The Effect of Perpendicular Lamp Position on Normal Plane Alignment for Light Distribution and Coverage in Adaptive Headlamps During Complex Driving Scenarios

<div>The causes of accidents involving nonconventional bicycle types have hardly been investigated in the literature to date. However, these vehicles could play an important role in reducing the CO<sub>2</sub> emissions generated by traffic. As a basis for improving the driving safety of these environmentally friendly vehicles, this article presents the results of a survey on accidents and near-accidents of multitrack bicycle vehicles. More than 120 critical or accident situations of 86 drivers were analyzed. The situations are investigated with respect to the circumstances, the causes, and the consequences of the accidents using manual analysis and multiple correspondence analysis. A distinction is made between single accidents and accidents with another party. The aim of the survey is not to make statistically accurate statements on the frequency and probability of accidents, but rather to analyze the accident or near-accident circumstances. It is shown that the causes of single accidents are usually too high cornering velocities in combination with other factors such as road conditions. In the case of accidents with external involvement, the person who caused the accident is usually the other party involved. The accident opponent is in most cases a passenger car. Here the overlooking of the vehicles is the most frequent cause of accidents. Finally, possibilities to reduce the probability of accidents are briefly discussed for the different situations. As the research shows, most of the situations described occur on the road. This indicates that there are deficits in the bicycle infrastructure for the vehicles considered here. The results also indicate that there are deficits with regard to the perceptibility of the vehicles by other road users.</div>

Road Traffic Accident (RTA) is defined as an accident, which takes place on the road between two or more objects, in which one is any kind of moving vehicle and the other is another vehicle, pedestrian, animal, or stationary object. The major scope of this study is to analyze factors influencing road accident in Kathmandu Valley (i.e. Kathmandu, Bhaktapur and Lalitpur district), Nepal. Data used in this research were collected from Kathmandu Valley Traffic Police for FY 2070/71 to 2079/80 of the Nepalese Calendar. Both quantitative and qualitative analysis of data was performed. There were several variables used to analyze the collected data including age of driver, gender of driver, fatality rate, time of accident, reason of accident, type of vehicle involved in an accident. The result of analysis shows that 76752 accidents took place in FY 2070/71 to 2079/80. Vehicles most involved in accidents were motorcycle/scooters (54675) followed by car/jeep/van (46928) (both combining, contributing total of almost 75%). The number of male deaths was three times more than that of female death, (i.e. male death victims were 1360 and female were 409). Based on the age, 55% of total death victims were of age group 16-35 i.e. 969 deaths were of this age group. Largest number of accidents (31473) took place during 12:00-18:00 and the major cause of accidents was reckless driving. Other cause of road accident includes over speeding, alcohol consumption, pedestrian’s carelessness, road condition, physical and mental condition of driver. The objective of this research is to identify the trend of accident, investigate the possible causes of accidents, and suggest countermeasures for reducing road traffic accident.

PURPOSES: According to accident statistics for road built in 2004, the ratio of accidents on frozen roads to normal roads is 0.9%, whereas the fatality ratio is 2.7%. The risk of accidents on frozen roads is very high. Measures taken every year to prevent traffic accidents of frozen roads in the winter season are still insufficient. Additionally, measures have been established mainly on rural roads. Therefore, for urban roads, analyses and measures to prevent accidents are lacking. In this study, data on accidents on frozen roads was used to search for the causes behind these accidents and measures to reduce accidents have been recommended. METHODS: In this study, collected data from the TAMS (Traffic Accident Management System), which were collected by the Seoul National Police Agency was used. The data were divided into vehicle, people, and condition of road. The analytical model used here was the Logistic Regression Model, which is frequently used for traffic safety and accident analysis. This study uses the odds ratio analysis to search for variables related to frozen road traffic accidents in each category. A total of 18 out of 47 variables were found to be the causes of accidents. RESULTS: From the results of the comparative analysis of 18 variables, the category of the condition of the road was found to be the most critical. Contrary to expectations, more accidents occurred in clear weather than in other conditions. Accidents on bridges occurred frequently, and its odds ratio was the highest compared with other road types. When BPT is operated, the probability of accidents on frozen roads is lower than in general conditions, and accidents occurred frequently on roads with less than four lanes. CONCLUSIONS : Based on the results of this study, suggestions for reducing the risk of future domestic road accidents in freezing conditions are indicated as follows. First, it is necessary to perform a technical review of the urban road traffic accidents caused by frozen roads. Second, it is necessary to establish criteria for the study of the road environment based on the major causes of road accidents on frozen roads. Third, improvements in urban road environmental factors should be made.

