Investigating mandatory and non-mandatory trip patterns based on socioeconomic characteristics and traffic analysis zone features using deep neural networks

Investigating mandatory and non-mandatory trip patterns based on socioeconomic characteristics and traffic analysis zone features using deep neural networks

Abstract Forecasting travel demand is a classic problem in transportation planning. The models made for this purpose take the socioeconomic characteristics of a subset of a population to estimate the total demand, mainly using random utility models. However, with machine learning algorithms fast bec...

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Bibliographic Details
Main Authors: Hamid Mirzahossein, Ali Bakhtiari, Navid Kalantari, Xia Jin
Format: Article
Language:English
Published: Springer 2022-09-01
Series:Computational Urban Science
Subjects:
Deep learning
Trip pattern prediction
Socioeconomic characteristics
Neural network
Mandatory patterns
Non-mandatory patterns
Online Access:https://doi.org/10.1007/s43762-022-00063-w

Internet

https://doi.org/10.1007/s43762-022-00063-w

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