Model-based explorative analysis of a queue-tail warning driver support system with inter-vehicle communication

摘要

We present an explorative analysis of an Advanced Driver Assistance system designed to warn drivers when approaching sharp decelerations in a queue tail. We give a review of different traffic flow models that can be used for the analysis. We select kinetic traffic flow models for the analysis amongst other because of their capability of reproducing different congestion patterns. We present a variant of kinetic traffic flow models called human-kinetic model, because it is strongly based on individual driver behaviour, i.e. on fully continuous acceleration/deceleration behaviour and explicit modelling of the activation level of the driver. A design for the ADA system is given and the system was applied to a reference situation with a queue. The explorative analysis shows that the system results in safer and smoother transition from free flowing to congested traffic. It also avoids compression of the queue-tail, thus preventing stop-and-go congestion patterns.