An exploration of calibrating activity-based mobility demand of travelers with bounded rationality

Example of ATP representation.Credit: Communications in Transportation Research, Tsinghua University Press

Parameter tuning of transportation allocation models is essential for travel demand analysis and management. As an extension of traditional traffic allocation, Bounded-Rational Activity-Travel Allocation (BR-ATA) endogenously combines activity-based modeling and traffic allocation to provide high-dimensional selection between high-dimensional selection facets along activity-travel patterns. interdependencies can be captured.

The inclusion of multiple episodes of activity participation and restricted rationality behavior expands the selection space and poses challenges for tuning the BR-ATA model. To date, no formulations and solution approaches have been developed for parameter calibration of BR-ATA. To solve this problem, Dong Wang and Feixiong Liao formulated his BR-ATA calibration as an optimization problem and solved it using the simultaneous perturbation stochastic approximation method.

They published their study on January 20, 2023. Communication in transport research.

“We formulate the BR-ATA calibration as an optimization problem, thanks to the multistate supernetwork, and analyze the influence of two additional components on the calibration problem. We also propose a formulation for the ATA calibration problem.To solve the proposed calibration problem, a simultaneous perturbation stochastic approximation algorithm is employed.To calibrate the illustrated activity-based travel demand, the numerical An example is presented: a group at Eindhoven University of Technology (Netherlands).

BR parameters and activity participation influence calibration

The execution time will be within the range of [0.30, 0.40] Time at which the BR parameter takes different values. Note that ATA calibration issues can take over 2 hours to reach a dead state. Regarding the effect of the number of activities, the execution time decreases as the number of activities increases.

“The execution time in which the BR-related parameters fall within [0.05, 0.2] Relatively stable and shorter than for smaller parameters (i.e. 0.01 or ATA calibration issues). Also, low activity always links flows concentrated in a specific period of time. Link congestion brings more ATP to balance the OD demand,” explains Dong Wang, associate professor at Qingdao University (China).

Extending Temporal and Spatial Dimensions to the BR-ATA Calibration Problem

SPSA takes 8.2 hours to reach the stopping condition for the BR-ATA calibration problem of the Sioux Falls network, and the calibrated demand approximates the prior value. Taking the location of a house as an example, the study shows that the relative error in adjusted demand is 0.01.

For the BR-DATA calibration problem of the Sioux Falls network, the run time is 0.92 hours and the number of iterations is 647. All calibrated demands are close to the prior value. To further illustrate the scalability on large networks, calibration of the BR-DATA model was performed on the Eastern Massachusetts network. SPSA takes over 10 hours to complete 1000 iterations and the corresponding RMSN (measured error) is as low as 0.06.

“This result shows that the SPSA algorithm is viable for BR-ATA and BR-DATA calibration problems in large networks,” said Feixiong Liao. “However, large-scale real-world applications require more effective algorithms,” he adds.

For more information:
Dong Wang et al. Formulations and solutions for coordinating bounded rational activity and travel allocations: an exploratory study, Communication in transport research (2023). DOI: 10.1016/j.commtr.2023.100092

Provided by Tsinghua University Press

Quote: A study on activity-based travel demand adjustment for travelers with limited rationality (20 January 2023), available on 20 January 2023 at -exploration-calibrating-activity-based-mobility- taken from demand.html

This document is subject to copyright. No part may be reproduced without written permission, except in fair trade for personal research or research purposes. Content is provided for informational purposes only.

Leave a Reply

Your email address will not be published. Required fields are marked *