An Anticipatory Dynamic Bayesian Network Approach towards an Autonomous Vehicle Safety Reasoning System

被引:0
作者
Frederick, Philip A. [1 ]
Cheok, KaC [2 ]
Del Rose, Mike [1 ]
Kania, Robert [1 ]
机构
[1] US Army DEVCOM Ground Vehicle Syst Ctr GVSC, 6501 East Eleven Mile Rd, Warren, MI 48397 USA
[2] Sch Engn & Comp Sci, Engn Ctr, Room 301115 Lib Dr, Rochester, MI 48309 USA
来源
UNMANNED SYSTEMS TECHNOLOGY XXIV | 2022年 / 12124卷
关键词
Autonomous Vehicles; Artificial Intelligence; Robotic Safety; Automated Temporal Reasoning;
D O I
10.1117/12.2616780
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Despite numerous investments toward autonomous vehicle technology this past decade the ensured safe operation of these systems is still an unresolved issue for both commercial and defense systems due to decision uncertainty. In complex dynamic domains (e.g. intersections or congested terrain) the expected mode of operation for ensured safety of these unmanned systems is still direct human control (whether through direct vehicle input or through teleoperation). This paper presents research toward an autonomous vehicle safety reasoning system that provides a novel approach to temporally address scene uncertainty to increase the safety envelope for commercial and defense systems.
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页数:22
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