Activity-based models of travel demand: promises, progress and prospects

S Rasouli, H Timmermans - International Journal of Urban …, 2014 - Taylor & Francis
Because two decades have almost passed since the introduction of activity-based models of
travel demand, this seems the right time to evaluate progress made in the development and …

Urban activity pattern classification using topic models from online geo-location data

S Hasan, SV Ukkusuri - Transportation Research Part C: Emerging …, 2014 - Elsevier
Location-based check-in services in various social media applications have enabled
individuals to share their activity-related choices providing a new source of human activity …

Daily activity pattern recognition by using support vector machines with multiple classes

M Allahviranloo, W Recker - Transportation Research Part B …, 2013 - Elsevier
The focus of this paper is to learn the daily activity engagement patterns of travelers using
Support Vector Machines (SVMs), a modeling approach that is widely used in Artificial …

Similarity analysis of frequent sequential activity pattern mining

Z Shou, X Di - Transportation Research Part C: Emerging …, 2018 - Elsevier
Activity pattern classification is extensively studied using multi-person single-day mobile
traces. However, human mobility exhibits intra-personal variability and thus single-day …

Building a validation measure for activity-based transportation models based on mobile phone data

F Liu, D Janssens, JX Cui, YP Wang, G Wets… - Expert Systems with …, 2014 - Elsevier
Activity-based micro-simulation transportation models typically predict 24-h activity-travel
sequences for each individual in a study area. These sequences serve as a key input for …

Characterizing activity sequences using profile Hidden Markov Models

F Liu, D Janssens, JX Cui, G Wets, M Cools - Expert Systems with …, 2015 - Elsevier
In literature, activity sequences, generated from activity-travel diaries, have been analyzed
and classified into clusters based on the composition and ordering of the activities using …

Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes

U Ahmed, AT Moreno, R Moeckel - Transportation, 2021 - Springer
Activity sequencing is a crucial component of disaggregate modeling approaches. This
paper presents a methodology to analyse and predict activity sequence patterns for persons …

Decoding Urban Mobility: Application of Natural Language Processing and Machine Learning to Activity Pattern Recognition, Prediction, and Temporal Transferability …

M Chen, Q Yuan, C Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Activity patterns provide valuable insights into activity-based travel demand modeling and
understanding human mobility. However, challenges often arise in accurately recognizing …

A complex network methodology for travel demand model evaluation and validation

M Saberi, TH Rashidi, M Ghasri, K Ewe - Networks and Spatial Economics, 2018 - Springer
Travel demand can be viewed as a weighted and directed graph where nodes are the
origins and destinations and links represent the trips between nodes. This paper presents a …

Discrepancy Analysis of Activity Sequences: What Explains the Complexity of People's Daily Activity–Travel Patterns?

K Kim - Transportation Research Record, 2014 - journals.sagepub.com
Sequence alignment, also known as optimal matching, has recently received new attention
for use in analysis of activity patterns. The method is almost always combined with a data …