A Driver Lateral and Longitudinal Control Model Based on Queuing Network Cognitive Architecture

被引：1

作者：

Bi, Luzheng ^{[1
]}

Wang, Cuie ^{[1
]}

Yang, Xuerui ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China

来源：

2013 FOURTH GLOBAL CONGRESS ON INTELLIGENT SYSTEMS (GCIS) | 2013年

关键词：

Car-following; Driver lateral control; Queuing Network;

D O I：

10.1109/GCIS.2013.50

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a new computational model of driver car-following control with lateral control based on the Queuing Network (QN) cognitive architecture. A driver car-following model within the framework of the QN cognitive architecture is first developed based on the time headway and then integrated with a QN-based driver lateral control model previously validated. The comparison between human driver data and the integrated model simulation data suggests that this computational model can perform car-following control with lateral control well, and its performance is in agreement with that of drivers under straight and curved roads. This proposed model can compute and simulate car-following behavior and thus has the potential to help develop driver assistance systems for the car-following scenario.

引用

页码：274 / 278

页数：5

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