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20182023
most citedMulti-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs

427 citations · 962 across the 17 of their papers we have counts for

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15 papers · 1 filter

cs.CV2023

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…

cs.CV2023★ 3 cited

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…

cs.CV2023★ 7 cited

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…

cs.CV2021

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…

cs.CV2021

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,…

cs.CV2021★ 16 cited

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV2020★ 114 cited

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…

cs.CV2019

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…

cs.CV2019

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.…

cs.CV2018★ 3 cited

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…

cs.CV2018

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…

cs.CV2018★ 427 cited

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…

cs.CV2018★ 383 cited

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…