Search Results for author: Anne Spalanzani

Found 5 papers, 0 papers with code

Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps

no code implementations8 Aug 2023 Rabbia Asghar, Manuel Diaz-Zapata, Lukas Rummelhard, Anne Spalanzani, Christian Laugier

Motion prediction is a challenging task for autonomous vehicles due to uncertainty in the sensor data, the non-deterministic nature of future, and complex behavior of agents.

Autonomous Vehicles Motion Forecasting +1

Allo-centric Occupancy Grid Prediction for Urban Traffic Scene Using Video Prediction Networks

no code implementations11 Jan 2023 Rabbia Asghar, Lukas Rummelhard, Anne Spalanzani, Christian Laugier

This allows for the static scene to remain fixed and to represent motion of the ego-vehicle on the grid like other agents'.

Video Prediction

Navigation In Urban Environments Amongst Pedestrians Using Multi-Objective Deep Reinforcement Learning

no code implementations11 Oct 2021 Niranjan Deshpande, Dominique Vaufreydaz, Anne Spalanzani

Urban autonomous driving in the presence of pedestrians as vulnerable road users is still a challenging and less examined research problem.

Autonomous Driving Autonomous Navigation +3

Behavioral decision-making for urban autonomous driving in the presence of pedestrians using Deep Recurrent Q-Network

no code implementations26 Oct 2020 Niranjan Deshpande, Dominique Vaufreydaz, Anne Spalanzani

In this work, a deep reinforcement learning based decision-making approach for high-level driving behavior is proposed for urban environments in the presence of pedestrians.

Autonomous Driving Decision Making +2

Building Prior Knowledge: A Markov Based Pedestrian Prediction Model Using Urban Environmental Data

no code implementations17 Sep 2018 Pavan Vasishta, Dominique Vaufreydaz, Anne Spalanzani

Autonomous Vehicles navigating in urban areas have a need to understand and predict future pedestrian behavior for safer navigation.

Autonomous Vehicles

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