Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions-Reference-Cited by-同舟云学术

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Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions

Published:2023-06 Issue: Volume:172 Page:134-173
ISSN:0191-2615
Container-title:Transportation Research Part B: Methodological
language:en
Short-container-title:Transportation Research Part B: Methodological

Author:

Kim Sung Hoo^ORCID,Mokhtarian Patricia L.^ORCID

Funder

U.S. Department of Transportation

US Department of Transportation UTC Program

Hanyang University

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Transportation,Civil and Structural Engineering

Reference280 articles.

1. Why is electric vehicle uptake low in Atlantic Canada? A comparison to leading adoption provinces;Abotalebi;J. Transp. Geogr.,2019

2. Effects of human-centered factors on crash injury severities;Adanu;J. Adv. Transp.,2017

3. Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities;Adanu;Accid. Anal. Prev.,2018

4. Quantifying the employment accessibility benefits of shared automated vehicle mobility services: consumer welfare approach using logsums;Ahmed;Transp. Res. Part A Policy Pract.,2020

5. Frequent versus occasional drivers: a hybrid route choice model;Alizadeh;Transp. Res. Part F Traff. Psychol. Behav.,2019

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1. The role of human errors and violations in pedestrian-related crashes: Harnessing a unique database and accounting for heterogeneity;Journal of Safety Research;2024-12

2. Investigating vehicle-vehicle and vehicle–pedestrian crash severity at street intersections with the latent class parameterized correlation bivariate generalized ordered probit;Accident Analysis & Prevention;2024-11

3. Preference heterogeneity analysis on train choice behaviour of high-speed railway passengers: A case study in China;Transportation Research Part A: Policy and Practice;2024-10

4. Kampala land passengers transportation planning: Examining consumer behavior through a bottom-up lens;Case Studies on Transport Policy;2024-09

5. Predicting Damages to Remainder Parcels in Right-of-Way Acquisitions for Expanding Transportation Infrastructure: Using a Truncated Finite-Mixture Model;Journal of Infrastructure Systems;2024-09

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