Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook
A few decades ago, the idea of a car driving without human assistance was something inconceivable. With the advent of deep learning-based machine learning in artificial intelligence, this imaginary idea has become part of our life. Like in other fields, these technological revolutions have brought d...
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Online Access: | http://eprints.utm.my/id/eprint/93452/1/UsmanUllahSheikh2020_InsightsandStrategiesforanAutonomousVehicle.pdf http://eprints.utm.my/id/eprint/93452/ http://dx.doi.org/10.1109/ACCESS.2020.3010940 |
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my.utm.934522021-11-30T08:21:13Z http://eprints.utm.my/id/eprint/93452/ Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook Hafeez, F. Sheikh, U. U. Alkhaldi, N. Al Garni, H. Z. Arfeen, Z. A. A. Khalid, S. TK Electrical engineering. Electronics Nuclear engineering A few decades ago, the idea of a car driving without human assistance was something inconceivable. With the advent of deep learning-based machine learning in artificial intelligence, this imaginary idea has become part of our life. Like in other fields, these technological revolutions have brought drastic changes to the field of automated driving systems. The autonomous vehicle is in the transition state between level 3 and level 4 of automation, but many mysteries are still waiting to be solved. Understanding the environment as precisely as a human driver is still far in the future. To attain human perception requires the capturing of extensive surrounding information that depends on the onboard sensors installed on the vehicle. Because the recent autonomous vehicle is equipped with several sensors, it captures surrounding information in diverse forms. Combining these multi-domain data with sensor fusion is the open area of research that is considered in this paper. Along with sensor fusion, another area of prime importance that is necessary to be explored is the prediction of pedestrian intentions. Though the study of the prediction of a pedestrian's intentions started approximately fifteen years ago, most of the research is based on detection rather than intention. Furthermore, this paper also discusses related research in the field of prediction of the pedestrian's intentions. At the end of the article, this review paper includes open questions, challenges, and proposed solutions. Institute of Electrical and Electronics Engineers Inc. 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/93452/1/UsmanUllahSheikh2020_InsightsandStrategiesforanAutonomousVehicle.pdf Hafeez, F. and Sheikh, U. U. and Alkhaldi, N. and Al Garni, H. Z. and Arfeen, Z. A. and A. Khalid, S. (2020) Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook. IEEE Access, 8 . ISSN 2169-3536 http://dx.doi.org/10.1109/ACCESS.2020.3010940 DOI: 10.1109/ACCESS.2020.3010940 |
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TK Electrical engineering. Electronics Nuclear engineering Hafeez, F. Sheikh, U. U. Alkhaldi, N. Al Garni, H. Z. Arfeen, Z. A. A. Khalid, S. Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
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A few decades ago, the idea of a car driving without human assistance was something inconceivable. With the advent of deep learning-based machine learning in artificial intelligence, this imaginary idea has become part of our life. Like in other fields, these technological revolutions have brought drastic changes to the field of automated driving systems. The autonomous vehicle is in the transition state between level 3 and level 4 of automation, but many mysteries are still waiting to be solved. Understanding the environment as precisely as a human driver is still far in the future. To attain human perception requires the capturing of extensive surrounding information that depends on the onboard sensors installed on the vehicle. Because the recent autonomous vehicle is equipped with several sensors, it captures surrounding information in diverse forms. Combining these multi-domain data with sensor fusion is the open area of research that is considered in this paper. Along with sensor fusion, another area of prime importance that is necessary to be explored is the prediction of pedestrian intentions. Though the study of the prediction of a pedestrian's intentions started approximately fifteen years ago, most of the research is based on detection rather than intention. Furthermore, this paper also discusses related research in the field of prediction of the pedestrian's intentions. At the end of the article, this review paper includes open questions, challenges, and proposed solutions. |
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Article |
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Hafeez, F. Sheikh, U. U. Alkhaldi, N. Al Garni, H. Z. Arfeen, Z. A. A. Khalid, S. |
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Hafeez, F. Sheikh, U. U. Alkhaldi, N. Al Garni, H. Z. Arfeen, Z. A. A. Khalid, S. |
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Hafeez, F. |
title |
Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
title_short |
Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
title_full |
Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
title_fullStr |
Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
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Insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
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insights and strategies for an autonomous vehicle with a sensor fusion innovation: a fictional outlook |
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Institute of Electrical and Electronics Engineers Inc. |
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2020 |
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http://eprints.utm.my/id/eprint/93452/1/UsmanUllahSheikh2020_InsightsandStrategiesforanAutonomousVehicle.pdf http://eprints.utm.my/id/eprint/93452/ http://dx.doi.org/10.1109/ACCESS.2020.3010940 |
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