NavPathNet: Onboard Trajectory Prediction for Two-Wheelers using Navigation Maps-Reference-Cited by-同舟云学术

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NavPathNet: Onboard Trajectory Prediction for Two-Wheelers using Navigation Maps

Published:2024-06-02 Issue: Volume:155 Page:2653-2659
ISSN:
Container-title:2024 IEEE Intelligent Vehicles Symposium (IV)
language:
Short-container-title:

Author:

Immel Fabian¹,Moia Alessandro²,Hu Haohao³

Affiliation:

1. FZI Research Center for Information Technology,Intelligent Systems and Production Engineering,Karlsruhe,Germany

2. Robert Bosch GmbH,Gerlingen-Schillerhoehe,Germany,70839

3. Karlsruhe Institute of Technology (KIT),Institute of Measurement and Control Systems,Karlsruhe,Germany

Funder

Robert Bosch

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10587320/10588370/10588507.pdf?arnumber=10588507

Reference24 articles.

1. Model-Based Prediction of Two-Wheelers

2. Trajectory Forecasts with Uncertainties of Vulnerable Road Users by Means of Neural Networks

3. Trajectory prediction of cyclists using a physical model and an artificial neural network

4. Pose Based Trajectory Forecast of Vulnerable Road Users

5. Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information

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