427 citations · 962 across the 17 of their papers we have counts for
18 papers
PBP: Path-based Trajectory Prediction for Autonomous Driving
Sepideh Afshar, Nachiket Deo, Akshay Bhagat +5
Trajectory prediction plays a crucial role in the autonomous driving stack by enabling autonomous vehicles to anticipate the motion of surrounding agents. Goal-based prediction mod…
Safe Control Transitions: Machine Vision Based Observable Readiness Index and Data-Driven Takeover Time Prediction
Ross Greer, Nachiket Deo, Akshay Rangesh +2
To make safe transitions from autonomous to manual control, a vehicle must have a representation of the awareness of driver state; two metrics which quantify this state are the Obs…
Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context
Ross Greer, Akshay Gopalkrishnan, Nachiket Deo +2
Detecting road traffic signs and accurately determining how they can affect the driver's future actions is a critical task for safe autonomous driving systems. However, various tra…
On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Dataset
Ross Greer, Jason Isa, Nachiket Deo +2
Safe path planning in autonomous driving is a complex task due to the interplay of static scene elements and uncertain surrounding agents. While all static scene elements are a sou…
Predicting Take-over Time for Autonomous Driving with Real-World Data: Robust Data Augmentation, Models, and Evaluation
Akshay Rangesh, Nachiket Deo, Ross Greer +2
Understanding occupant-vehicle interactions by modeling control transitions is important to ensure safe approaches to passenger vehicle automation. Models which contain contextual,…
Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals
Nachiket Deo, Eric M. Wolff, Oscar Beijbom
Accurately predicting the future motion of surrounding vehicles requires reasoning about the inherent uncertainty in driving behavior. This uncertainty can be loosely decoupled int…
Autonomous Vehicles that Alert Humans to Take-Over Controls: Modeling with Real-World Data
Akshay Rangesh, Nachiket Deo, Ross Greer +2
With increasing automation in passenger vehicles, the study of safe and smooth occupant-vehicle interaction and control transitions is key. In this study, we focus on the developme…
Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Loss
Ross Greer, Nachiket Deo, Mohan Trivedi
Predicting a vehicle's trajectory is an essential ability for autonomous vehicles navigating through complex urban traffic scenes. Bird's-eye-view roadmap information provides valu…
Trajectory Prediction for Autonomous Driving based on Multi-Head Attention with Joint Agent-Map Representation
Kaouther Messaoud, Nachiket Deo, Mohan M. Trivedi +1
Predicting the trajectories of surrounding agents is an essential ability for autonomous vehicles navigating through complex traffic scenes. The future trajectories of agents can b…
Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans
Nachiket Deo, Mohan M. Trivedi
We address the problem of forecasting pedestrian and vehicle trajectories in unknown environments, conditioned on their past motion and scene structure. Trajectory forecasting is a…
Scene Compliant Trajectory Forecast with Agent-Centric Spatio-Temporal Grids
Daniela Ridel, Nachiket Deo, Denis Wolf +1
Forecasting long-term human motion is a challenging task due to the non-linearity, multi-modality and inherent uncertainty in future trajectories. The underlying scene and past mot…
Scene Induced Multi-Modal Trajectory Forecasting via Planning
Nachiket Deo, Mohan M. Trivedi
We address multi-modal trajectory forecasting of agents in unknown scenes by formulating it as a planning problem. We present an approach consisting of three models; a goal predict…
Understanding Pedestrian-Vehicle Interactions with Vehicle Mounted Vision: An LSTM Model and Empirical Analysis
Daniela A. Ridel, Nachiket Deo, Denis Wolf +1
Pedestrians and vehicles often share the road in complex inner city traffic. This leads to interactions between the vehicle and pedestrians, with each affecting the other's motion.…
Looking at the Driver/Rider in Autonomous Vehicles to Predict Take-Over Readiness
Nachiket Deo, Mohan M. Trivedi
Continuous estimation the driver's take-over readiness is critical for safe and timely transfer of control during the failure modes of autonomous vehicles. In this paper, we propos…
Audio segmentation based on melodic style with hand-crafted features and with convolutional neural networks
Amruta Vidwans, Nachiket Deo, Preeti Rao
We investigate methods for the automatic labeling of the taan section, a prominent structural component of the Hindustani Khayal vocal concert. The taan contains improvised raga-ba…
Convolutional Social Pooling for Vehicle Trajectory Prediction
Nachiket Deo, Mohan M. Trivedi
Forecasting the motion of surrounding vehicles is a critical ability for an autonomous vehicle deployed in complex traffic. Motion of all vehicles in a scene is governed by the tra…
Multi-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs
Nachiket Deo, Mohan M. Trivedi
To safely and efficiently navigate through complex traffic scenarios, autonomous vehicles need to have the ability to predict the future motion of surrounding vehicles. Multiple in…
How would surround vehicles move? A Unified Framework for Maneuver Classification and Motion Prediction
Nachiket Deo, Akshay Rangesh, Mohan M. Trivedi
Reliable prediction of surround vehicle motion is a critical requirement for path planning for autonomous vehicles. In this paper we propose a unified framework for surround vehicl…