Designing an embedded system for practical applications needs objectives such as high accuracy, low power consumption and cost, and secure environment. NVIDIA’s Jetson is the most popular platform for embedded system applications which promises to achieve a balance between all these objectives. This paper focused on autonomous vehicles and embedded system studies evaluating the Jetson card features used in smart cars. The characteristics of autonomous vehicles and presents the data was compared for researchers categorized by author names, vehicle names, platform, camera, purpose and environment. In paper shows that most of studies had different purposes and tested area in different environments. We also developed a cost-effective lane detection model for developing and testing the autonomous vehicle JetRacer AI Kit and detail the overall structure of the system in this work. We tested the lane detection performance for system feasibility. In addition, we presented our ongoing work to further develop the features of this vehicle based on the proposed framework.
A Review of a Research in Autonomous Vehicles with Embedded Systems
Lect. Notes in Networks, Syst.
The Proceedings of the International Conference on Smart City Applications ; 2023 ; Paris, France October 04, 2023 - October 06, 2023
2024-02-20
11 pages
Article/Chapter (Book)
Electronic Resource
English
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