Autonomous Emergency Breaking (AEB) Evaluation For Indian Traffic Scenarios using GPS and LiDAR Data

Babu M, Naga Praveen and Gawande, Malika and Rajalakshmi, P (2022) Autonomous Emergency Breaking (AEB) Evaluation For Indian Traffic Scenarios using GPS and LiDAR Data. In: 1st IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022, 20 May 2022 through 22 May 2022, Virtual, Arad.

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Abstract

Autonomous emergency braking (AEB) and forward-collision warning (FCW) is a cutting-edge active safety technology that assists drivers in avoiding or minimizing crashes with global cars and other vulnerable road users (VRU) for SAE autonomy Level 3 and 4 categories. The Indian traffic scenario data is recorded for Hyderabad city using Lidar and GPS sensors. This dataset is available at IIIT Hyderabad. This real-world traffic scenario is converted into a virtual closed-loop scenario for evaluating AEB and FCW for different VRUs in this present study. The synthetic Radar and camera data are generated by the radar detection generator and vision detection generator blocks in the driving scenario simulator. The results of the virtual scenario developed using sensor perception reveals the ego car velocity ego car acceleration when the lead vehicle's time-to-collision (TTC) is less than FCW. The simulation results are observed for a total of 9 seconds. The control algorithms for AEB and FCW prevent accidents with rear-end collisions of global vehicles, and accurate world traffic scenario data assessed its performance. © 2022 IEEE.

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IITH Creators:
IITH CreatorsORCiD
Rajalakshmi, Phttps://orcid.org/0000-0002-7252-6728
Item Type: Conference or Workshop Item (Paper)
Additional Information: ACKNOWLEDGMENT This work was supported by DST National Mission Interdisciplinary Cyber-Physical Systems (NM-ICPS), Technology Innovation Hub on Autonomous Navigation and Data Acquisition Systems: TiHAN Foundations at Indian Institute of Technology (IIT) Hyderabad. Also, would like to thank the International Institute of Information Technology (IIIT) Hyderabad for providing a database on open data sources.
Uncontrolled Keywords: Advanced driver-assistance system (ADAS); Autonomous emergency braking (AEB); Forward collision warning (FCW); GPS and LiDAR; Radio Detection and Ranging (Radar); Time to collision (TTC)
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 12 Oct 2022 12:52
Last Modified: 12 Oct 2022 12:52
URI: http://raiith.iith.ac.in/id/eprint/10909
Publisher URL: http://doi.org/10.1109/GlobConET53749.2022.9872495
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