Next Article in Journal
Fully-Unsupervised Embeddings-Based Hypernym Discovery
Previous Article in Journal
Gear Fault Diagnosis through Vibration and Acoustic Signal Combination Based on Convolutional Neural Network
Open AccessArticle

Reliable Estimation of Urban Link Travel Time Using Multi-Sensor Data Fusion

by Yajuan Guo 1,2 and Licai Yang 1,*
1
School of Control Science and Engineering, Shandong University, Jinan 250061, China
2
School of Traffic and Logistics Engineering, Shandong Jiaotong University, Jinan 250357, China
*
Author to whom correspondence should be addressed.
Information 2020, 11(5), 267; https://doi.org/10.3390/info11050267
Received: 10 March 2020 / Revised: 23 April 2020 / Accepted: 14 May 2020 / Published: 16 May 2020
(This article belongs to the Section Information Processes)
Travel time is one of the most critical indexes to describe urban traffic operating states. How to obtain accurate and robust travel time estimates, so as to facilitate to make traffic control decision-making for administrators and trip-planning for travelers, is an urgent issue of wide concern. This paper proposes a reliable estimation method of urban link travel time using multi-sensor data fusion. Utilizing the characteristic analysis of each individual traffic sensor data, we first extract link travel time from license plate recognition data, geomagnetic detector data and floating car data, respectively, and find that their distribution patterns are similar and follow logarithmic normal distribution. Then, a support degree algorithm based on similarity function and a credibility algorithm based on membership function are developed, aiming to overcome the conflicts among multi-sensor traffic data and the uncertainties of single-sensor traffic data. The reliable fusion weights for each type of traffic sensor data are further determined by integrating the corresponding support degree with credibility. A case study was conducted using real-world data from a link of Jingshi Road in Jinan, China and demonstrated that the proposed method can effectively improve the accuracy and reliability of link travel time estimations in urban road systems. View Full-Text
Keywords: multi-sensor traffic data fusion; urban link travel time; reliable estimation; support degree; credibility multi-sensor traffic data fusion; urban link travel time; reliable estimation; support degree; credibility
Show Figures

Figure 1

MDPI and ACS Style

Guo, Y.; Yang, L. Reliable Estimation of Urban Link Travel Time Using Multi-Sensor Data Fusion. Information 2020, 11, 267.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop