WS16: Intelligent Driving for Autonomous Driving Vehicles

Workshop Code: 7u9g1

Time: 13:30-17:00


  • Karl Granström
    Affiliation: Chalmers University of Technology, Sweden

  • Xinyu Zhang
    Affiliation: Tsinghua University, China

  • Pr Jean-Philippe LAUFFENBURGER
    Affiliation: Université de Haute-Alsace (Mulhouse)

Scope and Goals

In the past decades, intelligent vehicles have received increasingly significant attention due to their great potential in enhancing vehicle safety and performance, and traffic efficiency. One of the key objectives of intelligent vehicles is to realize a high degree of autonomy under dynamic, complex environments. From multi-disciplinary perspectives including robotics, computer vision, artificial intelligence, control theory, et al, many research efforts have been devoted to improving the performance of autonomous sensing, planning, decision-making and control abilities for intelligent vehicles. Furthermore, due to the requirements of unknown complex environments, it is necessary for intelligent vehicles to have improved learning ability such as online learning and driving skill learning from past experiences for sensing, decison-making, planning and motion control. In real-world traffic, there are various uncertainties and complexities in road and weather conditions, objects and obstacles are dynamic, etc. An autonomous vehicle has to deal with the following technical challenges: (1) to rapidly and accurately detect, recognize and track dynamic objects with complex backgrounds, (2) to implement motion planning and avoid dynamic obstacles with multiple goals such as safety, agility, and traffic efficiency, and (3) to learn from past experience and reuse the learned knowledge to continually improve driving performance. This workshop seeks to explore the areas related to these challenges.

The purpose of this workshop is to gather a group of active researchers in the areas of real-time object detection, recognition and tracking for intelligent vehicles, deep learning for real-time sensing of intelligent vehicles, reinforcement learning for autonomous control of intelligent vehicles, end to End Learning for intelligent vehicles , autonomous decision-making for intelligent vehicles, motion planning of autonomous vehicles, path tracking and motion control for intelligent vehicles, intelligence tests for autonomous vehicles intelligent vehicles in a same room and discuss their most recent research results. The research results can touch upon both advances in theory and applications. The proposed workshop will consist of several invited talks and regular talks.

Topics of Interest

  • Real-time object detection, recognition and tracking for intelligent vehicles
  • Deep learning for real-time sensing of intelligent vehicles
  • Reinforcement learning for autonomous control of intelligent vehicles
  • Autonomous decision-making for intelligent vehicles
  • End to End Learning for intelligent vehicles
  • Motion planning of autonomous vehicles
  • Path tracking and motion control for intelligent vehicles
  • Intelligence tests for autonomous vehicles
  • Other machine learning approaches with applications in autonomous vehicles


  • Bayesian Framework for Autonomous Vehicle Localization

  • Multi-Objective Adaptive Cruise Control Strategy Based on Variable Time Headway

  • Lane Detection and Road Surface Reconstruction Based on Multiple Vanishing Points

  • Low Latency V2X Applications and Network Requirements: Performance Evaluation