors in road traffic, accident data were analyzed with respect to the categories of road users and accident types of this age group. Based on the accident data analysis, active and passive safety systems are described that could increase the road safety particular for senior citizens. It was found that older road users are frequently involved in accidents as car occupants, cyclists and pedestrians. In addition, car drivers and cyclists aged 65 years and older are frequently involved in driving, turning and crossing accidents. Lane departure warning and emergency braking assistants have ahigh potential for accident avoidance as they can defuse critical situations at the last moment. Restraint systems (airbags, seat belts) adapted to physical characteristics could minimize the severity of injuries to older car occupants.

A Driver Safety System using Android (Mind your Route)

Abstract: The initiative of the project is to develop an Android application which increases road safety. We aim to utilize the android studio for developing a mobile application. As there is a drastic Increase in number of vehicles so are the accidents caused in day-to-day life. So, Road Safety is the major concern. Logistics plays a vital role as it is the supply chain for delivering or transportation of goods. The heavy vehicles which are involved in this process are observed in accidents which cause huge damage to people's lives. To Improvise the safety, we are here to implement an Android Application which provides or pushes notifications/alarms.

Youth Participation in School Safety Zones Assessment: A Case Study in Indonesia

The impacts of the Manahan flyover development in front of Junior High School 1 in Surakarta City, Indonesia, increased road safety risks for the students due to poor urban mobility planning. Since its opening in late 2018, there have already been 12 crashes around the flyover, which resulted in two deaths in the two years after the opening. This research aims to assess the school safety zones using the Star Rating for Schools (SR4S) from the International Road Assessment Programme (iRAP) and propose recommendations for safer road infrastructure using a youth participation approach. The students are empowered with capacity building in road safety to be able to map road problems. They were then involved in participatory design to propose safer road infrastructure which met their needs. The SR4S results can influence the government as the decision-makers to provide a safe environment around the Manahan flyover.

Characteristics of traffic accident statistics for older road users

The comparison of different age groups both with respect to the number of traffic accident victims and in relation to the risk of causing an accident is the prerequisite for adifferentiated assessment of persons likely to be a threat and the risk. For this purpose, selected accident statistics were analyzed and evaluated in the context of general population developments. It turns out that the accident risk for older drivers over 75years of age is not exceptionally high; however, the risk of dying in aroad traffic accident is more pronounced for the group of over 75-year-olds. The result varies depending on the means of transport. The findings are intended to stimulate further discussion and give indications for areas of action to increase road safety, especially for older road users.

Automated Driver Drowsiness Detection

This project uses image processing and Python programming language to create an automatic sleepiness detection system for drivers. The system's objective is to develop an algorithm that can reliably gauge a driver's sleepiness under various circumstances by using real-time grayscale photographs. The driver will be observed by the system as it scans their face and eyelids for hypo vigilance, which is a precursor to tiredness. To properly determine the driver's level of sleepiness, the system entails three steps: feature selection, eye-pair state detection, and decision-making. The algorithm will differentiate between the two states on a collection of captured photos of both tired and awake drivers. To identify sleepiness in drivers, facial feature recognition algorithms has been employed, with an emphasis on the eye pair. Images will be taken with a mounted camera. For the system to successfully be integrated into current driver assistance systems, it will be measured on how well it is able to identify tiredness. The project's importance stem from its ability is to increase road safety by identifying driver sleepiness, a major contributing factor to accidents on the road. In conclusion, this research will significantly impact road safety by tackling the problem of accidents caused by drowsiness.

Machine learning based novel frameworks developments and architectures for secured communication in VANETs for smart transportation

Vehicle ad hoc networks have made intelligent transportation systems that significantly increase road safety as well as management possible. Vehicles can now communicate and share information about the road using this new technology. However, malicious users might inject fake emergency alerts into vehicular ad hoc network (VANET), making it impossible for nodes to access accurate road information. In vehicular ad hoc networks, assessing credibility of nodes has become a crucial task to ensure reliability as well as trustworthiness of data. Using machine learning methods, this study proposes a novel security technique that improves communication and intruder detection in VANET for smart transportation. Ciphertext-policy game theory encryption analysis for smart transportation is used here to improve the security of the VANET. Fuzzy rule-based encoder perceptron neural networks are utilized in the detection of the VANET intruder. For a variety of network datasets, the experimental analysis is conducted in terms of throughput, QoS, latency, computational cost, and data transmission rate.

