Hoogendoom Serge  

Generic Driving Behavior Modeling by Differential Game Theory


In the last few decades, a number of driving models have been put forward based on the analogy with self-driven many particle systems. Examples of such models are the social-forces type models for car-following behavior, the Intelligent Driver Model, and the MOBIL model describing lane-changing behavior.
In this contribution, we put forward a new generic theory of driving behavior, based on the principle of least effort. In this theory, drivers are assumed to minimize the predicted effort of their control actions, including acceleration towards the free speed, car-following and lane changing. The derivation of the mathematical model is based on mathematical optimal control theory and differential game theory. Different models are put forward, e.g. considering drivers who may or may not anticipate the reactions of the other drivers. Furthermore, both non-cooperative and cooperative driving rules will be discussed. 

We present the main behavioral assumptions, the derivation of the mathematical model, and the resulting car-following and lane changing models. We also show the analogy and differences between the proposed model and other driving models, and discuss under which behavioral assumptions the proposed model reduces to well known driving models based on principles from physics (e.g. social forces). Finally, other model properties (such as the fundamental diagram and emergent lane distributions) will be presented.



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