The Monthly Newsletter of IEEE Vehicular Technology Society—February 2020

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From the IEEE VTS Resource Center
Multi-Sensor Data Fusion for Self-Driving Cars

Title: Multi Sensor Data Fusion for Self Driving Cars

Speaker: Thanuka Wickramarathne, UMass Lowell

Description: In this lecture, we explore the notions of multi-sensor data fusion that are applicable to autonomous vehicles operating in dynamic environments. The lecture will begin with a brief introduction to data fusion covering data fusion-levels and architectures for autonomous vehicles; environment perception data and their representation; objects, grids and raw data oriented data fusion problems; and, some other details that play a vital role in real-life sensor fusion applications.

Then we will introduce sensor fusion, target tracking and situational awareness techniques with a special focus on self-driving technologies ranging from simple Kalman filters to advanced interacting multi-modal tracking techniques. In addition, we will also present some of the algorithms that are available in the literature along with some ongoing work on multiple-hypothesis tracking with speakers research group in collaboration with local industry.

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In This Issue
Message from the EiC
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Society
Highlights from the VTS BoG Winter Meeting
A Paradigm Shift for Industry
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Conferences and Events
IEEE VTC2020-Spring
IEEE VTC2020-Fall
IEEE VPPC 2020 in Gijón
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Call for Nominations
2020 VTS Awards
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From the IEEE VTS Resource Center
Multi-Sensor Data Fusion for Self-Driving Cars
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From the IEEE Vehicular Technology Magazine
Transmission Protocol Customization for Network Slicing
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Mobile Radio
Global Rollouts of 5G
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Connected and Automated Vehicles
Volvo Models in Europe Inform Each Other of Hazards
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Transportation Systems
Sydney’s Light Rail for Parramatta, NSW, Australia
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F. Richard Yu

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