A survey of Automotive Driving Assistance Systems technologies

In the last decade, many researches have been done in the area of intelligent vehicles all over the world, led to Intelligent Transportation Systems (ITS) that improve road safety and reduce traffic accidents. Autonomous intelligent vehicles are now widely applied to Driver Assistance and Safety War...

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Published in2018 International Conference on Artificial Intelligence and Data Processing (IDAP) pp. 1 - 12
Main Authors Swief, Asmaa, El-Habrouk, Mohamed
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2018
Subjects
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DOI10.1109/IDAP.2018.8620826

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Abstract In the last decade, many researches have been done in the area of intelligent vehicles all over the world, led to Intelligent Transportation Systems (ITS) that improve road safety and reduce traffic accidents. Autonomous intelligent vehicles are now widely applied to Driver Assistance and Safety Warning Systems (DASWS), such as Forward Collision Warning, Adaptive Cruise Control, and Lane Departure Warning. Recently, better traffic capacity and traffic safety can be implemented using computer control, artificial intelligence and communication technologies. Many features as, lane departure systems, fatigue detection systems, automatic cruise control, light and sight assist), etc., In addition to self-driving Artificial Intelligent (AI) technologies can greatly reduce driver's workload and improve transportation system safety. This survey provides information about the environment perception modeling and the local map to build the localization and map building module by processing the original data like the sensors 'information of vision, LIght Detection And Ranging (LIDAR), RAdio Detection And Ranging (RADAR), etc. This information uses the geometric feature location estimated in the map to determine the vehicle's position, and to interpret sensor information to estimate the locations of geometric features in a global map. It also provides information about objects detection and motion planning techniques, motion control, sensors' features, safety and security framework.
AbstractList In the last decade, many researches have been done in the area of intelligent vehicles all over the world, led to Intelligent Transportation Systems (ITS) that improve road safety and reduce traffic accidents. Autonomous intelligent vehicles are now widely applied to Driver Assistance and Safety Warning Systems (DASWS), such as Forward Collision Warning, Adaptive Cruise Control, and Lane Departure Warning. Recently, better traffic capacity and traffic safety can be implemented using computer control, artificial intelligence and communication technologies. Many features as, lane departure systems, fatigue detection systems, automatic cruise control, light and sight assist), etc., In addition to self-driving Artificial Intelligent (AI) technologies can greatly reduce driver's workload and improve transportation system safety. This survey provides information about the environment perception modeling and the local map to build the localization and map building module by processing the original data like the sensors 'information of vision, LIght Detection And Ranging (LIDAR), RAdio Detection And Ranging (RADAR), etc. This information uses the geometric feature location estimated in the map to determine the vehicle's position, and to interpret sensor information to estimate the locations of geometric features in a global map. It also provides information about objects detection and motion planning techniques, motion control, sensors' features, safety and security framework.
Author Swief, Asmaa
El-Habrouk, Mohamed
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Snippet In the last decade, many researches have been done in the area of intelligent vehicles all over the world, led to Intelligent Transportation Systems (ITS) that...
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SubjectTerms and deep learning
Autonomous driving
Autonomous vehicles
Buildings
Cruise control
Laser radar
lateral control
Localization and map building
longitudinal control
object detection techniques
path planning
Safety
Sensor phenomena and characterization
Title A survey of Automotive Driving Assistance Systems technologies
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