Developing an Artificial Neural Network for Modeling Heavy Vehicle Rollover

2000-01-3418

12/04/2000

Event
International Truck & Bus Meeting & Exposition
Authors Abstract
Content
A backpropagation through time algorithm was used to model and predict the rollover of a tank truck carrying varying liquid volumes, traveling at various speeds, and performing a number of steering maneuvers of up to 12 seconds duration. The training and testing data sets were built with data produced by simulations using first principle models. Because neural networks have trouble predicting behaviors beyond the boundaries of their training sets, the training set was weighted with 5 per cent of the input examples involving vehicle rollover due to sloshing. The network outputs under test data sets produced very strong correlations with first principle roll simulations in both rollover and non-extreme steering maneuvers.
Meta TagsDetails
DOI
https://doi.org/10.4271/2000-01-3418
Pages
13
Citation
Woerner, D., Ranganathan, R., and Butler, A., "Developing an Artificial Neural Network for Modeling Heavy Vehicle Rollover," SAE Technical Paper 2000-01-3418, 2000, https://doi.org/10.4271/2000-01-3418.
Additional Details
Publisher
Published
Dec 4, 2000
Product Code
2000-01-3418
Content Type
Technical Paper
Language
English