A Multi-Sensor Data Fusion Approach for Real-Time Lane-Based Traffic Estimation

A Multi-Sensor Data Fusion Approach for Real-Time Lane-Based Traffic Estimation

abstract: Modern intelligent transportation systems (ITS) make driving more efficient, easier, and safer. Knowledge of real-time traffic conditions is a critical input for operating ITS. Real-time freeway traffic state estimation approaches have been used to quantify traffic conditions given limited...

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Bibliographic Details
Other Authors: Zhou, Zhuoyang (Author)
Format: Doctoral Thesis
Language:English
Published: 2015
Subjects:
Industrial engineering
Civil engineering
Engineering
Data Driven Algorithm
Lane Based
Multi-Sensor Data Fusion
Multi-Sensor Extended Kalman Filter
Traffic Flow Model
Traffic State Estimation
Online Access:http://hdl.handle.net/2286/R.I.29941

Internet

http://hdl.handle.net/2286/R.I.29941

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