Causes Of Collisions Research Articles

Effect of Turbulence on the Collision Rate between Settling Ice Crystals and Droplets

Abstract In mixed-phase clouds, graupel forms by riming, a process whereby ice crystals and supercooled water droplets settling through a turbulent flow collide and aggregate. We consider here the early stage of the collision process of small ice crystals with water droplets and determine numerically the geometric collision kernel in turbulent flows (therefore neglecting all interactions between the particles and assuming a collision efficiency equal to unity), over a range of energy dissipation rate 1–250 cm2 s−3 relevant to cloud microphysics. We take into account the effect of small, but nonzero fluid inertia, which is essential since it favors a biased orientation of the crystals with their broad side down. Since water droplets and ice crystals have different masses and shapes, they generally settle with different velocities. Turbulence does not play any significant role on the collision kernel when the difference between the settling velocities of the two sets of particles is larger than a few millimeters per second. The situation is completely different when the settling speeds of droplets and crystals are comparable, in which case turbulence is the main cause of collisions. Our results are compatible with those of recent experiments according to which turbulence does not clearly increase the growth rate of tethered graupel in a flow transporting water droplets.

디지털 트윈 기술로 협동 로봇의 고장 또는 결합 원인을 효율적으로 파악하는 시스템에 대한 연구

As the coexistence of humans and robots has increased since the start of the Fourth Industrial Revolution, this study proposes a platform for processing and analyzing data to efficiently address the causes and prevention of robot collisions at industrial sites. The platform facilitates easy and convenient data processing and analysis, allowing users to quickly identify the causes of collisions between collaborative robots as well as control equipment failures or defects. Utilizing data, the platform also enables the remote operation of equipment in virtual spaces, making it effective for communication and remote technical support in the manufacturing industry.

Distracted driving: its Causes and Effects

Distracted driving is a major problem for road safety as it is one of the main global causes of collisions and deaths. Distracted driving rates are still startlingly high even with major improvements in car safety systems and laws. This widespread problem demands a thorough examination of its origins and consequences, especially from the perspective of data science, which provides strong instruments and techniques for deciphering complicated events. All activities that take attention away from the core job of driving fall under the umbrella phrase of "distracted driving". Three broad categories of distractions exist: visual (distracting one's eyes from the road), manual (distracting one's hands from the wheel), and cognitive (distracting one's thinking from driving). Using a cell phone to text or chat, eating, drinking, interacting with other passengers, and modifying in-car entertainment or navigation systems are typical instances. Because distracted driving is a complex phenomenon that interacts with a range of environmental, behavioral, and technological factors, efforts to reduce its influence are made more difficult.

Lateral Oscillation Characteristics of Vehicle Trajectories on the Straight Sections of Freeways

The lateral oscillations of vehicle trajectories are a significant cause of collisions. There is a dearth of research, however, on the oscillatory behaviors of vehicles driving on straight sections of freeways. This study aimed to investigate the effects of vehicle type, lane position, and speed on oscillation behavior and to propose quantitative indicators to explain lateral oscillation characteristics. Based on these characteristics, a more appropriate lane width can be determined. First, the k-means algorithm was performed to cluster the vehicles into three categories: passenger cars, medium-large cars, and extra-large trucks. Then, statistical methods such as analysis of variance (ANOVA) and regression analysis were employed to elaborate on the speed distribution, lateral amplitude (LA), and distance traveled within the oscillation cycle (DTOC) for various vehicle types. The results show that different types of vehicles have different lateral oscillation tendencies. The LA and DTOC for passenger cars are generally more extensive than for medium-large cars and extra-large trucks, and their oscillation patterns are the most complicated. The vehicle trajectory oscillation pattern varies significantly for different lane positions and speeds, but speed is the dominant influencing factor. The naturalistic driving dataset from German freeways served as the foundation for this study. These results can assist road engineers in better understanding the behavioral characteristics of vehicle trajectory oscillations and designing safer freeways.

About the problem of accidents on ships

The article presents an analysis of the statistics of the consequences of accidents on ships. Particular attention is paid to the causes of collisions and ways to reduce their number. The types of damage as part of the total damage as a result of an accident on a ship are disclosed. Measures to reduce the level of accidents in river and sea transport are given.

