Session D6a: Ground Vehicle Navigation

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Date: Thursday, April 23, 2020
Time: 1:45 p.m. - 5:00 p.m.
Location: Galleria I/II

Session Chairs:

Dr. David Bevly Auburn University	Dr. Victoria Kropp BMW, Germany

1.	Evaluating the Urban Trench Model for Improved GNSS Positioning In Urban Areas: Lucy Icking, Tobias Kersten, and Steffen Schön, Institut für Erdmessung, Germany
2.	Evaluating GNSS Navigation Availability in 3-D Mapped Urban Environments: Kana Nagai, Titilayo Fasoro, Matthew Spenko, Ron Henderson, and Boris Pervan, Illinois Institute of Technology
3.	GNSS/LiDAR Integration Aided by Self-adaptive Gaussian Mixture Models in Urban Scenarios: An Approach Robust to Non-Gaussian Noise: Weisong Wen, Xiwei Bai, Li-Ta Hsu, The Hong Kong Polytechnic University, China; Tim Pfeifer, Chemnitz, Chemnitz University of Technology, Germany
4.	Optimal GPS Integrity-Constrained Path Planning for Ground Vehicles: Mahdi Maaref and Zaher M. Kassas, University of California, Irvine
5.	Robust Vehicle Localization and Integrity Monitoring based on Spatial Feature Constrained PF: Jelena Gabela, Ivan Majic, University of Melbourne, Australia; Allison Kealy, RMIT University, Australia; Mark Hedley, Shenghong Li, CSIRO, Data 61, Australia
6.	Novel Snapshot Integrity Algorithm for Automotive Applications: Test Results Based on Real Data: Rod Bryant, Olivier Julien, Chris Hide, Said Moridi, u-blox, Switzerland; Ian Sheret, Polymath Insight Limited, Switzerland
7.	Effect of Wheel Odometer on Low-cost Visual-Inertial Navigation System for Ground Vehicles: Jaehyuck Cha, Jae Hyung Jung, Jae Young Chung, Tae Ihn Kim, Chan Gook Park, Department of Mechanical & Aerospace Engineering / Automation and Systems Research Institute, Seoul National University, Republic of Korea; Myung Hwan Seo, Sang Yeon Park, Jong Yun Yeo, IVS, In-Vehicle Solution, Development Team, Hyundai MnSOFT, Republic of Korea
8.	Deep Learned Multi-Modal Traffic Agent Predictions for Truck Platooning Cut-Ins: Samuel Paul Douglass Jr., Scott Martin, Andrew Jennings, Howard Chen, David M. Bevly, Auburn University
Alternate
1.	LiDAR Data Enrichment Using Deep Learning Based on High-Resolution Image: An Approach to Achieve High-Performance LiDAR SLAM Using Low-cost LiDAR: Jiang Yue, Hong Kong Polytechnic University & Nanjing University of Science and Technology, China; Weisong Wen, Hong Kong Polytechnic University, China; Jing Han, Nanjing University of Science and Technology, China Li-Ta Hsu, Hong Kong Polytechnic University, China

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