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Fuzzy Control Modeling and Simulation for Urban Traffic Lights at Single Intersection

TLDR
The fuzzy control model for urban traffic lights at single intersection is built from the perspective of cybernetics and has better control effect which reduces vehicle average delay at the single intersection.
Abstract
The fuzzy control model for urban traffic lights at single intersection is built from the perspective of cybernetics The modeling is designed by imitating the decision-making process of traffic policemen leading and unblocking traffic flow The specific control algorithm and fuzzy controller are introduced in detail afterward By using the Simulink tool in Matlab, the fuzzy control model is simulated and analyzed Comparing with the timed traffic lights control solution, the fuzzy control model has better control effect which reduces vehicle average delay at the single intersection

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Proceedings ArticleDOI

Efficient Collection of Connected Vehicle Data based on Compressive Sensing

TL;DR: In this article, a real-time compressive sensing (CS) approach is proposed to collect and compress data in real time and can recover the original data accurately and efficiently when it is necessary.
Posted Content

Efficient Collection of Connected Vehicle Data based on Compressive Sensing

Lei Lin
- 06 Jun 2018 - 
TL;DR: In this paper, a real-time compressive sensing (CS) approach is proposed to collect and compress data in real time and can recover the original data accurately and efficiently when it is necessary.
Posted Content

Capture and Recovery of Connected Vehicle Data: A Compressive Sensing Approach

TL;DR: A compressive sensing (CS) approach which allows CVs to capture and compress data in real-time and later recover the original data accurately and efficiently and can greatly improve the accuracy of travel time estimation when CVs are in traffic congestion.
Posted Content

An Agent-Based Simulation Model for Optimization of the Signalized Intersection Connected to Freeway On-Ramp

TL;DR: Three potential optimization solutions were proposed and tested with the help of VISSIM and according to the simulation results, solution (3) performs the best, resulting in the least vehicle delay time.
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