TL;DR
This paper investigates a traffic flow model incorporating driver behavior fluctuations, revealing emergent traffic jams with self-similar patterns and analyzing how different fluctuations affect jam durations and flow efficiency.
Contribution
It introduces a traffic model with strong noise representing driver variability and studies the impact on jam formation and lifetime distributions.
Findings
Traffic jams exhibit self-similar structures near maximum throughput.
Reducing fluctuations at maximum speed lengthens jam lifetimes.
Outflow from jams self-organizes into maximum throughput state.
Abstract
We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations for driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from a traffic jam self-organizes into this state of maximum throughput.
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