Empirical Research and Modeling of Longitudinal Driving Behavior Under Adverse Conditions

Empirical Research and Modeling of Longitudinal Driving Behavior Under Adverse Conditions

Hoogendoorn, R.G.

Brookhuis, K.A. (promotor)

Civil Engineering and Geosciences

Transport & Planning

2012-07-05

Adverse conditions (emergency situations, adverse weather conditions, freeway incidents) have been shown to have a substantial impact on traffic flow operations. It is however unclear to what extent the conditions impact longitudinal driving behavior and what the determinants of these changes in driving behavior are. Furthermore, it is not yet clear how these changes in driving behavior can best be modeled. To this end we performed three extensive driving simulator experiments intended to investigate the influence of emergency situations, adverse weather conditions and freeway incidents on empirical longitudinal driving behavior as well as driver workload. Furthermore we determined the influence of these conditions on parameter values and model performance of an often used car-following model, i.e., the Intelligent Driver Model (Treiber et al., 2000). We also determined changes in the position of so-called action points in a psycho-spacing model and took some first steps towards the development of a new stochastic car following model based on a Bayesian network modeling approach.

adverse conditions

http://resolver.tudelft.nl/uuid:1e0117ef-d0db-4d00-bce6-203d75a30ddc

TRAIL Thesis Series

9789055841585

Institutional Repository

doctoral thesis

(c) 2012 Hoogendoorn, R.G.