Volunteers Wanted for Autonomous Vehicles Committee
Shuqing Zeng, VTS Ad Hoc Committee on Autonomous Vehicles Chair

The VTS Ad Hoc Committee on Autonomous Vehicles is seeking volunteers to fill positions as Vice-Chair and Members. Any current IEEE or VTS member may apply.

Selected volunteers will initiate related projects within VTS that focus on autonomous vehicles, and take other actions to enhance professional development amongst VTS members with respect to autonomous vehicles.

Two projects currently in discussion are:

About the VTS Ad Hoc Committee on Autonomous Vehicles

Recent breakthroughs in artificial intelligence, sensor, connected vehicle, and electrification technologies come together to get autonomous vehicles (AV) driving safely and efficiently.

However, the reported fatal accidents involving vehicles with AV systems have raised public concerns on safety of AVs. If the robustness and maturity of state-of-the-art autonomous vehicle systems is not further improved, the full potential of autonomous vehicles cannot be achieved.

The VTS Ad Hoc Committee on Autonomous Vehicles is tasked to identify unsolved problems and invite research in the technical aspects of automated driving.

The Committee considers methods and representative techniques to solve typical problems or to document successful test cases and applications. The addressed modalities of the system may range from ego self-contained vehicles to ad-hoc networked platoons, and they may be designed as multi-vehicle systems assisted by cloud computing as well as edge computing.

Key topics include (but are not limited to):

Architectures for intelligent autonomous systems

Validation and verification of autonomous systems

End-to-end driving (generate actuator commands directly from sensory input)

Collected vehicles

Vehicle-to-vehicle communication

AV assisted by edge computing

Advanced driver-assistance systems (ADAS)

Sensors and hardware (e.g., mono-camera, stereo-camera, omnidirectional camera, automotive radars, LiDARs, multiple camera array)

Active sensing

Localization and mapping

GPS-IMU positioning fusion

Simultaneous localization and mapping

Visual odometry

A priori map-based localization

Digital map construction and change management

Perception and multi-modality sensor fusion

Presentation learning with multi-modality sensors

Object detection

Semantic segmentation

3D object detection from 3D point cloud

Object tracking and re-identification

Lane detection and tracking

Drivable space identification and plan

Threat assessment and situation analysis

Uncertainty decision making

Vehicle maneuver and behavior planning

Path and motion trajectory planning

Vehicle dynamics modeling

Advanced model-predicted vehicle control

Reinforcement learning and its application in autonomous driving

Multi-task reinforcement learning

Vehicle simulation and use scenario generation

Semi-automated image or point clouding annotation system

Physical-based photometric modelling and radiometric modelling in simulation

Biography—Shuqing Zeng (M’03–SM’12) received a PhD in Computer Science from Michigan State University in 2004. Since then, he has been with the General Motors Research and Development Center, where he is currently a Staff Researcher. His research interests include computer vision, sensor fusion, autonomous driving, and vehicle active-safety applications. He was a team member of Tartan Racing who won the 2007 DARPA Urban Challenge. He designed the perception system of the semi-autonomous system Super Cruise, first deployed in the 2018 Cadillac CT6.

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