8th grader's traffic safety research wins prize

1999 ◽  
Keyword(s):  
Traffic Safety ◽  
Safety Research

scholarly journals Recognition Method of Drinking-driving Behaviors Based on PCA and RBF Neural Network

2018 ◽  
Vol 30 (4) ◽  
pp. 407-417
Author(s):  
Yifan Sun ◽  
Jinglei Zhang ◽  
Xiaoyuan Wang ◽  
Zhangu Wang ◽  
Jie Yu
Keyword(s):  
Neural Network ◽  
Traffic Safety ◽  
Road Traffic ◽  
Rbf Neural Network ◽  
Principal Component ◽  
Physiological Data ◽  
Recognition Model ◽  
Driving Behaviors ◽  
Model Based ◽  
Safety Research

Drinking-driving behaviors are important causes of road traffic injuries, which are serious threats to the lives and property of traffic participants. Therefore, reducing the occurrences of drinking-driving behaviors has become an important problem of traffic safety research. Forty-eight male drivers and six female drivers who could drink moderate alcohol were chosen as participants. The drivers’ physiological data, operation behavior data, car running data, and driving environment data were collected by designing various virtual traffic scenes and organizing drivers to conduct driving simulation experiments. The original variables were analyzed by the Principal Component Analysis (PCA), and seven principal components were extracted as the input vector of the Radial Basis Function (RBF) neural network. The principal component data was used to train and verify the RBF neural network. The Levenberg-Marquardt (LM) algorithm was chosen to train the parameters of the neural network and build a drinking-driving recognition model based on PCA and RBF  neural network to realize an accurate recognition of drinking-driving behaviors. The test results showed that the drinking-driving recognition model based on PCA and RBF neural network could identify drinking drivers accurately during driving process with a recognition accuracy of 92.01%, and the operation efficiency of the model was high. The research can provide useful reference for prevention and treatment of drinking and  driving and traffic safety maintenance.

scholarly journals A comparison of pharmacoepidemiological study designs in medication use and traffic safety research

2012 ◽  
Vol 27 (6) ◽  
pp. 473-481 ◽  
Author(s):  
Silvia Ravera ◽  
Nienke van Rein ◽  
Johan J. de Gier ◽  
Lolkje T. W. de Jong-van den Berg
Keyword(s):  
Traffic Safety ◽  
Medication Use ◽  
Pharmacoepidemiological Study ◽  
Safety Research ◽  
Study Designs

Tire Pressure Monitoring Inflatable Restraint System

2011 ◽  
Vol 328-330 ◽  
pp. 1705-1708
Author(s):  
Tan Li ◽  
Xi Chen ◽  
Qi Xin Yin ◽  
Yong Ping Hou
Keyword(s):  
Traffic Safety ◽  
High Speed ◽  
Traffic Accidents ◽  
Drunk Driving ◽  
Restraint System ◽  
Highway Traffic ◽  
Pressure Monitoring ◽  
Gas Generator ◽  
Tire Pressure ◽  
Safety Research

Tire blowout is a very serious security incident, particularly on the highway. As the existing anti-blowout device and measures also failed to meet the requirements to ensure traffic safety, research and development of prevention and treatment system is particularly important. In light of this, the Tire Pressure Monitoring Inflatable Restraint System is put forward. Sensor can send signals to the controller, and then the controller directs the gas generator to generate a lot of gas instantly, and through a special airway tire is inflated, so that the instability of the vehicle is eased. The concept of "vacuum tube tire" is first proposed, it can adapt to the inflation process better. Tire blowout, drunk driving and speeding is called together "three big killers on road" in China, so we can see that there are many incidents like these. Meanwhile, tire blowout is not like the other two which can be prevented by human’s means, it is sometimes not within our control. According to statistics, 70% of national highway traffic accidents are due to tire blowout, and a speed of more than 160km/h makes mortality possibility up to nearly 100%. In the check of the tires, more than 40% of them have security risks. [1] Statistics show that: The main reason why traffic accidents of high-speed driving keep increasing is leaked or inflated tires. In China, there is statistical data show that 46% traffic accidents on the highway were due to tire problem, in which tire blowout accounts for more than 70% of the total accidents, and the most crucial reasons of this is because the owners’ improper tire maintenance method. Beyond the boring concept, we can see a bunch of rather alarming figures, accounting for 49.81% highway accidents deaths, 63.94% injuries, 43.38% direct property loss were caused by high-speed tire blowout. High-speed tire blowout is considered to be the super-killer of traffic safety. And all the tire blowout incidents warn people to pay attention to tire safety.

scholarly journals Company employees as experimental participants in traffic safety research: Prevalence and implications

2019 ◽  
Vol 60 ◽  
pp. 81-92
Author(s):  
Igor Radun ◽  
Gustav Nilsonne ◽  
Jenni Radun ◽  
Gert Helgesson ◽  
Göran Kecklund
Keyword(s):  
Traffic Safety ◽  
Safety Research

Role of Exposure in Analysis of Road Accidents

2005 ◽  
Vol 1908 (1) ◽  
pp. 96-103 ◽  
Author(s):  
Filip Van den Bossche ◽  
Geert Wets ◽  
Tom Brijs
Keyword(s):  
Traffic Safety ◽  
Moving Average ◽  
Added Value ◽  
Autoregressive Moving Average ◽  
Road Accidents ◽  
Safety Research ◽  
Primary Determinant ◽  
Missing Variables ◽  
The Impact

Exposure is a key variable in traffic safety research. In the literature, it is noted as the first and primary determinant of traffic safety. In many cases, however, no valid exposure measure is available. In Belgium, monthly traffic counts for 12 years are available. This offers the opportunity to investigate the added value of exposure in models, next to legal, economic, and climatologic variables. Multiple regression with autoregressive moving average (ARMA) errors is used to quantify the impact of these factors on aggregated traffic safety. For each dependent variable, a model with and without exposure is constructed. The models show that exposure is significantly related to the number of accidents with persons killed and seriously injured and to the corresponding victims, but not to the lightly injured outcomes. Moreover, the addition or deletion of exposure does not influence the effects of the remaining variables in the model. The effects of exposure clearly depend on the type of measure used and on the time horizon considered. The framework of a regression model with ARMA errors allows for missing variables being accounted for by the error term. Even without a variable such as exposure, valid models can be constructed.

Driving task analysis as a tool in traffic safety research and practice

2007 ◽  
Vol 45 (9) ◽  
pp. 952-979 ◽  
Author(s):  
Wolfgang Fastenmeier ◽  
Herbert Gstalter
Keyword(s):  
Traffic Safety ◽  
Task Analysis ◽  
Research And Practice ◽  
Safety Research ◽  
Driving Task
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