Safety Assessment Of Vehicles Research Articles

Reliability-Based Vehicle Safety Assessment and Design Optimization of Roadway Radius and Speed Limit in Windy Environments

This paper presents a reliability-based analysis of road vehicle accidents and the optimization of roadway radius and speed limit design based on vehicle dynamics, mainly focusing on windy environments. The performance functions are formulated as failure modes of vehicle rollover and sideslip and are defined on a finite set of basic variables with probabilistic characteristics, so-called random variables. The random variables are vehicle speed, steer angle, tire–road friction coefficient, road bank angle, and wind speed. The probability of accident was evaluated using the first-order reliability method (FORM) and numerical studies were conducted using a single-unit truck model. The analysis demonstrates that wind is a significant factor when assessing vehicle safety on roads, and probabilistic studies such as reliability-based design optimization (RBDO) are necessarily required to enhance vehicle safety in windy environments. Accordingly, design optimization of roadway radius and speed limit was conducted, and new designs were proposed satisfying the target reliability. This study suggests that probabilistic mechanics and theory can be of value for analysis and design of wind-related vehicle safety.

Probabilistic Assessment of Vehicle Safety under Various Driving Conditions: A Reliability Approach

A probabilistic assessment model of vehicle safety under various driving conditions based on reliability method is developed. This model is built according to the advanced transient dynamic vehicle simulation models which can consider the coupling effects between vehicles and various driving conditions, such as wind gust, snow- covered or icy road surface and/or curving. By considering uncertainties of critical variables, the safety index is introduced to provide rational assessment of accident risks. In order to consider the complicated implicit limit state functions, the response surface method (RMS) is adopted to provide an efficient estimation of accident risks. Finally, the impacts of different critical variables on accident risks of a typical truck under several representative hazardous scenarios are investigated.

FIMCAR–Frontal Impact and Compatibility Assessment Research: How to Test Self and Partner Protection

For the assessment of vehicle safety in frontal collisions, the crash compatibility between the colliding vehicles is crucial. Compatibility compromises both the self protection and the partner protection properties of vehicles. Although compatibility has received worldwide attention for many years, no final assessment approach has been defined. Within the FIMCAR project, different frontal impact test procedures are analysed regarding their potential for future frontal impact legislation. The research activities focus on car-to-car frontal impact accidents based on accident investigations involving newer cars. Test procedures were developed with both a crash test programme and numerical simulations. The proposal from FIMCAR is to use a full width test procedure with deformable element and compatibility metrics in combination with the current ECE R94 off-set procedure as a frontal impact assessment approach which also addresses compatibility.

Reliability-based assessment of vehicle safety in adverse driving conditions

The framework of a reliability-based assessment model of vehicle safety under adverse driving conditions is developed. Such a framework is built based on the advanced transient dynamic vehicle simulation models which can consider the coupling effects between vehicles and adverse driving conditions, such as wind gust, snow-covered or icy road surface and/or curving. The single-vehicle safety index is introduced to provide rational assessment of accident risks by considering uncertainties of critical variables. In order to consider the complicated implicit limit state functions, the response surface method (RMS) is adopted to provide an efficient estimation of accident risks. Finally, a parametric study is conducted to demonstrate the methodology and the impacts of different critical variables on accident risks of a typical truck under several representative hazardous scenarios are investigated.