@inproceedings{51c7e40aecf441c7b8624d70c9dbac45,
title = "Collision warning system: Embedded enabled (RTMaps with NXP BLBX2)",
abstract = "Forward Collision Warning (FCW) also referred as the Forward Collision Avoidance (FCA) system has become an essential part of the Autonomous cars or smart vehicles. The FCW System has found its position as one of the foremost automobile safety features included in the present smart vehicles. This paper proposes a Forward collision warning system which includes its subsystem as Forward-looking automotive radar model and a Classifier algorithm developed and designed in the Intempora RTMaps Embedded with NXP Bluebox 2.0. The classifier and regression algorithm work on the principle of supervised learning, the proposed model predicts the collision or no-collision occurrence based on the radar sensed inputs. The implementation, precision and accuracy of the classifier and regression algorithm is presented. The proposed model is deployed on the Bluebox 2.0 platform with the RTMaps Embedded framework.",
keywords = "ADAS, AEB, BLBX2, CAMP, Classification, DT, Ego Vehicle, FCA, FCW, GD, Intempora, Lead Vehicle, LR, Regression, RTMaps, SGD, SVM.",
author = "Dewant Katare and Mohamed El-Sharkawy",
year = "2018",
doi = "10.1109/ISSPIT.2018.8705101",
language = "English",
series = "2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
booktitle = "2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018",
address = "United States",
note = "2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018 ; Conference date: 06-12-2018 Through 08-12-2018",
}