30 citations · 127 across the 33 of their papers we have counts for
8 papers · 1 filter
Sentinel: An Onboard Lane Change Advisory System for Intelligent Vehicles to Reduce Traffic Delay during Freeway Incidents
Goodarz Mehr, Azim Eskandarian
This paper introduces Sentinel, an onboard system for intelligent vehicles that guides their lane changing behavior during a freeway incident with the goal of reducing traffic cong…
A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery
Ce Zhang, Azim Eskandarian
Common spatial pattern (CSP) is a popular feature extraction method for electroencephalogram (EEG) motor imagery (MI). This study modifies the conventional CSP algorithm to improve…
A Survey and Tutorial of EEG-Based Brain Monitoring for Driver State Analysis
Ce Zhang, Azim Eskandarian
Drivers cognitive and physiological states affect their ability to control their vehicles. Thus, these driver states are important to the safety of automobiles. The design of advan…
Accurate Alignment Inspection System for Low-resolution Automotive and Mobility LiDAR
Seontake Oh, Ji-Hwan You, Azim Eskandarian +1
A misalignment of LiDAR as low as a few degrees could cause a significant error in obstacle detection and mapping that could cause safety and quality issues. In this paper, an accu…
Automatic LiDAR Extrinsic Calibration System using Photodetector and Planar Board for Large-scale Applications
Ji-Hwan You, Seon Taek Oh, Jae-Eun Park +2
This paper presents a novel automatic calibration system to estimate the extrinsic parameters of LiDAR mounted on a mobile platform for sensor misalignment inspection in the large-…
A Probabilistic Approach to Driver Assistance for Delay Reduction at Congested Highway Lane Drops
Goodarz Mehr, Azim Eskandarian
This paper proposes an onboard advance warning system based on a probabilistic prediction model that advises vehicles on when to change lanes for an upcoming lane drop. Using sever…
Traffic Delay Reduction at Highway Diverges Using an Advance Warning System Based on a Probabilistic Prediction Model
Goodarz Mehr, Azim Eskandarian
This paper presents an on-board advance warning system for vehicles based on a probabilistic prediction model that advises them on when to change lanes to reach a highway diverge o…
Estimating the Probability that a Vehicle Reaches a Near-Term Goal State Using Multiple Lane Changes
Goodarz Mehr, Azim Eskandarian
This paper proposes a model to estimate the probability of a vehicle reaching a near-term goal state using one or multiple lane changes based on parameters corresponding to traffic…