Automated Pneumatic Braking and Bumper System

2021 ◽  
Vol 9 (VII) ◽  
pp. 3305-3308
Author(s):  
Mr. Nale Pradeep. R
Keyword(s):  
Traffic Accidents ◽  
Causes Of Death ◽  
Sensor Data ◽  
Human Beings ◽  
Automotive Safety ◽  
Car Industry ◽  
Vehicle Accidents ◽  
Braking System ◽  
Vehicle Sensors ◽  
Bumper System

Automobiles have been used to move human beings or things and the automobile technology has been developed within the last few years. The traffic accidents are increasing as automobile production has been increasing. The number of casualties during the vehicle accidents is very large as compared to the other causes of death. It is important to prevent accidents and to protect the driver and pedestrian when accidents occur. Though there are different causes for these accidents but proper technology of braking system and technology to reduce the damage during accident (such as pneumatic bumper system) can be effective on the accident rates. Therefore, pre-crashing system is demanded. Automotive safety has gained an increasing amount of interest from the general public, governments, and the car industry. The pre-crash system is to prevent accidents on roads with poor visibility by using sensor network to find invisible vehicles, which are to be detected by autonomous on-vehicle sensors. The pre-crashing system is processing the sensor data and controlling the vehicle to prevent accidents and accidents caused by careless driving. The pneumatic system is simple and easy in operation and hence can be used in automation industry.

A Reassessment of Suicide Measurement

Crisis ◽  
2009 ◽  
Vol 30 (1) ◽  
pp. 6-12 ◽  
Author(s):  
D.P. Doessel ◽  
Ruth F.G. Williams ◽  
Harvey Whiteford
Keyword(s):  
Causes Of Death ◽  
Motor Vehicle ◽  
Years Of Life Lost ◽  
Health Prevention ◽  
Prevention Strategies ◽  
Vehicle Accidents ◽  
The Social ◽  
Evaluation Exercise ◽  
Two Measures ◽  
Circulatory Diseases

Background. Concern with suicide measurement is a positive, albeit relatively recent, development. A concern with “the social loss from suicide” requires careful attention to appropriately measuring the phenomenon. This paper applies two different methods of measuring suicide data: the conventional age-standardized suicide (count) rate; and the alternative rate, the potential years of life lost (PYLL) rate. Aims. The purpose of applying these two measures is to place suicide in Queensland in a historical and comparative (relative to other causes of death) perspective. Methods. Both measures are applied to suicide data for Queensland since 1920. These measures are applied also to two “largish” causes of death and two “smaller” causes of death, i.e., circulatory diseases, cancers, motor vehicle accidents, suicide. Results. The two measures generate quite different pictures of suicide in Queensland: Using the PYLL measure, suicide is a quantitatively larger issue than is indicated by the count measure. Conclusions. The PYLL measure is the more appropriate measure for evaluation exercise of public health prevention strategies. This is because the PYLL measure is weighted by years of life lost and, thus, it incorporates more information than the count measure which implicitly weights each death with a somewhat partial value, viz. unity.

ISO 26262 Concept Phase Analysis on Distributed Electro-Hydraulic Braking System: The Influence of System Architecture on ASIL Decomposition

2014 ◽  
Author(s):  
Zhizhong Wang ◽  
Liangyao Yu ◽  
Ning Pan ◽  
Lei Zhang ◽  
Jian Song
Keyword(s):  
System Architecture ◽  
Event Analysis ◽  
Automotive Safety ◽  
System Architectures ◽  
Iso 26262 ◽  
Braking System ◽  
Safety Integrity Level ◽  
Actuator System ◽  
Hazardous Event ◽  
Wire System

The Distributed Electro-hydraulic Braking system (DEHB) is a wet type brake-by-wire system. As a safety critical automotive electrical and/or electronic (E/E) system, DEHB shall be designed under the guideline of ISO 26262 in order to avoid unreasonable risk due to the malfunctions in the item. This paper explores how the Automotive Safety Integrity Level (ASIL) decomposition in the concept phase is influenced by the system architectures of DEHB. Based on a typical hazardous event, analysis on DEHB with the same system architecture as the Electro-mechanical Braking system (EMB) is carried out, which is taken as the basis for comparison. Two types of DEHB with different system architectures are then analyzed. Results show that the adoption of hydraulic backup enables ASIL decomposition in the pedal unit. The adoption of both hydraulic backup and normally open balance valves offers the opportunity to perform ASIL decomposition in the brake actuator system of DEHB.

scholarly journals The Contribution of Avoidable Mortality to the Life Expectancy Gains in Korea between 1998 and 2017

2020 ◽  
Vol 17 (18) ◽  
pp. 6499
Author(s):  
Jinwook Bahk ◽  
Kyunghee Jung-Choi
Keyword(s):  
Public Health ◽  
Health Policy ◽  
Life Expectancy ◽  
Traffic Accidents ◽  
Causes Of Death ◽  
Cross Sectional Study ◽  
Cerebrovascular Diseases ◽  
Avoidable Mortality ◽  
Cross Sectional ◽  
Major Factors

