Automatic driving technology using artificial Intelligence

被引:0
|
作者
Lei, Li [1 ]
机构
[1] Chongqing Ind Polytech Coll, Dept Vehicle Engn, Chongqing 401120, Peoples R China
来源
AGRO FOOD INDUSTRY HI-TECH | 2017年 / 28卷 / 01期
关键词
Unmanned ground vehicles; autopilot system; intelligent control; UNMANNED GROUND VEHICLES; SYSTEMS;
D O I
暂无
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Unmanned ground vehicles are an important force in the future of the military that realizes unmanned and information warfare. Different types of equipment, such as nuclear, biological, and explosive, can replace humans in complex battlefield environments. With the rise of information warfare, modern warfare will be more damaging and easily lead to personnel casualties. Reducing such damage without lessening equipment and supplies handling, medical evacuation, military reconnaissance surveillance, mine detection, and joint combat tasks is crucial. Under military requirement, unmanned ground vehicles shows military potential and combative effectiveness when executing the most dangerous military missions, thereby representing an important direction in military equipment development. Unmanned vehicles will also play a role in the success of future wars and battlefield initiatives. The unmanned ground vehicle is complex and a nonlinear time-varying system, which is difficult to describe with an accurate mathematical model. The model of traditional control is also struggles to satisfy the design index of the system. However, based on the traditional control theory, artificial intelligence can solve the control problem. A vehicle-automated driving system is responsible for the real-time and accurate motion control action of an unmanned ground vehicle. The performance of such a driving system is key to the vehicle's intelligence in environmental awareness, path planning, and decision-making ability. With the technology's development, the future of vehicle automated driving system should be more capable of adapting to environments and autonomous driving.
引用
收藏
页码:570 / 574
页数:5
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