The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
An Overview of Lidar Imaging Systems for Autonomous Vehicles
Open accessAbstract
Lidar imaging systems are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a race dedicated to deciding the final solution to be implemented. However, the diversity of state-of-the-art approaches to the solution brings a large uncertainty on the decision of the dominant final solution. Furthermore, the performance data of each approach often arise from different manufacturers and developers, which usually have some interest in the dispute. Within this paper, we intend to overcome the situation by providing an introductory, neutral overview of the technology linked to lidar imaging systems for autonomous vehicles, and its current state of development. We start with the main single-point measurement principles utilized, which then are combined with different imaging strategies, also described in the paper. An overview of the features of the light sources and photodetectors specific to lidar imaging systems most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development in autonomous vehicles has been included, in order to present some of the problems which still need to be solved before implementation may be considered as final. The reader is provided with a detailed bibliography containing both relevant books and state-of-the-art papers for further progress in the subject.
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Cited by
Coherent LiDAR With an 8,192-Element Optical Phased Array and Driving Laser
Poulton, C. V., Byrd, M. J., Russo, P., Moss, B., Shatrovoy, O., Khandaker, M., & Watts, M. R. (2022) · IEEE Journal of Selected Topics in Quantum Electronics · doi:10.1109/jstqe.2022.3187707 · Cited by 225
Object Detection for Autonomous Vehicles with Sensor-based Technology Using YOLO
Dazlee, N. M. A. A., Khalil, S. A., Abdul-Rahman, S., & Mutalib, S. (2022) · International Journal of Intelligent Systems and Applications in Engineering · doi:10.18201/ijisae.2022.276 · Cited by 54
Metadata
- Authors
- Royo, S., & Ballesta-Garcia, M.
- Venue
- Applied Sciences
- Publisher
- MDPI AG
- Published
- 2019-09-30
- Volume
- 9
- Issue
- 19
- Pages
- 4093
- ISSN
- 2076-3417 (ISSN-L)
- OpenAlex
- W2977461652
- Cited by
- 494
- References
- 69
- FWCI
- 29.44
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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