Age, gender, personality, burnout, job characteristics and job content as predictors of driver fatigue

Objectives. Several studies have shown that one of the most common causes of collision is driver fatigue since fatigue causes drowsiness while driving and this decreases the driver’s ability to maneuver the vehicle and increases the probability of their nodding off and falling asleep at the wheel. This may be due to a variety of personal reasons and specific factors connected to working conditions. In the present work we therefore intend to develop a predictive model for fatigue in professional drivers using the following indicators: age, gender, personality, burnout, characteristics and job content. Method. The participants were 516 professional drivers from different transport sectors, obtained through non-probabilistic sampling. SPSS version 25.0 was used for data analysis. Results. The predictive capacity of a number of variables that affect drivers by causing fatigue is determined. Fatigue can be predicted through certain variables, with the best predictor being exhaustion (48.8%). Conclusions. This research contributes to a greater knowledge of the factors that produce fatigue in professional drivers. It highlights the importance of designing interventions to reduce the incidence of fatigue, resulting in greater well-being for the driver and a lower incidence of collisions.

Defending the city\u2019s cleanliness with their lives? A study of road traffic collisions involving sanitation workers in China over five years

BackgroundWith increasing urbanization in developing countries, sanitation workers are frequently involved in road traffic collisions. Our purpose was to study specific collisions involving sanitation workers and provide decision-making suggestions and reference measures for the sanitation industry and urban managers to reduce the occurrence of collisions.MethodsWe obtained online news data about sanitation worker road traffic collisions in China between 2013 and 2017 and analyzed occurrence time and location, victim characteristics, and causes of collisions.ResultsIn China, between 2013 and 2017, 511 road traffic collisions were reported, with the fewest in February and July. Most occurred around 5:00 a.m. in Eastern regions and in urban areas. Victims were mainly over 50 years old, with more females than males. Collisions usually resulted in death at the scene. The ambiguity of laws, the exploitation of workers through industry outsourcing, and the difficulty of processing claims may be the main factors preventing victims from obtaining legal compensation.ConclusionsThe most common cause of collisions was drivers’ speeding, but workers also regularly risk death by crossing the road in pursuit of their duties. The absence of legal controls for environmental protection, the excessive pursuit of efficiency in urban governance, and the lack of basic education of sanitation workers are underlying causes of collisions. Raising awareness about sanitation worker road traffic collisions will help protect the work safety rights of this vulnerable group.

Control of self-excited rotor disturbances in three-lobe journal bearing space using a couple stress lubricant

In this study, the dynamic behavior of three-lobe noncircular hydrodynamic journal bearings lubricated with couple stress fluid is presented. Currently, application of journal bearings with different geometries such as lobed bearings and using non-Newtonian lubricants, including various additives, are the common suggested solutions by tribology researchers to improve the performance of rotor-journal bearing systems. Due to the incompatibility of new lubricant behaviors including polymer chains or other types of suspended particles with considerable size from the classic Navier–Stokes equations, different models such as couple stress fluid theory have been proposed to evaluate their performance. To investigate the self-excited rotor disturbances caused by various factors, like operating in critical speeds, simultaneous solution of governing Reynolds equation of oil lubricant and the rotor motion equations has been done. The result of dynamic analyses using linear and nonlinear approaches indicates the possibility of enhancing the stiffness and damping ability of the three-lobe bearings by strengthening the couple stress properties of lubricant. It is seen from the results that by increasing the couple stress parameter of oil, the type of rotor perturbations in the bearing clearance space changes from divergent oscillations, as a leading cause of collision between the rotor surface and the bearing shell, to limit cycle motion around the rotor stable position or convergent fluctuations to the static equilibrium point. This improvement in the stability range of three-lobe journal bearings using a couple stress lubricant appears in the results of a linear analysis model in terms of increasing the critical mass parameter and decreasing the whirl frequency ratio. In addition, bifurcation diagram results show that using noncircular three-lobe bearings instead of circular types and replacing the Newtonian lubricant with the couple stress fluid improve the dynamic stability of rotor- bearing supports.