Traffic accidents involving articulated vehicles are characterized by severe consequences and great material damage. Particularly accidents involving articulated vehicles such as tractors with semi-trailers have these aforementioned characteristics. In a large number of accidents involving these vehicles, the main cause of the accident is the human factor, while in others it may be caused by technical failure on the tractor or semi-trailer, road conditions, unfavorable road characteristics, etc., or a combination of several conditions. According to the NHTSA data, about 6 million traffic accidents occur in the United States annually. Heavy goods vehicles are involved in about 10% of all accidents, of which more than 50% of accidents involve tractors with semi-trailers. Accidents involving tractors are caused by technical failure on vehicles in more than 30% of cases, which is significantly higher than in traffic accidents involving other types of vehicles. The most common form of these traffic accidents is a semi-trailer skid, also called jackknifing. This paper explains the most common causes of jackknife accidents, as well as the phenomenon that is closely related to this type of accident, which in theory is called trailer swing. Special emphasis is given to the methodology of technical inspection of vehicles as a factor of preventive actions in order to eliminate technical malfunction of articulated vehicles as the cause of the destabilization of tractors or semi-trailers.

The current tendency is to attribute the cause of each road accident to certain factors that, closely related, define a system whose crisis points can construct serious elements of danger for road safety. The situation then becomes complex when it is impossible to attribute the cause of an accident to a sole component of the system ‘driver – vehicle – environment – infrastructure’, because more than one problem is present when investigating the path leading up to an event and it is unclear in what measure to hold the driver responsible for actions that have risked his or her own life, and in many cases, the lives of others. This is a problem that cannot be solved by assigning closed formulas when the investigation of different locations presents diverse characteristics and the variables in play can change even slightly from case to case in the same network under study. In this article, logistic regression models are proposed to evaluate the reliability of a roadway, where it is understood as a probability that a driver travels along a path in a specific period of time and in specific operative conditions, without an accident with injury or death occurring. The analysis has been conducted globally, placing in contemporaneous correlation infrastructural, environmental and behavioural components. The models have been applied to a stretch of freeway and state roads in the province of Cosenza (Italy) by defining the seriousness of the accidents that occurred.

The goal of this research is to apply risk management model related to the Occupational Health and Safety (OHS) by integrating Causal Effects Diagram ( CED), Analytic Network Process (ANP) and Interpretive Structural Modeling (ISM). The research method consists of three (3) stages. Stage 1) Using CED method to know the correlation between the risks and their causes. Stage 2) Making an assessment by using Analytic Network Process (ANP) with Software Matlab, stage 3) Interpretive Structural Modeling (ISM) is used to get the model of connectivity in mitigation of occupational accident. From ANP method, it is clear that the dominant potential risk in structural phase is 44% and the highest cause of accident by human factor is 77%, and it is due to the unsafe behavior. ISM method is used to know the mitigation in reducing the occupational accident risks, namely improvement of Occupational Health and Safety (OHS) management, Each Scaffolding establishment must be inspected by a certified expert, the working methods must obey the Indonesian National Standard (SNI), The risk control should be done in relation to potential cause of occupational accident which can minimize the risk on construction work ( zero accident ).

