WS17: Connected and Automated Vehicles
( CFP )

Workshop Code: s422g

Time: 13:30-17:00


  • Ge Guo
    Affiliation: Northeastern University, China


  • Shengbo Eben Li
    Affiliation: Tsinghua University, China

  • Yantao Tian
    Affiliation: Jilin University, China

  • Hongbo Gao
    Affiliation: Tsinghua University, China

Scope and Goals

Connected and automated vehicles (CAVs) have the ability of gathering and sharing traffic information and vehicle state with neighboring vehicles. Therefore, CAVs are believed to be a promising technology to deliver greater safety and mobility benefits to the next generation intelligent transportation systems. In particular, CAVs can also bring new perspectives and innovation to autonomous driving and cooperative driving to achieve more comfortable driving experience, realize accurate traffic control and reduce adverse environmental effects. CAVs can be made smarter via the use of advanced technologies such as machine learning, deep reinforcement learning, artificial intelligence, advanced computing, among many others.

This workshop aims to gather researchers in the areas of connected and automated vehicles, hybrid electric vehicles, vehicular cyber-physical systems, and intelligent transportation systems, motion planning and control, path tracking, deep reinforcement learning for autonomous control and decision-making in a same room and discuss their recent research advances in theory and applications.

Topics of Interest

  • Cooperative control of vehicles
  • Vehicular cyber-physical systems
  • Autonomous driving under limit working conditions
  • Driving assistance under low adhesion ground
  • Trajectory tracking control for electric vehicle
  • Deep reinforcement learning for intelligent/autonomous vehicles
  • Autonomous decision-making for intelligent/autonomous vehicles
  • Motion planning of intelligent/autonomous vehicles
  • Path tracking and motion control for intelligent/autonomous vehicles


Invited talks without papers:

  • Dynamical modeling and distributed control of multiple connected vehicles
    Shengbo Li, Tsinghua University, China

  • Hazard-evaluation-oriented Moving Horizon Parallel Steering Control for Driver-Automation Collaboration during Automated Driving
    Hongyan Guo, Jilin University, China,

  • Situational Assessments Based on Uncertainty-Risk Awareness in Complex Traffic Scenarios
    Hongbo Gao, Tsinghua University, China

Presentation with accepted papers:

  • 220. Hazard-Evaluation-Based Driver-Automation Switched Shared Steering Control for Intelligent Vehicles.
    Yangyang Guo, jun liu, Linhuan Song, Hongyan Guo*, Yunfeng Hu, Hong Chen.

  • 247. Decision-Theoretic Cooperative Parking for Connected Vehicles: An Investigation
    ALI Aliedani*, Seng Loke.

  • 358. Deep Q Learning Based High Level Driving Policy Determination
    Kyushik Min, Hayoung Kim, Kunsoo Huh*.

  • 81. Vehicle Platoon Control with Communication Scheduling.
    Liyuan Wang*, Ge Guo, Wei Yue.

  • 204. Observer-based Cooperative Adaptive Cruise Control of Vehicular Platoons with Random Network Access.
    Shixi Wen*, Ge Guo, Yiwen He, Ligang Wu, Qian Zhou.