Multi-attribute decision making on mitigating a collision of an autonomous vehicle on motorways

Autonomous vehicles have the potential to improve automotive safety, largely by removing human error as a possible cause of collisions. However, it cannot be guaranteed that autonomous vehicles will be able to eliminate all collisions. Therefore, automotive safety will continue to be a necessity for automotive design. This paper proposes a decision making system which selects the least severe collision for an autonomous vehicle to take, when facing multiple imminent and unavoidable collisions on a motorway. The novel decision making system developed combines simulation results and multi-attribute decision making (MADM) methods. The simulator includes models of vehicle dynamics and the manoeuvre trajectory path. MADM methods are used to decide which vehicle(s) the autonomous vehicle should collide with, based on the severity of collisions. Severity of collisions is calculated in the simulator using the following variables: impact velocity between autonomous vehicle and vehicle ahead, impact velocity between vehicle behind and autonomous vehicle, manoeuvre acceleration and time-to-collision. Various MADM methods are investigated and three methods are selected including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Analytical Hierarchy Process (AHP), and the Analytical Network Process (ANP). Various collision scenarios are defined and tested in order to understand the impact that small changes in parameters of the autonomous vehicle and vehicles ahead and behind have on the decision made. The analysed decision making results are promising and lead to the conclusion that MADM methods can be successfully applied in autonomous vehicles.

A comparison between Artificial Neural Network and Hybrid Intelligent Genetic Algorithm in predicting the severity of fixed object crashes among elderly drivers

Run-off-road (ROR) crashes have always been a major concern as this type of crash is usually associated with a considerable number of serious injury and fatal crashes. A substantial portion of ROR fatalities occur in collisions with fixed objects at the roadside. Thus, this study seeks to investigate the severity of ROR crashes where elderly drivers, aged 65 years or more, hit a fixed object. The reason why the present study investigates this issue among older drivers is that, comparing to younger drivers, this age group of drivers have different psychological and physical features. Because of these differences, they are more likely to get injured in ROR types of crashes. This paper applies two types of Artificial Intelligence (AI) techniques, including hybrid Intelligent Genetic Algorithm and Artificial Neural Network (ANN) using the crashe information of California in 2012 obtained from Highway Safety Information System (HSIS) database. Although the results showed that the developed ANN outperformed the hybrid Intelligent Genetic Algorithm, the hybrid approach was more capable of predicting high-severity crashes. This is rooted in the way the hybrid model was trained by taking advantage of the Genetic Algorithm (GA). The results also indicated that the light condition has been the most significant parameter in evaluating the level of severity associated with fixed object crashes among elderly drivers, which is followed by the existence of the right and left shoulders. Following these three contributing factors, cause of collision, Average Annual Daily Traffic (AADT), number of involved vehicles, age, road surface condition, and gender have been identified as the most important variables in the developed ANN, respectively. This helps to identify gaps and improve public safety towards improving the overall highway safety situation of older drivers.

Nighttime driving: visual, lighting and visibility challenges.

Nighttime driving is dangerous and is one of the most challenging driving situations for most drivers. Fatality rates are higher at night than in the day when adjusted for distances travelled, particularly for crashes involving pedestrians and cyclists. Although there are multiple contributory factors, the low light levels at night are believed to be the major cause of collisions with pedestrians and cyclists at night, most likely due to their reduced visibility. Understanding the visibility problems involved in nighttime driving is thus critical, given the increased risk to road safety. This review discusses research that highlights key differences in the nighttime road environment compared to the day and how this affects visual function and driving performance, together with an overview of studies investigating how driver age and visual status affect nighttime driving performance. Research that has focused on the visibility of vulnerable road users at nighttime (pedestrians and cyclists) is also included. Collectively, the research evidence suggests that visual function is reduced under the mesopic lighting conditions of night driving and that these effects are exacerbated by increasing age and visual impairment. Light and glare from road lighting and headlights have significant impacts on vision and night driving and these effects are likely to change with evolving technologies, such as LED streetlighting and headlights. Research also highlights the importance of the visibility of vulnerable road users at night and the role of retroreflective clothing in the 'biomotion' configuration for improving their conspicuity and hence safety.

