Measuring and visualizing space–time congestion patterns in an urban road network using large-scale smartphone-collected GPS data-Reference-Cited by-同舟云学术

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Measuring and visualizing space–time congestion patterns in an urban road network using large-scale smartphone-collected GPS data

Published:2017-09-13 Issue:7 Volume:11 Page:391-401
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Stipancic Joshua¹,Miranda-Moreno Luis¹,Labbe Aurélie²,Saunier Nicolas³^ORCID

Affiliation:

1. Department of Civil Engineering and Applied Mechanics, McGill University, Montreal, Canada

2. Department of Decision Sciences, HEC Montréal, Montreal, Canada

3. Department of Civil, Geological and Mining Engineering, Polytechnique Montréal, Montreal, Canada

Publisher

Informa UK Limited

Subject

Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2017.1374022

Reference28 articles.

1. Bachman, Christian. 2011. “Multi-sensor Data Fusion for Traffic Speed and Travel.” Masters thesis, University of Toronto, Toronto.

2. Determining the Number of Probe Vehicles for Freeway Travel Time Estimation by Microscopic Simulation

3. Estimating travel times and vehicle trajectories on freeways using dual loop detectors

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2. Exploring Spatiotemporal Patterns of Frequently Congested Urban Road Segments Based on Multi-Source Data: A Case Study of China’s Super-Large Cities;Transportation Research Record: Journal of the Transportation Research Board;2024-06-18

3. Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods;Mathematics;2024-04-20

4. Investigating the Effects of Variable Speed Limit Strategies on Driving Behavior and Traffic Safety;2024

5. Traffic Congestion Prediction Using Feature Series LSTM Neural Network and a New Congestion Index;International Journal on Artificial Intelligence Tools;2023-09-21

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