Summary
International Symposium on Nonlinear Theory and Its Applications
2022
Session Number:A2L-D
Session:
Number:A2L-D-01
Predicting Traffic Breakdown in Expressways Using Linear Combination of Vehicle Detector Data
Rikuto Shigemi , Hiroyasu Ando , Kentaro Wada , Risa Mukai,
pp.21-24
Publication Date:12/12/2022
Online ISSN:2188-5079
Summary:
Traffic congestion brings about a variety of social issues to be solved urgently. In this study, we examine a precision of traffic prediction with a simple linear model. Instead of improving the complex models, we appropriately select training data with a linear model, and verify the feasibility of prediction by exploring ”data complexity”.