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Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki

Abstract

In order to study driver steering control behavior for vehicle, a driver model for single-lane change maneuver is constructed by a neural network system concerned with the man-machine-environment system. And, using sensitivity analysis, it is found that the model represent the driver control behavior, and the relation between the driver control behavior and vehicle responses. The sensitivity analysis is also examined by applying to the 2nd order predictive driver model. The validity of the sensitivity analysis is confirmed. 5 refs., 8 figs.
Authors:
Yang, Z; Okayama, T; Katayama, T; [1]  Kageyama, I [2] 
  1. Japan Automobile Research Institute Inc., Tsukuba (Japan)
  2. Nihon University, Tokyo (Japan)
Publication Date:
Oct 01, 1997
Product Type:
Conference
Report Number:
ETDE/JP-98753752; CONF-9710216-
Reference Number:
SCA: 320203; 570000; 550100; 551000; PA: JP-98:0G1241; EDB-98:073732; SN: 98001948905
Resource Relation:
Conference: 1997 Fall Japan Society of Automotive Engineers (JSAE) meeting science lecture, JSAE 1997 nen shuki taikai gakujutsu koenkai, Hiroshima (Japan), 21-23 Oct 1997; Other Information: PBD: 1 Oct 1997; Related Information: Is Part Of Preprint of the Fall 1997 JSAE (Japan Society of Automotive Engineers) Meeting Science Lecture. No. 975; PB: 312 p.; Jidosha gijutsukai 1997 nen shuki taikai gakujutsu koenkai maezurishu. 975
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 57 HEALTH AND SAFETY; 55 BIOLOGY AND MEDICINE, BASIC STUDIES; AUTOMOBILES; ROUTING; MOTOR VEHICLE OPERATORS; INTERCHANGEABILITY; HUMAN FACTORS; BEHAVIOR; NEURAL NETWORKS; NUMERICAL ANALYSIS; KNOWLEDGE BASE; OPERATION; CONTROL; MAN-MACHINE SYSTEMS; MATHEMATICAL MODELS; SENSITIVITY ANALYSIS; VALIDATION
OSTI ID:
625119
Research Organizations:
Society of Automotive Engineers of Japan, Tokyo (Japan)
Country of Origin:
Japan
Language:
Japanese
Other Identifying Numbers:
Other: ON: DE98753752; TRN: JN98G1241
Availability:
Available from Society of Automotive Engineers of Japan Inc., Gobancho 10-2, Chiyoda-ku, Tokyo, (Japan); OSTI as DE98753752
Submitting Site:
NEDO
Size:
pp. 193-196
Announcement Date:

Citation Formats

Yang, Z, Okayama, T, Katayama, T, and Kageyama, I. Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki. Japan: N. p., 1997. Web.
Yang, Z, Okayama, T, Katayama, T, & Kageyama, I. Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki. Japan.
Yang, Z, Okayama, T, Katayama, T, and Kageyama, I. 1997. "Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki." Japan.
@misc{etde_625119,
title = {Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki}
author = {Yang, Z, Okayama, T, Katayama, T, and Kageyama, I}
abstractNote = {In order to study driver steering control behavior for vehicle, a driver model for single-lane change maneuver is constructed by a neural network system concerned with the man-machine-environment system. And, using sensitivity analysis, it is found that the model represent the driver control behavior, and the relation between the driver control behavior and vehicle responses. The sensitivity analysis is also examined by applying to the 2nd order predictive driver model. The validity of the sensitivity analysis is confirmed. 5 refs., 8 figs.}
place = {Japan}
year = {1997}
month = {Oct}
}