Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model

12/17/2011
by   Bartlomiej Placzek, et al.
0

In this paper a method is proposed for performance evaluation of road traffic control systems. The method is designed to be implemented in an on-line simulation environment, which enables optimisation of adaptive traffic control strategies. Performance measures are computed using a fuzzy cellular traffic model, formulated as a hybrid system combining cellular automata and fuzzy calculus. Experimental results show that the introduced method allows the performance to be evaluated using imprecise traffic measurements. Moreover, the fuzzy definitions of performance measures are convenient for uncertainty determination in traffic control decisions.

READ FULL TEXT
research
04/12/2020

Traffic light control based on fuzzy Q-leaming

Traffic is an issue that many big cities are confronted with because of ...
research
02/18/2021

On Typical Hesitant Fuzzy Languages and Automata

The idea of nondeterministic typical hesitant fuzzy automata is a genera...
research
04/23/2019

Fuzzy Q-Learning Based Multi-Agent System for Intelligent Traffic Control by a Game Theory Approach

This paper introduces a multi-agent approach to adjust traffic lights ba...
research
06/04/2014

A self-organizing system for urban traffic control based on predictive interval microscopic model

This paper introduces a self-organizing traffic signal system for an urb...
research
12/17/2011

Vehicles Recognition Using Fuzzy Descriptors of Image Segments

In this paper a vision-based vehicles recognition method is presented. P...
research
07/10/2009

Modeling self-organizing traffic lights with elementary cellular automata

There have been several highway traffic models proposed based on cellula...
research
04/30/2019

A Performance Evaluation Tool for Drone Communications in 4G Cellular Networks

We introduce a measurement tool for performance evaluation of wireless c...

Please sign up or login with your details

Forgot password? Click here to reset