AIMC Topic: Motor Vehicles

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Hybrid SVM-CNN Classification Technique for Human-Vehicle Targets in an Automotive LFMCW Radar.

Sensors (Basel, Switzerland) Jun 21, 2020
Human-vehicle classification is an essential component to avoiding accidents in autonomous driving. The classification technique based on the automotive radar sensor has been paid more attention by related researchers, owing to its robustness to low-...
Humans Accidents, Traffic Neural Networks, Computer Radar Motor Vehicles Algorithms Support Vector Machine Pedestrians
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Beyond safety drivers: Applying air traffic control principles to support the deployment of driverless vehicles.

PloS one May 21, 2020
By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles' deployment, and provide employment. It is bec...
Software Algorithms Computer Systems Humans Artificial Intelligence Man-Machine Systems Aviation Motor Vehicles Safety Automobile Driving Automation United States Models, Theoretical Robotics
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Co-existence or displacement: Do street trials of intelligent vehicles test society?

The British journal of sociology Jan 14, 2020
This paper examines recent street tests of autonomous vehicles (AVs) in the UK and makes the case for an experimental approach in the sociology of intelligent technology. In recent years intelligent vehicle testing has moved from the laboratory to th...
Motor Vehicles Cities Automobiles London Humans Artificial Intelligence Technology
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Robust SAR Automatic Target Recognition Based on Transferred MS-CNN with L-Regularization.

Computational intelligence and neuroscience Nov 15, 2019
Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via Convolutional Neural Networks (CNNs) has made huge progress toward deep learning, some key issues still remain unsolved due to the lack of sufficient samples and robust mode...
Warfare Motor Vehicles Image Processing, Computer-Assisted Pattern Recognition, Automated Humans Radar Neural Networks, Computer Machine Learning
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A Multibranch Object Detection Method for Traffic Scenes.

Computational intelligence and neuroscience Nov 11, 2019
The performance of convolutional neural network- (CNN-) based object detection has achieved incredible success. Howbeit, existing CNN-based algorithms suffer from a problem that small-scale objects are difficult to detect because it may have lost its...
Motor Vehicles Light Pattern Recognition, Automated Bicycling Humans Neural Networks, Computer Time Factors Cities
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Large-Truck Safety Warning System Based on Lightweight SSD Model.

Computational intelligence and neuroscience Oct 13, 2019
Transportation is an important link in the mining process, and large trucks are one of the important tools for mine transportation. Due to their large size and small driving position, large trucks have a blind spot, which is a hidden danger to the sa...
Humans Artificial Intelligence Animals Motor Vehicles Safety Pattern Recognition, Automated
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A novel bio-heuristic computing algorithm to solve the capacitated vehicle routing problem based on Adleman-Lipton model.

Bio Systems Jul 29, 2019
DNA computing, as one of potential means to solve complicated computational problems, is a new field of interdisciplinary research, including computational mathematics, parallel algorithms, bioinformatics. Capacitated vehicle routing problem is one o...
Transportation Motor Vehicles Computers, Molecular Models, Theoretical Accidents, Traffic Problem Solving Computer Heuristics Humans Algorithms Computer Simulation Cities Computational Biology
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A hybrid neural network for large-scale expressway network OD prediction based on toll data.

PloS one May 23, 2019
Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collec...
Automobile Driving Motor Vehicles China Models, Theoretical Data Interpretation, Statistical Humans Neural Networks, Computer
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Applying machine learning approaches to analyze the vulnerable road-users' crashes at statewide traffic analysis zones.

Journal of safety research May 10, 2019
INTRODUCTION: In this paper, we present machine learning techniques to analyze pedestrian and bicycle crash by developing macro-level crash prediction models.
Motor Vehicles Automobile Driving Bicycling Transportation Pedestrians Accidents, Traffic Safety Humans Machine Learning Socioeconomic Factors Environment Design Models, Statistical
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Evaluate driver response to active warning system in level-2 automated vehicles.

Accident; analysis and prevention Apr 18, 2019
As vehicles with automated functions become more prevalent on U.S. roadways, maintaining driver attention while the vehicle is engaged in automation will be an important consideration for safe operation of these vehicles. The objective of this paper ...
Artificial Intelligence Female Young Adult Adult Male Middle Aged Humans Motor Vehicles Case-Control Studies Automobile Driving Time Factors Automation Attention Protective Devices
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