no code implementations • 2 Jan 2024 • Sagar Dasgupta, Kazi Hassan Shakib, Mizanur Rahman
To collect data, a vehicle equipped with a GNSS receiver, along with Inertial Measurement Unit (IMU) is used.
no code implementations • 31 Oct 2022 • Muhammad Sami Irfan, Mizanur Rahman, Travis Atkison, Sagar Dasgupta, Alexander Hainen
Specifically, an RL agent is trained to learn an optimal rate of sybil vehicle injection to create congestion for an approach(s).
no code implementations • 9 Sep 2022 • Finley Walden, Sagar Dasgupta, Mizanur Rahman, Mhafuzul Islam
Although visual sensors of an AV, such as camera, lidar, and radar, help to see its surrounding environment, an AV cannot see beyond those sensors line of sight.
no code implementations • 9 Sep 2022 • Sagar Dasgupta, Kazi Shakib, Mizanur Rahman, Silvana V Croope, Steven Jones
The objective of this study is to develop an innovative audio analytics-based human trafficking detection framework for autonomous vehicles.
no code implementations • 19 Aug 2021 • Sagar Dasgupta, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury
Data from multiple low-cost in-vehicle sensors (i. e., accelerometer, steering angle sensor, speed sensor, and GNSS) are fused and fed into a recurrent neural network model, which is a long short-term memory (LSTM) network for predicting the location shift, i. e., the distance that an AV travels between two consecutive timestamps.
no code implementations • 19 Aug 2021 • Sagar Dasgupta, Tonmoy Ghosh, Mizanur Rahman
We find that the accuracy of the RL model ranges from 99. 99% to 100%, and the recall value is 100%.
no code implementations • 19 Aug 2021 • Sagar Dasgupta, Courtland Hollis, Mizanur Rahman, Travis Atkison
Thus, the objectives of this paper are to: (i) develop a "slow poisoning" attack generation strategy for an ATSC, and (ii) develop a prediction-based "slow poisoning" attack detection strategy using a recurrent neural network -- i. e., long short-term memory model.
no code implementations • 5 Jun 2021 • Sagar Dasgupta, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury
In this study, a sensor fusion based GNSS spoofing attack detection framework is presented that consists of three concurrent strategies for an autonomous vehicle (AV): (i) prediction of location shift, (ii) detection of turns (left or right), and (iii) recognition of motion state (including standstill state).
no code implementations • 16 Oct 2020 • Sagar Dasgupta, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury
A spoofed attack is difficult to detect as a spoofer (attacker who performs spoofing attack) can mimic the GNSS signal and transmit inaccurate location coordinates to an AV.