On board Driver Monitoring System with Safety Enhanced Brake System

Recent automobile vehicles require additional safety features to enhance the active safety. Due to lack of safety systems in vehicles road accidents are on the rise. The major cause of collision far 80% of accidents is drivers fault as cited by the ministry of road accidents of India. The current research work is carried out to analyze the fault of the driver and to measures the health condition of the driver by placing throb sensor and temperature sensor in steering wheel so as to slow down the vehicle by using Jake brake during abnormal health issue. The proposed systems were analyzed for different category of the condition of driver to improve the safety system technology. When triggered the exhaust valve is opened after the compression stroke enable to escape of compressed air from the cylinders to slowdown the vehicle which prevents the accidents in emergency situations.

Uncertainty Analysis of Rear-End Collision Risk Based on Car-Following Driving Simulation Experiments

Rear-end collisions are one of the most common types of accidents, and the importance of examining rear-end collisions has been demonstrated by numerous accidents analysis researches. Over the past decades, lots of models have been built to describe driving behaviour during car following to better understand the cause of collisions. However, it is necessary to consider individual difference in car-following modelling while it seems to be ignored in most of previous models. In this study, a rear-end collision avoidance behaviour model considering drivers’ individual differences was developed based on a common deceleration pattern extracted from driving behaviour data, which were collected in a car-following driving simulation experiment. Parameters of variables in the model were calibrated by liner regression and Monte Carlo method was adopted in model simulation for uncertainty analysis. Simulation results confirmed the effectiveness of this model by comparing them to the experiment data and the influence of driving speed and headway distance on the rear-end collision risk was indicated as well. The thresholds for driving speed and headway distance were 18 m/s and 15 m, respectively. An obvious increase of collision risk was observed according to the simulation results.

Assessment of collisions and grounding accidents with human factors analysis and classification system (HFACS) and statistical methods

It is important to establish all the causes of marine accidents, but this is sometimes quite difficult. Therefore, analyzing the causes by examining as many accidents as possible using a common classification system and submission of proposals is extremely essential. Overall, the study is an examination of collision and grounding accidents using the Human Factors Analysis and Classification System (HFACS). In the first phase of the study, the frequency and distribution of the causes of collision and grounding accidents were examined by HFACS categories. In the second phase, unsafe acts, which have been identified as the most important categories, and preconditions for unsafe acts are evaluated by bridge crew structure. The Chi-Square Test of Compliance and Independence and Simple Correspondence Analysis are used as statistical methods. As a result of study, the most important causes are identified as human factor differences between collision and grounding accidents, decision errors, resource management deficiencies, violations, skill-based errors and miscommunication.

Mitigating false blocking problem in wireless ad hoc networks

The hidden terminal problem in wireless sensor network (WSN) is one of the main causes of collision. Even though RTS/CTS handshaking has been implemented in CSMA/CA standard to alleviate the problem, it does not solve the collision completely. Moreover, it induces an issue called false blocking problem. Unaware of a busy status of a hidden receiver, adjacent nodes which can be potential senders will keep transmitting RTS packets to obtain a response but in vain. These RTS retransmission will cause other nodes which overhear the RTS packets blindly defer, causing them to be falsely blocked. The false blocking problem can exhaust scarce energy and degrade the network performance especially in a large distributed sensor network with heavy traffic condition. In this paper, we propose and evaluate a scheme that combines both the Block Notification (BN) and Ready-to-Send (RS) packets. The BN packet is used to notify the deferred state to adjacent nodes in order to avoid unnecessary backoff and RTS retransmissions. The RS packet, on the other hand, is used to validate the received RTS packets and in case the BN packets are not received, the node can verify the RTS packets before going to the deferred state too. Simulation results have shown that the proposed scheme can overcome the false blocking problem by reducing both the number of unnecessary RTS retransmissions and energy consumed.

