Modelling multi-anticipative driving strategies of human drivers
Martin Treiber
Institute for Economics and Traffic, TU Dresden, Andreas-Schubert-Str. 23, D-01062 Dresden, Germany
We generalize a wide class of time-continuous microscopic traffic models
to include essential
aspects of traffic dynamics not captured by these models,
but relevant for human drivers. Specifically, we consider
(i) finite reaction times and limited attention, (ii) errors
in estimating the input variables, (iii) looking several vehicles ahead
(spatial anticipation), (iv) temporal anticipation, and
(v) long-term adaptation to the global traffic situation.
The estimation errors are modelled as stochastic Wiener
processes and lead to time-correlated fluctuations of the acceleration.
By means of simulations based on the intelligent-driver model
we show that the destabilizing effects of
reaction times, limited attention, and estimation errors can be
compensated for by spatial and temporal ''multi-anticipation''.
Particularly, the anticipation mechanisms allow accident-free smooth
driving in complex traffic situations
even if reaction times exceed typical time
headways. Clearly, the reaction time
and the time headway are different and independent quantities both
required to describe realistic driving behaviour.
The effects of multi-anticipation increase both
spatial and temporal scales of stop-and-go
waves and smoothes the transition zones between free and
congested traffic states, in agreement with real traffic data.
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