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Trust In Unmanned Driving System

Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, 2015
This study proposes a between-subject experiment with four conditions representing different levels of anthropomorphism and automation embedded in unmanned driving systems. Participants will be exposed to either a humanoid robot (high anthropomorphism) or a smartphone (low anthropomorphism) that have high and low automation level respectively as an ...
Jae-Gil Lee, Jihyang Gu, Dong-Hee Shin
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Kinematics model of unmanned driving vehicle

2010 8th World Congress on Intelligent Control and Automation, 2010
A kinematics characteristic of unmanned driving vehicle based on Ackerman principle was analyzed in this paper, and then the kinematics model was set up. Considering that the vehicle is influenced by different errors such as: side slip, brake or slider, nonholonomic restriction of vehicle is always destroyed, then analyzing this instance and setting up
null Xiaoping Ren, null Zixing Cai
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Autonomous Driving Simulation for Unmanned Vehicles

2015 IEEE Winter Conference on Applications of Computer Vision, 2015
Human can judge driver's driving ability by observing the vehicle motion in different traffic scenes. Identically, driving behavior can be the main basis for evaluating the performance of an unmanned vehicle in both field test and simulation test. Although simulation test avoids disadvantages of field test, existing simulation systems lack traffic ...
Danchen Zhao   +3 more
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Unmanned Driving System Based on DeepLabV3+ Semantic Segmentation

2021 36th Youth Academic Annual Conference of Chinese Association of Automation (YAC), 2021
Recently, semantic segmentation technology has developed rapidly and is gradually applied in the field of autonomous driving. In this paper, DeepLabV3+ semantic segmentation is applied to the driverless system to realize the classification of road scene images at pixel level accuracy, so as to improve the accuracy of collected road information.
Hongyu Wang, Jiefei Ma, Haifei Chi
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Control of Hybrid Drive for Unmanned Aerial Vehicle

2018 International Symposium on Electrical Machines (SME), 2018
In the paper, the concept of a hybrid drive control for unmanned aerial vehicle was presented. A combustion engine was coupled with a brushless dc motor by an electromagnetic coupling. The signal processor TMS320F2812 was used to control the hybrid drive and control algorithms of motoring and generating operation of the BLDC and the combustion engine ...
Piotr Bogusz   +3 more
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Development of Unmanned Ground Vehicles Available of Urban Drive

2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009
This paper describes an unmanned ground vehicle that can move urban environment. The UGV technology grows rapidly. Generally UGV is developed for military purpose. Now a days, many university and research institute research new UGV technology for commercial use such as transportation service. This vehicle can drive on the urban environment.
HeeChang Moon   +3 more
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Survey of Pedestrian Action Recognition in Unmanned-Driving

2019
With the development of unmanned-driving car technology, there are higher requirements for the intelligence, safety and stability of intelligent vehicle driving. Especially in a complex and uncertain environment, the driverless car can accurately detect the pedestrian action, which can effectively realize the autonomous driving of the vehicle.
Li Chen   +4 more
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The Design of System for Unmanned Driving Target Car

2009 International Workshop on Intelligent Systems and Applications, 2009
With the use of moving objects in the developing, experimenting, checking and training process of the so-called air to ground and ground to ground equipments, the quality of experiment and training is possibly restrained once the moving objects stand still or can only move with low velocity. So it is necessary to design a system with a target similarly
Yonghong Hu, Xiaolin Zhang
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DRIVE DYNAMICS OF UNMANNED AIRCRAFT

Agrarian Bulletin of the Non-Chernozem Area, 2021
Aleksandr Borisovich Turygin   +1 more
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