A fuzzy neural approach for vehicle guidance in real-time
Authored by Bo Mi, Dongyan Liu
Date Published: 2017
DOI: 10.1080/10798587.2015.1118274
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Abstract
In recent years, neural network has allured much attention of
transportation studies due to its competence of addressing traffic
complexity. However, design and implementation of such system remains
intractable in terms of its opaqueness. Instead, adopting a
knowledge-based approach, which can automatically generate a set of
expert rules to model the problems, could be a possible solution. To
this extent, we devised a fuzzy neural network strategy to optimize the
route decision on urban roads in this paper. Our scheme works on an
evolutionarily weighted network model, whose resource requirements are
adequately alleviated. We also introduced a GA (Genetic Algorithm)-based
learning algorithm to obtain the weights of fuzzy system and validated
its performance by agent-based modeling.
Tags
Congestion
Genetic algorithm
decision-support
traffic
System
Vehicle routing guidance
Fuzzy neural network
Traffic control