Human-Computer Interaction of Networked Vehicles Based on Big Data and Hybrid Intelligent Algorithm

Intelligent connected vehicle (ICV) refers to realizing the exchange and sharing of intelligent information between vehicles, roads, people, clouds, and so on by carrying advanced on-board sensors, controllers, actuators, and other devices and combining modern communication and network technology. I...

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Vydáno v:Wireless communications and mobile computing Ročník 2022; číslo 1
Hlavní autoři: Shang, Jianfeng, Liu, Huiying, Li, Weidong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Hindawi 2022
John Wiley & Sons, Inc
Témata:
Actuators
Artificial intelligence
Automobiles
Big Data
Cloud computing
Cognitive load
Control theory
Data processing
Datasets
Discriminant analysis
Genetic algorithms
Human motion
Human performance
Human-computer interaction
Hybrid systems
Information resources
Neural networks
Optimization algorithms
Parallel programming
Real time
Sensors
Simulated annealing
Sparsity
Traffic information
Vehicles
Voice recognition
ISSN:1530-8669, 1530-8677
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Shrnutí:Intelligent connected vehicle (ICV) refers to realizing the exchange and sharing of intelligent information between vehicles, roads, people, clouds, and so on by carrying advanced on-board sensors, controllers, actuators, and other devices and combining modern communication and network technology. In the age of big data, the information of everything can be transformed into digital resources, and transportation big data has become a basic resource. This paper constructs a big data platform for traffic data processing to realize the function of real-time collection, processing, and analysis of traffic data. Based on the proposed big data platform, the parallel programming framework of MapReduce and HDFS distributed storage system are used to process the real-time vehicle dynamic information in parallel, and the output result is used as the input of running genetic algorithm simulated annealing (GA-SA) for parallel calculation. At the same time, it studies the impact of various elements on users’ interactive behavior, constructs the demand framework and design model of automobile human-computer interaction, and then realizes fast and comprehensive search. The experimental results show that the human-computer interaction method of intelligent networked vehicle can find the optimal driving path, transmit it to each networked vehicle through the human-computer interaction system, realize human-computer interaction, reduce the impact of user unintentional operation on redundant motion, reduce the motion error accumulation of the system, and improve the performance of human-computer interaction system.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1530-8669
1530-8677
DOI:10.1155/2022/5281132