[HTML][HTML] Choice modelling in the age of machine learning-discussion paper
Since its inception, the choice modelling field has been dominated by theory-driven
modelling approaches. Machine learning offers an alternative data-driven approach for …
modelling approaches. Machine learning offers an alternative data-driven approach for …
A dynamic choice model to estimate the user cost of crowding with large-scale transit data
Efficient mass transit provision should be responsive to the behaviour of passengers.
Operators often conduct surveys to elicit passenger perspectives, but these can be …
Operators often conduct surveys to elicit passenger perspectives, but these can be …
Differential impacts of autonomous and connected-autonomous vehicles on household residential location
High market penetration of autonomous vehicles (AVs) and connected-autonomous vehicles
(CAVs) is expected to impact transportation network performance, which is an important …
(CAVs) is expected to impact transportation network performance, which is an important …
[PDF][PDF] Choice modelling in the age of machine learning
Since its inception, the choice modelling field has been dominated by theory-driven models.
The recent emergence and growing popularity of machine learning models offer an …
The recent emergence and growing popularity of machine learning models offer an …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
[HTML][HTML] Distribution-free estimation of individual parameter logit (IPL) models using combined evolutionary and optimization algorithms
J Swait - Journal of choice modelling, 2023 - Elsevier
When estimating random coefficients models from choice data, decisions relating to the
multivariate density function assumed to describe preference heterogeneity across the …
multivariate density function assumed to describe preference heterogeneity across the …
A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data
The emergence of data-driven demand analysis has led to the increased use of generative
modelling to learn the probabilistic dependencies between random variables. Although their …
modelling to learn the probabilistic dependencies between random variables. Although their …
Discrete choice analysis with machine learning capabilities
This paper discusses capabilities that are essential to models applied in policy analysis
settings and the limitations of direct applications of off-the-shelf machine learning …
settings and the limitations of direct applications of off-the-shelf machine learning …
A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
JÁ Martín-Baos, JA López-Gómez… - … research part C …, 2023 - Elsevier
The emergence of a variety of Machine Learning (ML) approaches for travel mode choice
prediction poses an interesting question to transport modellers: which models should be …
prediction poses an interesting question to transport modellers: which models should be …
Visual hazardous models: a hybrid approach to investigate road hazardous events
H Rangam, SK Sivasankaran… - Accident Analysis & …, 2024 - Elsevier
Road users (drivers, passengers, pedestrians, and Animals) are exposed to hazardous
events during their commute. With 23% of global fatalities among pedestrians, their safety …
events during their commute. With 23% of global fatalities among pedestrians, their safety …