Road collisions avoidance using vehicular cyber-physical systems: a taxonomy and review

AbstractRoad traffic is known to have its own complex dynamics. One implication of complexity is that road traffic collisions have become an unwelcome but unavoidable part of human life. One of the major causes of collisions is the human factor. While car manufacturers have been focusing on developing feasible solutions for autonomous and semi-autonomous vehicles to replace or assist human drivers, the proposed solutions have been designed only for individual vehicles. The road traffic, however, is an interaction-oriented system including complex flows. Such a system requires a complex systems approach to solving this problem as it involves considering not only pedestrians, road environment, but also road traffic which can include multiple vehicles. Recent research has demonstrated that large-scale autonomous vehicular traffic can be better modeled using a collective approach as proposed in the form of vehicular cyber-physical systems (VCPS) such as given by Li et al. (IEEE Trans Parallel Distrib Syst 23(9):1775–1789, 2012) or Work et al. (Automotive cyber physical systems in the context of human mobility. In: National workshop on high-confidence automotive cyber-physical systems, Troy, MI, 2008). To the best of our knowledge, there is currently no comprehensive review of collision avoidance in the VCPS. In this paper, we present a comprehensive literature review of VCPS from the collision-avoidance perspective. The review includes a careful selection of articles from highly cited sources presented in the form of taxonomy. We also highlight open research problems in this domain.

국내 구급차량의 운행 중 사고 분석에 관한 조사 연구

The purpose of this study is to investigate the circumstances surrounding collisions involving ambulances with an aim to improving the safe operation of emergency services. Collisions are relatively common within paramedic emergency services. We analyzed the time, injury site, and any other specific factors of 908 collisions occurring within four cities. Within our study 29.6% of paramedics have been involved in accidents while responding to an emergency call, with the main cause of the accident being signal violation (35.7%), and is the other party's negligence (22.2%). 92.1% of these accidents occurred while the emergency lights were being operated. XX% of accidents took place in the afternoon, while xx% took place within the hours of xx:xx and xx:xx, during which time there is generally lower levels of traffic, which can cause severe brain and neck damage of 14.4% but the other part is 62.1%. (Ed note; this is not clear at all. 14.4% of collisions resulted in severe head and neck injuries, while 23.5% of collisions resulted in no injury. According to the respondents, defensive driving (xx%), observance of traffic laws (xx%), safe driving habits (xx%)to paramedics were the most critical factors in evading collision. Signal passes were identified as the most common cause of collision (70.1%). Although the majority of collisions occurred while the emergency lights were operational, the damage can cause severe damage at the time of accident occurred. Language: ko

Development of Lane Departure Warning Traffic System

In road-transport terminology, a lane departure warning system (LDWS) is a mechanism designed to warn a driver when the vehicle begins to move out of its lane on freeways and arterial roads. These systems are designed to minimize accidents by addressing the main causes of collisions: driving error, distraction and drowsiness. In this work the authors present a system which has the potential to reduce fatalities which are caused by the common type of crashes called the Run –Off-Road (ROR) crash. The work is to build a lane Departure Warning System for use on roads and highways. The functioning of the system will be to constantly monitor the car placement in relation to the road marks (with the aid of infrared proximity sensor), detect when the driver drifts away from the current lane without an appropriate warn signal, and provide a quick and effective alert to the driver to take a corrective action. To provide an alert system to trigger the quickest response possible. So the aim of this work is to make an intelligent system in hope to design a safer mean of transportation to save lives wasted on roads yearly, especially with the increase in the number of cars introduced to the roads each year. So the need of such security systems in today’s intelligent cars is essential.

Error Detection in the Navigational Watch Based on the Behavior Analysis of Navigators

Poor lookouts, i.e. one of errors in situation awareness, are pointed out as the major cause of collisions of ships, through investigations of collision accidents. In order to evaluate safety measures for preventing collisions caused by poor lookouts, it is necessary to understand background factors, so called “contexts”, of errors in situation awareness regardless of occurrence of collisions. The purpose of this study is to point out the possible significant contexts, using a navigator’s situation awareness model. As a result, the authors point out that one of the possible significant contexts is a problem on judgment of priority levels of other ships with regard to attention.

설문분석을 통한 어선 비어선간 충돌사고에 관한 연구

The postal or group questionnaire survey was conducted to inquire into the cause of collision between fishing vessel and non-fishing vessel targeting fishing vessel personnel(FVP), non-NFVP and a person involved in a marine accident. As a result, we could verify the root cause of collision, a negligence of lookout which noted overwork for FVP and careless for non-FVP. The cause of collision by inappropriate avoid action was poor communications for FVP and non-FVP. To reduce collision, we need to be trained to take a sharp lookout, a radio communication by VHF and the collision avoidance actions by early and substantial action to keep well clear. The results are expected to contribute for the reduction of collision and victims.