The intelligent inspection robots in substations mostly use wheeled chassis, which have good passability when running on flat roads, but it is difficult to effectively cross obstacles under terrain conditions such as steps and stairs. A quadruped inspection robot for substation is designed to improve the walking ability of the robot with a four-leg alternate walking mode to optimize the leg structure design for road conditions such as steps and stairs in the substation. The robot is equipped with pan-tilt detection components and inspection equipment such as multi-degree-of-freedom manipulators can complete intelligent inspection and lightweight maintenance tasks in open substations, and achieve full coverage of the inspection area.

A prototype for pipeline routing using remotely sensed data and geographic information system analysis

Road safety is the right of all road users. However, the reality is that the high number of deaths is still caused by accidents while driving on the road. One of the contributing factors to these accidents is the lack of warning signs when the braking system malfunctions. This study aims to monitor the temperature during braking and provide an early warning safety system for motorcycle riders based on the ESP32 microcontroller and the MAX6675 thermocouple type-K temperature sensor module. The method in this study, employed a quantitative experimental approach by conducting experiments on three types of road terrains: flat road, gentle downhill road, and steep downhill road. Braking was performed at intervals of 30 meters, with a final braking distance of 300 meters. The findings of this study indicate that the distance and road conditions have an impact on the increase in brake pad temperature. The experiments showed a significant temperature increase at a braking distance of 300 meters, with values of 99.75°C on flat roads, 115.50°C on gentle downhill roads, and 129.00°C on steep downhill roads.
 
 Keywords: early warning sign; ESP32 microcontroller; temperature monitoring; temperature sensor; road safety.

This study aims to evaluate the effect of road conditions on the fatigue life of coil springs using the strain life approach. This approach is accomplished by measuring the strain signal in the coil spring at the front of the car with a strain gauge at the component's critical point. Three different types of roads, namely flat roads, uphill roads, and downhill roads were chosen to test the strain signals obtained. After analysis, it was found that the fatigue life of the coil spring on the downhill road had the lowest value of 1.52e+4 cycles before it broke. This value is 54% lower than the fatigue life on flat roads and 96% lower than on uphill roads. This result is due to the braking factor on the way down which puts a higher tension on the coil springs, reducing their fatigue life. This study can contribute to the automotive industry to consider different road conditions in the design and testing of their products, especially in critical components such as coil springs. The strain life approach has also been shown to be effective in evaluating the fatigue life of automobile components, which can help improve vehicle quality and safety.

In this paper, research is done in the influence of different terrain and traffic conditions on road sections on the driver?s driving performances, i.e. on the car energy efficiency and CO2 emission. A methodology aimed at determining to which extent unfavorable traffic and/or terrain conditions on a road section contribute to the driver?s worse driving performances, and also to determine when the driver?s aggressive driving style is responsible for greater fuel consumption and greater CO2 emission is proposed. In order to apply the proposed methodology, a research study was carried out in a cargo transportation company and 12 drives who drove the same vehicle on five different road sections were selected. As many as 284014 of the instances of the data about the defined parameters of the road section and the driver?s driving style were collected, based on which and with the help of machine learning a prediction of the scores for the road section and the scores for the driver?s driving style was performed. The obtained results have shown that the proposed methodology is a useful tool for managers enabling them to simply and quickly determine potential room for increasing the energy efficiency of the vehicle fleet and decreasing CO2 emission.

