This paper presents the approach and methodology of the Large Truck Crash Causation Study (LTCCS), undertaken jointly by the Federal Motor Carrier Safety Administration and the National Highway Traffic Safety Administration. The LTCCS is a study of a nationally-representative sample of serious and fatal heavy truck crashes occurring between 2001 and 2003. The data collected provides a detailed ...

Research was undertaken to determine vehicle size parameters influencing driver fatality odds, independent of mass, in two-vehicle collisions. Forty vehicle parameters were evaluated for 1,500 vehicle groupings. Logistic regression analyses show driver factors (belt use, age, drinking) collectively contribute more to fatality odds than vehicle factors, and that mass is the most important vehicu...

Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal r...

Digital human figure models are a useful tool for simulation of driver ingress and egress for passenger cars, light trucks, and heavy commercial trucks. Simulation allows evaluation of the suitability of steps and handholds as a system. Accurate simulation requires detailed, validated algorithms to predict driver motions. One critical component of such an algorithm is the accurate prediction of...

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two mach...

The complexity of human behaviors makes their modeling very difficult. To build a model that reproduce many concurrent aspects of those behaviors, we propose to use a testdriven like methodology. To validate this methodology, we reuse a car driver model and build a truck driver model by considering relevant aspects. We analyze, test and verify the model by using the hysteresis phenomena appeari...