Advanced Sensing and Control for Connected and Automated Vehicles
Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data,...
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| Format: | Online |
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| Sprog: | engelsk |
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MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Online adgang: | ONIX_20220506_9783036534879_191 |
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| _version_ | 1869524665656934400 |
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| collection | Directory of Open Access Books |
| description | Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs. |
| format | Online |
| id | doab-20.500.12854ir-81125 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-811252024-04-09T23:16:11Z Advanced Sensing and Control for Connected and Automated Vehicles Huang, Chao Du, Haiping Zhao, Wanzhong Zhao, Yifan Yan, Fuwu Lv, Chen TROOP truck platooning path planning kalman filter V2V communication string stability off-tracking articulated cargo trucks kabsch algorithm potential field sigmoid curve autonomous vehicles connected and autonomous vehicles artificial neural networks end-to-end learning multi-task learning urban vehicle platooning simulation attention executive control simulated driving task-cuing experiment electroencephalogram fronto-parietal network object vehicle estimation radar accuracy data-driven radar latency weighted interpolation autonomous vehicle urban platooning vehicle-to-vehicle communication in-vehicle network analytic hierarchy architecture traffic scenes object detection multi-scale channel attention attention feature fusion collision warning system ultra-wideband dead reckoning time to collision vehicle dynamic parameters Unscented Kalman Filter multiple-model electric vehicle unified chassis control unsprung mass autonomous driving trajectory tracking real-time control model predictive control tyre blow-out yaw stability roll stability vehicle dynamics model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs. 2022-05-06T11:29:11Z 2022-05-06T11:29:11Z 2022 book ONIX_20220506_9783036534879_191 9783036534879 9783036534886 https://directory.doabooks.org/handle/20.500.12854/81125 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/5154 https://mdpi.com/books/pdfview/book/5154 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-3488-6 10.3390/books978-3-0365-3488-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036534879 9783036534886 284 Basel open access |
| spellingShingle | TROOP truck platooning path planning kalman filter V2V communication string stability off-tracking articulated cargo trucks kabsch algorithm potential field sigmoid curve autonomous vehicles connected and autonomous vehicles artificial neural networks end-to-end learning multi-task learning urban vehicle platooning simulation attention executive control simulated driving task-cuing experiment electroencephalogram fronto-parietal network object vehicle estimation radar accuracy data-driven radar latency weighted interpolation autonomous vehicle urban platooning vehicle-to-vehicle communication in-vehicle network analytic hierarchy architecture traffic scenes object detection multi-scale channel attention attention feature fusion collision warning system ultra-wideband dead reckoning time to collision vehicle dynamic parameters Unscented Kalman Filter multiple-model electric vehicle unified chassis control unsprung mass autonomous driving trajectory tracking real-time control model predictive control tyre blow-out yaw stability roll stability vehicle dynamics model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Advanced Sensing and Control for Connected and Automated Vehicles |
| title | Advanced Sensing and Control for Connected and Automated Vehicles |
| title_full | Advanced Sensing and Control for Connected and Automated Vehicles |
| title_fullStr | Advanced Sensing and Control for Connected and Automated Vehicles |
| title_full_unstemmed | Advanced Sensing and Control for Connected and Automated Vehicles |
| title_short | Advanced Sensing and Control for Connected and Automated Vehicles |
| title_sort | advanced sensing and control for connected and automated vehicles |
| topic | TROOP truck platooning path planning kalman filter V2V communication string stability off-tracking articulated cargo trucks kabsch algorithm potential field sigmoid curve autonomous vehicles connected and autonomous vehicles artificial neural networks end-to-end learning multi-task learning urban vehicle platooning simulation attention executive control simulated driving task-cuing experiment electroencephalogram fronto-parietal network object vehicle estimation radar accuracy data-driven radar latency weighted interpolation autonomous vehicle urban platooning vehicle-to-vehicle communication in-vehicle network analytic hierarchy architecture traffic scenes object detection multi-scale channel attention attention feature fusion collision warning system ultra-wideband dead reckoning time to collision vehicle dynamic parameters Unscented Kalman Filter multiple-model electric vehicle unified chassis control unsprung mass autonomous driving trajectory tracking real-time control model predictive control tyre blow-out yaw stability roll stability vehicle dynamics model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | TROOP truck platooning path planning kalman filter V2V communication string stability off-tracking articulated cargo trucks kabsch algorithm potential field sigmoid curve autonomous vehicles connected and autonomous vehicles artificial neural networks end-to-end learning multi-task learning urban vehicle platooning simulation attention executive control simulated driving task-cuing experiment electroencephalogram fronto-parietal network object vehicle estimation radar accuracy data-driven radar latency weighted interpolation autonomous vehicle urban platooning vehicle-to-vehicle communication in-vehicle network analytic hierarchy architecture traffic scenes object detection multi-scale channel attention attention feature fusion collision warning system ultra-wideband dead reckoning time to collision vehicle dynamic parameters Unscented Kalman Filter multiple-model electric vehicle unified chassis control unsprung mass autonomous driving trajectory tracking real-time control model predictive control tyre blow-out yaw stability roll stability vehicle dynamics model n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20220506_9783036534879_191 |