Abstract
Driving is a tracking task with preview as has been recognized since the 60s. Subsequent research to model human curve negotiation divides into two camps. One in which a limited number of points in the future (generally one or two) are used to guide lane keeping control on straight and curved roads and another that uses optimal preview control (OPC) to characterize human control behavior. The former is too simplistic as it cannot accurately handle curve entry and exit with a single preview and gain setting (i.e. non situation adaptive) and the latter is arguably too computationally intense for a human to adopt (but not unreasonable to converge to over time). This paper shows theoretically that by selecting two preview points strategically related to vehicle dynamics for near preview point and striking a balance between curve cutting on entry, curve overshoot on exit, and smooth control throughout for the far preview point, two-point-controllers approach the performance of a full optimal preview controller. The difference between the reference full OPC and two-point-controllers lies mainly in the fact that the three phases of curve negotiation (entry, within, and exit) require different previews and gains which only the OPC is capable of.
Original language | English |
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Title of host publication | IFAC-PapersOnLine |
Subtitle of host publication | 13th IFAC Symposium on Analysis, Design, and Evaluation ofHuman-Machine Systems HMS 2016 |
Editors | T. Sawaragi |
Publisher | Elsevier |
Pages | 102-107 |
Volume | 49 - 19 |
DOIs | |
Publication status | Published - 2016 |
Event | 13th IFAC Symposium on Analysis, Design, and Evaluation of Human-Machine Systems - Kyoto, Japan Duration: 30 Aug 2016 → 2 Sept 2016 |
Conference
Conference | 13th IFAC Symposium on Analysis, Design, and Evaluation of Human-Machine Systems |
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Abbreviated title | HMS 2016 |
Country/Territory | Japan |
City | Kyoto |
Period | 30/08/16 → 2/09/16 |
Keywords
- cybernetics
- driver model
- human performance
- Manual control
- Optimal preview control