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2023-01-16T04:31:49Z
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Stochastic modeling of vehicle trajectory during lane-changing
Nishiwaki, Yoshihiro
Miyajima, Chiyomi
Kitaoka, Hidenori
Takeda, Kazuya
open access
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Driving Behavior
Dynamic System
Sampling
hidden Markov model
A signal processing approach for modeling vehicle trajectory during lane changing driving is discussed. Because individual driving habits are not a deterministic process, we developed a stochastic method. The proposed model consists of two parts: a dynamic system represented by a hidden Markov model and a cognitive distance space derived from the range distance distribution. The first part models the local dynamics of vehicular movements and generates a set of probable trajectories. The second part selects an optimal trajectory by stochastically evaluating the distances from surrounding vehicles. From experimental evaluation, we show that the model can predict the vehicle trajectory at given traffic conditions with 17.6 m prediction error for two different drivers.
IEEE
2009-04-19
eng
journal article
VoR
http://hdl.handle.net/2237/13898
https://nagoya.repo.nii.ac.jp/records/12022
https://doi.org/10.1109/ICASSP.2009.4959849
1520-6149
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009)
1377
1380
https://nagoya.repo.nii.ac.jp/record/12022/files/Nishiwaki_ICASSP2009-04.pdf
application/pdf
688.6 kB
2018-02-20