This study evaluated the contribution of avoidable causes of death to gains in life expectancy between 1998 and 2017 in Korea. This is a multi-year, cross-sectional study using national data. Death certificate data from 1998 to 2017 were obtained from Statistics Korea. The difference in life expectancy between 1998 and 2017 by age and cause of death were decomposed using Arriaga’s method. Life expectancy rose 7.73 years over 20 years in Korea, which was largely (more than 50%) due to changes in avoidable causes of death. As age increased, the contribution to changes in life expectancy increased, and the gain in life expectancy due to avoidable causes also tended to increase. The major factors that drove that gain in life expectancy were avoidable causes such as cerebrovascular diseases and traffic accidents. The gain in life expectancy from preventable diseases was greater in men than in women. The results of this study indicate that active public health programs have been effective in improving life expectancy in Korea. Moreover, avoidable mortality could be further improved with good public health policy. Health policy aimed at reducing amenable and preventable deaths should be further implemented to promote population health.

scholarly journals Identifying and Labeling Potentially Risky Driving: A Multistage Process Using Real-World Driving Data

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Charles Marks ◽  
Arash Jahangiri ◽  
Sahar Ghanipoor Machiani
Keyword(s):  
Real World ◽  
Traffic Accidents ◽  
Network Models ◽  
Multistage Process ◽  
Neural Network Models ◽  
Risky Driving ◽  
Vehicle Accidents ◽  
Driving Behaviors ◽  
Novel Approach ◽  
Risky Driving Behaviors

Every year, over 50 million people are injured and 1.35 million die in traffic accidents. Risky driving behaviors are responsible for over half of all fatal vehicle accidents. Identifying risky driving behaviors within real-world driving (RWD) datasets is a promising avenue to reduce the mortality burden associated with these unsafe behaviors, but numerous technical hurdles must be overcome to do so. Herein, we describe the implementation of a multistage process for classifying unlabeled RWD data as potentially risky or not. In the first stage, data are reformatted and reduced in preparation for classification. In the second stage, subsets of the reformatted data are labeled as potentially risky (or not) using the Iterative-DBSCAN method. In the third stage, the labeled subsets are then used to fit random forest (RF) classification models—RF models were chosen after they were found to be performing better than logistic regression and artificial neural network models. In the final stage, the RF models are used predictively to label the remaining RWD data as potentially risky (or not). The implementation of each stage is described and analyzed for the classification of RWD data from vehicles on public roads in Ann Arbor, Michigan. Overall, we identified 22.7 million observations of potentially risky driving out of 268.2 million observations. This study provides a novel approach for identifying potentially risky driving behaviors within RWD datasets. As such, this study represents an important step in the implementation of protocols designed to address and prevent the harms associated with risky driving.

scholarly journals Exploring Factors Influencing Injury Severity of Vehicle At-Fault Accidents: A Comparative Analysis of Passenger and Freight Vehicles

2020 ◽  
Vol 17 (4) ◽  
pp. 1146 ◽  
Author(s):  
Jianyu Wang ◽  
Huapu Lu ◽  
Zhiyuan Sun ◽  
Tianshi Wang
Keyword(s):  
Influencing Factors ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Vehicle Accidents ◽  
Passenger Vehicles ◽  
Factors Influencing ◽  
Administrative Division ◽  
Hit And Run ◽  
Side Collision ◽  
Freight Vehicles

The objective of this study is to find factors influencing the injury severity of vehicle at-fault accidents in Shenyang (China), and discuss the commonalities and differences between passenger and freight vehicle accidents. We analyzed 1647 traffic accidents from 2015 to 2017, in which motor vehicles were fully or mainly responsible, including 1164 traffic accidents caused by passenger vehicles and 483 traffic accidents caused by freight vehicles. Twenty influencing factors from the aspects of accident, driver, time, space and environmental attributes are analyzed to find their statistical connection with injury severity using the binary logistic regression model. For passenger vehicles, five influencing factors (side collision; illegal act while driving; hit-and-run; season and administrative division), showed statistically significant correlations with the injury severity. For freight vehicles, three influencing factors (illegal act while driving; season and administrative division), showed statistically significant correlations with the injury severity. Illegal act while driving is the only common influencing factor for the injury severity of both passenger and freight vehicle accidents. Side collision and hit-and-run are significant influencing factors for the injury severity of passenger vehicle accidents, but not for freight vehicle accidents. Season and administrative division present different results on influencing passenger and freight vehicle accidents. Based on these results, measures including driver education and road infrastructure improvement could be implemented to reduce the injury severity of accidents in passenger and freight vehicles.

scholarly journals The Lightweight Autonomous Vehicle Self-Diagnosis (LAVS) Using Machine Learning Based on Sensors and Multi-Protocol IoT Gateway

