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 in | 2018 International Conference on Artificial Intelligence and Data Processing (IDAP) pp. 1 - 12 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.09.2018
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Subjects | |
Online Access | Get full text |
DOI | 10.1109/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. |
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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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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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