DEEPTRAVEL: A neural network based travel time estimation model with auxiliary supervision

DEEPTRAVEL: A neural network based travel time estimation model with auxiliary supervision

Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment or designed heuristically in a non-learning-based way. The former is not able to capture many cross-segment complex factors while...

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Bibliographic Details
Main Authors: ZHANG, Hanyuan, WU, Hao, SUN, Weiwei, ZHENG, Baihua
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Complex factors
Real data sets
Road segments
Supervision models
Trajectory data
Trajectory points
Travel time estimation
Urban mobility
Travel time
Databases and Information Systems
Numerical Analysis and Scientific Computing
Transportation
Online Access:https://ink.library.smu.edu.sg/sis_research/4107
https://ink.library.smu.edu.sg/context/sis_research/article/5110/viewcontent/DeepTravel.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/4107
https://ink.library.smu.edu.sg/context/sis_research/article/5110/viewcontent/DeepTravel.pdf

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