Legal Framework for Rear-End Crashes in Mixed-Traffic Platooning: A Matrix Game Approach

Autonomous vehicles (AV) hold great potential to increase road safety, reduce traffic congestion, and improve mobility systems. However, the deployment of AVs introduces new liability challenges when they are involved in car accidents. A new legal framework should be developed to tackle such a challenge. This paper proposes a legal framework, incorporating liability rules to rear-end crashes in mixed-traffic platoons with AVs and human-propelled vehicles (HV). We leverage a matrix game approach to understand interactions among players whose utility captures crash loss for drivers according to liability rules. We investigate how liability rules may impact the game equilibrium between vehicles and whether human drivers’ moral hazards arise if liability is not designed properly. We find that compared to the no-fault liability rule, contributory and comparative rules make road users have incentives to execute a smaller reaction time to improve road safety. There exists moral hazards for human drivers when risk-averse AV players are in the car platoon.

Exploring the factors influencing acquisition and learning experiences of cars fitted with advanced driver assistance systems (ADAS)

Advanced Driver Assistance Systems (ADAS) have shown substantial potential to increase road safety. To guarantee a growing presence and correct use of ADAS, road safety initiatives such as driver education and programs to promote safer vehicles need to be oriented towards the specific needs of individual drivers. The aim of this study was to explore a sample of Australian drivers’ rationale for driving a vehicle with ADAS and the strategies that they use when learning to operate the functions of ADAS. Semi-structured interviews were conducted with 48 Australian drivers aged between 19 and 78 years (M = 41.54, SD = 16.32; 25 females). The results were organised into four themes: (i) reasons for driving/purchasing a car with ADAS, (ii) systems influencing driver purchasing systems, (iii) strategies used by drivers when learning about ADAS, and (iv) perceptions regarding the importance of learning and training to use ADAS. Acquisition of vehicles with ADAS frequently occurred because of the perceived safety benefits of specific systems (e.g., rear parking sensor or in-vehicle information system). Additionally, some participants did not highlight the safety benefits as the main reason for driving/purchasing a car with ADAS. Indeed, some participants mentioned that ADAS acquisition was not a reasoned process but rather an opportunistic decision when upgrading their vehicles, mainly because these systems were already included in a vehicle. Regarding education, it was found that participants were using trial-and-error as their main approach to learning about the capabilities of ADAS and official sources of knowledge about the system were rarely consulted. On a positive note, participants recognised the importance of learning to use ADAS systems correctly, showing that there is demand for effective and engaging driver education.

A Roadside and Cloud-Based Vehicular Communications Framework for the Provision of C-ITS Services

Road infrastructure plays a critical role in the support and development of the Cooperative Intelligent Transport Systems (C-ITS) paradigm. Roadside Units (RSUs), equipped with vehicular communication capabilities, traffic radars, cameras, and other sensors, can provide a multitude of vehicular services and enhance the cooperative perception of vehicles on the road, leading to increased road safety and traffic efficiency. Moreover, the central C-ITS system responsible for overseeing the road traffic and infrastructure, such as the RSUs, needs an efficient way of collecting and disseminating important information to road users. Warnings of accidents or other dangers, and other types of vehicular services such as Electronic Toll Collection (ETC), are examples of the types of information that the central C-ITS system is responsible for disseminating. To remedy these issues, we present the design of an implemented roadside and cloud architecture for the support of C-ITS services. With the main objectives of managing Vehicle-to-Everything (V2X) communication units and network messages of a public authority or motorway operator acting as a central C-ITS system, the proposed architecture was developed for different mobility testbeds in Portugal, under the scope of the STEROID research project and the pan-European Connected Roads (C-Roads) initiative. RSUs, equipped with ETSI ITS-G5 communications, are deployed with a cellular link or fiber optics connection for remote control and configuration. These are connected to a cloud Message Queuing Telemetry Transport (MQTT) broker where communication is based on a geographical tiling scheme, which allows the selection of the appropriate coverage areas for the dissemination of C-ITS messages. The architecture is deployed in the field, on several Portuguese motorways, where road traffic and infrastructure are monitored through a C-ITS platform with visualization and event reporting capabilities. The provided architecture is independent of the underlying communication technology and can be easily adapted in the future to support Cellular-V2X (PC5 interface) or 5G RSUs. Performance results of the deployed architecture are provided.

Mapping Grip Force Characteristics in the Measurement of Stress in Driving

Reducing drivers' stress can potentially increase road safety. However, state-of-the-art physiological stress indices are intrusive and limited by long time lags. Grip force is an innovative index of stress that is transparent to the user and, according to our previous findings, requires a two- to five-second time window. The aim of this study was to map the various parameters affecting the relationship between grip force and stress during driving tasks. Two stressors were used: the driving mode and the distance from the vehicle to a crossing pedestrian. Thirty-nine participants performed a driving task during either remote driving or simulated driving. A pedestrian dummy crossed the road without warning at two distances. The grip force on the steering wheel and the skin conductance response were both measured. Various model parameters were explored, including time window parameters, calculation types, and steering wheel surfaces for the grip force measurements. The significant and most powerful models were identified. These findings may aid in the development of car safety systems that incorporate continuous measurements of stress.