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2534 ◽  
Author(s):  
YiNa Jeong ◽  
SuRak Son ◽  
ByungKwan Lee
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Autonomous Vehicle ◽  
Sensor Data ◽  
The Internet ◽  
Message Queue ◽  
Road Side Unit ◽  
The Neural Network ◽  
Total Condition ◽  
Vehicle Sensors

This paper proposes the lightweight autonomous vehicle self-diagnosis (LAVS) using machine learning based on sensors and the internet of things (IoT) gateway. It collects sensor data from in-vehicle sensors and changes the sensor data to sensor messages as it passes through protocol buses. The changed messages are divided into header information, sensor messages, and payloads and they are stored in an address table, a message queue, and a data collection table separately. In sequence, the sensor messages are converted to the message type of the other protocol and the payloads are transferred to an in-vehicle diagnosis module (In-VDM). The LAVS informs the diagnosis result of Cloud or road side unit(RSU) by the internet of vehicles (IoV) and of drivers by Bluetooth. To design the LAVS, the following two modules are needed. First, a multi-protocol integrated gateway module (MIGM) converts sensor messages for communication between two different protocols, transfers the extracted payloads to the In-VDM, and performs IoV to transfer the diagnosis result and payloads to the Cloud through wireless access in vehicular environment(WAVE). Second, the In-VDM uses random forest to diagnose parts of the vehicle, and delivers the results of the random forest as an input to the neural network to diagnose the total condition of the vehicle. Since the In-VDM uses them for self-diagnosis, it can diagnose a vehicle with efficiency. In addition, because the LAVS converts payloads to a WAVE message and uses IoV to transfer the WAVE messages to RSU or the Cloud, it prevents accidents in advance by informing the vehicle condition of drivers rapidly.

scholarly journals Relationship Between Traffic Volume and Accident Frequency at Intersections

2020 ◽  
Vol 17 (4) ◽  
pp. 1393
Author(s):  
Angus Eugene Retallack ◽  
Bertram Ostendorf
Keyword(s):  
Traffic Accidents ◽  
Negative Binomial ◽  
Motor Vehicle ◽  
Traffic Volume ◽  
Accident Risk ◽  
Vehicle Accidents ◽  
Accident Frequency ◽  
Traffic Volumes ◽  
Congestion Index ◽  
Binomial Models

Driven by the high social costs and emotional trauma that result from traffic accidents around the world, research into understanding the factors that influence accident occurrence is critical. There is a lack of consensus about how the management of congestion may affect traffic accidents. This paper aims to improve our understanding of this relationship by analysing accidents at 120 intersections in Adelaide, Australia. Data comprised of 1629 motor vehicle accidents with traffic volumes from a dataset of more than five million hourly measurements. The effect of rainfall was also examined. Results showed an approximately linear relationship between traffic volume and accident frequency at lower traffic volumes. In the highest traffic volumes, poisson and negative binomial models showed a significant quadratic explanatory term as accident frequency increases at a higher rate. This implies that focusing management efforts on avoiding these conditions would be most effective in reducing accident frequency. The relative risk of rainfall on accident frequency decreases with increasing congestion index. Accident risk is five times greater during rain at low congestion levels, successively decreasing to no elevated risk at the highest congestion level. No significant effect of congestion index on accident severity was detected.

Special Issue on Intelligent Integrated Systems for Human-Oriented Information Society

2000 ◽  
Vol 12 (5) ◽  
pp. 501-501
Author(s):  
Michitaka Kameyama ◽  
Keyword(s):  
Real World ◽  
Intelligent Transportation System ◽  
Data Transfer ◽  
Image Sensor ◽  
Sensor Data ◽  
Service Robot ◽  
Human Beings ◽  
Special Issue ◽  
Real World Data

Recent advance in the information technology makes our society very convenient from the viewpoint of human-to-human information communication. However, our new living style will require not only human-tohuman communication but also autonomous intelligent applications that support human beings such as an intelligent robot system, an intelligent transportation system, and a security/safe system as shown in Figure. These applications will contribute to human-oriented information society.Intelligent vehicle Home service robot Security The use of special-purpose VLSI processors capable of processing a large amount of real-world data is essential to make such applications realistic. In recent industrial trend, the special-purpose processors are called ""System LSIs"". One of the most important environmental informations in real-world applications is a vision information. The factor common to the applications is to catch an environment information moment by moment and to respond quickly with it. Therefore, it is important to make the response time from inputs to outputs very small. In this case, sensor data transfer bottleneck is not allowed as well as memory-to-PE (Processing Element) data transfer bottleneck. An image sensor signal processing VLSI together with image sensor devices is a key issue in such applications. From the above point of views, this special issue was planned to demonstrate the recent results of this area. Finally, I would like to express my appreciation to the authors for their efforts and contributions to this special issue and also the members of the Editorial Board for their cooperation.

Sign in / Sign up

Export Citation Format

Share Document