EXPERIMENTAL AND NUMERICAL ESTIMATION OF DAMPING IN COMPOSITE PLATES WITH EMBEDDED VISCOELASTIC TREATMENTS

Driving at night with traditional headlamps poses significant threats, with many accidents occurring during the night because of temporary blindness caused by the headlights of the oncoming traffic. When in high beam, the headlights cause temporary visual impairment of human eyes called the Troxler effect. While it reduces the time to react, it also leads to decreased visibility which contributes to most mishaps that occur at night. Customarily the headlight adjustments are controlled manually where poor driving skills or error in judgment can have catastrophic effects. Accidents also occur due to poor lighting conditions as the current regular headlamp configurations do not illuminate the roads precisely, especially during curves and on unpredictable terrains. Hence, there is a need for adaptive headlamps in automobiles that can prevent Troxler’s effect on the drivers of the opposite vehicles while not compromising the road’s illumination for the driver on-board. This paper reviews research papers and patents to understand various methodologies used in implementing adaptive headlamps and explore the scope for future work in this area of research. This paper also reviews vehicle detection algorithms and various vehicle mathematical models for headlamp control based on steering angles.

Road safety assessment is imminent to reduce road accidents in Sri Lanka. The existing road safety assessments in other countries are inapplicable to Sri Lankan Road conditions as there are significant differences between the road conditions of Sri Lanka and other countries. This study aims to identify the governing roadside elements which are influential to the cause of accidents and can be used for road star rating. The study was conducted in three districts of Sri Lanka: Anuradhapura, Polonnaruwa and Kurunegala. The data for road characteristics were obtained through the Google Earth Web engine whereas accident data were collected from Sri Lanka Police. The variables such as road condition, road length, road width, delineation, shoulder condition, footpath, vehicle parking length, road divide status, roadside objects length, number of lanes, number of intersections, number of pedestrian crossings, and number of bus bays were analyzed to develop a Negative Binomial regression model considering the number of accidents as the dependent variable. The results reveal that six variables: number of lanes, road condition, number of intersections, road divide status, road section length and width of lane are significant towards the occurrence of accidents. Moreover, the results demonstrate the relationship between the road characteristics and the accident number which is crucial in road designing in order to reduce road accidents. The findings affirm the possibility in developing a road safety rating mechanism for Sri Lankan streets to standardize the road network with the international standards while enhancing the road conditions with reflecting to the required safety levels. KEYWORDS: Road safety, Road star rating, Sri Lankan roads, Negative binomial regression

Braking system is a crucial component of tractors as it ensures safe operation and control of the vehicle. The limited space availability in the workspace of a small tractor exposes the operator to undesirable posture and a maximum level of vibration during operation. The primary cause of road accidents, particularly collisions, is attributed to the tractor operator's insufficient capacity to provide the necessary pedal power for engaging the brake pedal. During the process of engaging the brake pedal, the operator adjusts the backrest support to facilitate access to the brake pedal while operating under stressed conditions. In the present study, a linear actuator‐assisted automatic braking system was developed for the small tractors. An integrated artificial neural network proportional–integral–derivative (ANN‐PID) controller‐based algorithm was developed to control the position of the brake pedal based on the input parameters like terrain condition, obstacle distance, and forward speed of the tractor. The tractor was operated at four different speeds (i.e., 10, 15, 20, and 25 km/h) in different terrain conditions (i.e., dry compacted soil, tilled soil, and asphalt road). The performance parameters like sensor digital output (SDO), force applied on the brake pedal (), and deceleration were considered as dependent parameters. The SDO was found to good approximation for sensing the position of the brake pedal during braking. The optimized network topology of the developed multilayer perceptron neural network (MLPNN) was 3‐6‐2 for predicting SDO and deceleration of the tractor with a coefficient of determination () for the training and testing datasets of the SDO and deceleration were obtained as 0.9953 and 0.9854, and 0.9254 and 0.9096, respectively. The Ziegler–Nichols (Z‐N method) method was adopted to determine the initial optimal gains of the PID controller and later these coefficients were optimized using response surface methodology. The optimized proportional (), integral (), and derivative () coefficient values were 4.8, 6.782, and 3.15, respectively. The developed integrated ANN, that is, MLPNN and PID‐based algorithm could successfully control the position of the brake pedal during braking. The stopping distance and slip of the tractor during automatic braking increased with an increase in the forward speed for the tractor from 10 to 25 km/h in all the selected terrain conditions.