Smart City Gnosys
Smart city article details
| Title | Robust Cognitive Capability In Autonomous Driving Using Sensor Fusion Techniques: A Survey |
|---|---|
| ID_Doc | 46832 |
| Authors | Nawaz M.; Tang J.K.-T.; Bibi K.; Xiao S.; Ho H.-P.; Yuan W. |
| Year | 2024 |
| Published | IEEE Transactions on Intelligent Transportation Systems, 25, 5 |
| DOI | http://dx.doi.org/10.1109/TITS.2023.3327949 |
| Abstract | Autonomous driving has become a prominent topic with the rise of intelligent urban vision in communities. Advancements in automated driving technology play a significant role in the intelligent transportation system. Autonomous vehicles (AVs) rely heavily on sensor technologies as they are responsible for navigating safely through their environment and avoiding obstacles. This paper aims to outline the vital role of sensor fusion in intelligent transportation systems. Sensor fusion is the process of combining data from multiple sensors to obtain more comprehensive measurements and greater cognitive abilities than a single sensor could achieve. By merging data from different sensors, it ensures that driving decisions are based on reliable data, with improved accuracy, reliability, and robustness in AVs. This paper provides a comprehensive review of AV capacity, impacts, planning, technological challenges, and omitted concerns. We used state-of-the-art evaluation tools to check the performance of different sensor fusion algorithms in AVs. This paper will help us to determine our position, direction, the impacts of AVs on society, the need for smart city mobility outcomes, and the way to solve the auto industry challenges in the future. The analysis of AV systems from the perspective of sensor fusion in this research is expected to be beneficial to current and future researchers. © 2000-2011 IEEE. |
| Author Keywords | autonomous vehicles; LiDAR points; object detection; object tracking; radar points; RGB cameras; Sensor fusion |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
29114  | 0.885 | Stahler J.; Markgraf C.; Pechinger M.; Gao D.W. | High-Performance Perception: A Camera-Based Approach For Smart Autonomous Electric Vehicles In Smart Cities | IEEE Electrification Magazine, 11, 2 (2023) |
| 38397 | 0.88 | Wang X.; Li K.; Chehri A. | Multi-Sensor Fusion Technology For 3D Object Detection In Autonomous Driving: A Review | IEEE Transactions on Intelligent Transportation Systems, 25, 2 (2024) |
| 59333 | 0.87 | Liu X.; Ma W. | Ubiquitous Sensing For Smart Cities With Autonomous Vehicles | The Rise of Smart Cities: Advanced Structural Sensing and Monitoring Systems (2022) |
| 10790 | 0.87 | Samonte M.J.C.; Laqueo L.M.D.; Mampusti R.K.L.; Panganiban K.D.H. | Assessing The Security And Architectural Frameworks Of Self-Driving Cars In Smart Cities | 2024 8th International Conference on Smart Grid and Smart Cities, ICSGSC 2024 (2024) |
| 5200 | 0.861 | Ji W.; Han K.; Liu T. | A Survey Of Urban Drive-By Sensing: An Optimization Perspective | Sustainable Cities and Society, 99 (2023) |
| 57439 | 0.86 | Aoki S.; Yonezawa T.; Kawaguchi N.; Steenkiste P.; Rajkumar R.R. | Time-Sensitive Cooperative Perception For Real-Time Data Sharing Over Vehicular Communications: Overview, Challenges, And Future Directions | IEEE Internet of Things Magazine, 5, 2 (2022) |
| 60387 | 0.858 | Ignatious H.A.; El-Sayed H. | Usecase-Based Generic Framework For Data Fusion And Decision Making In Autonomous Driving | 20th International Wireless Communications and Mobile Computing Conference, IWCMC 2024 (2024) |
| 58036 | 0.857 | Ušinskis V.; Makulavičius M.; Petkevičius S.; Dzedzickis A.; Bučinskas V. | Towards Autonomous Driving: Technologies And Data For Vehicles-To-Everything Communication | Sensors, 24, 11 (2024) |
| 27062 | 0.855 | Mandal R.; Mandal A.; Dutta S.; Yusuf Alam M.; Saha S.; Nandi S. | Framework Of Intelligent Transportation System: A Survey | Lecture Notes in Networks and Systems, 404 (2023) |
| 34724 | 0.855 | Kalda K.; Pizzagalli S.-L.; Soe R.-M.; Sell R.; Bellone M. | Language Of Driving For Autonomous Vehicles | Applied Sciences (Switzerland), 12, 11 (2022) |