profile photo

Ke Ma

Ke Ma is a Ph.D. student in the Connected & Autonomous Transportation Systems (CATS) Laboratory at the University of Wisconsin-Madison , U.S. (advised by Prof. Xiaopeng (Shaw) Li ), where he works on Connected and Automated Vehicle, Traffic Flow Theory, Control Theory, and Machine Learning, etc. Before that, he obtained his Bachelor and Master degree (advised by Prof. Hao Wang ) from Central South University, Changsha, China in 2018 and Southeast University, Nanjing, China 2021, respectively.

Email  /  Google Scholar  /  Linkedin  /  Github  /  Zhihu  /  Researchgate


  • 11/2022, Paper is published by Transportation Research part-C , "String Stability of Automated Vehicles Based on Experimental Analysis of Feedback Delay and Parasitic Lag".
  • 10/2022, Podium presentaion in Indian Informs 2022.
  • 09/2022, One conference paper is accpected by TRB 2022.
  • 08/2022, Two conference papers are accpected by IEEE ITSC 2022.
  • Projects

  • Longitudinal Control for CAV Test
  • Recent literature shows that automated vehicle (AV) significantly impacts traffic flow stability. However, as a widely used longitudinal AV technology, the Adaptive Cruise Control (ACC) system still has several unknown features that lack field data for modeling. We ran a series of novel tests with two ACC vehicles to simulate the behavior of the AV platoon in the field experiment. We designed a linear car-following controller in the upper layer system and tested the string stability of the ACC vehicle platoon. Data is collected through the vehicle's GPS sensor and upper controller. These data can help us estimate the feedback delay in the upper layer and parasitic lag in the lower layer.

    Read more

  • Communication for V2X
  • A binary light code is developed for V2X communications based on cameras and LED lights. Several use cases (UCs) for implementing the binary light code are defined as follows...

  • Machine learning in AV
  • Connected and automated vehicles (CAVs) play an important role in the intelligent transportation system. The decision of CAVs lane-changing in heterogeneous traffic flow composed of CAVs and regular vehicles (RVs) becomes a key link. We build a framework of the lane-changing decisions on wide spatiotemporal conditions (WST-LCDF) for CAVs training and leaning to increase CAVs speed at automation-to-driver handover. In addition, the normal prediction index (RMSE and MAPE) and the simulation result index ( and ) were conducted to evaluate the influence of WST-LCDF...


  • Connected and automated vehicle micro-traffic simulation platform(CAVSP) , "Github page"
  • Research

    Journal Paper:

    1. String stability of automated vehicles based on experimental analysis of feedback delay and parasitic lag | paper
      Ke Ma, Hao Wang, Zewen Zuo, Yuxuan Hou, Xiaopeng Li, Rui Jiang
      Transportation Research Part C: Emerging Technologies, 2022

    2. Analysis of road capacity and pollutant emissions: Impacts of Connected and automated vehicle platoons on traffic flow | paper
      Ke Ma, Hao Wang, Tiancheng Ruan
      Physica A: Statistical Mechanics and its Applications, 2021

    3. How Connected and Automated Vehicle-Exclusive Lanes Affect On-Ramp Junctions | paper
      Ke Ma, Hao Wang
      Journal of Transportation Engineering, Part A: Systems, 2021

    4. Influence of exclusive lanes for connected and autonomous vehicles on freeway traffic flow | paper
      Ke Ma, Hao Wang
      IEEE Access, 2019

    5. The automatic detection of pedestrians under the high-density conditions by deep learning techniques | paper
      Cheng-Jie Jin, Xiaomeng Shi, Ting Hui, Dawei Li, and Ke Ma
      Journal of Advanced Transportation, 2021

    6. Impact of CAV platoon management on traffic flow considering degradation of control mode | paper
      Linjie Zhou, Tiancheng Ruan, Ke Ma, Changyin Dong, and Hao Wang
      Physica A: Statistical Mechanics and its Applications, 2021

    Conference paper:

    1. Vehicle Trajectory Prediction With A Physics-aware Learning-based Model Considering Shockwaves In A Connected Vehicle Environment | paper
      Indian Informs, 2022

    2. A deep learning lane-changing decision framework with wide spatiotemporal conditions for connected and automated vehicles | paper
      IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022

    3. Empirical study of feedback delay in stability analysis for production vehicles with different powertrains | paper
      IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022

    4. Empirical Study of Response Delay of Production Automated Vehicles | paper
      International Conference on Transportation and Development, 2022

    5. Lane-changing decision model for connected and automated vehicle based on back-propagation neural network | paper
      International Conference on Transportation and Development, 2020

    6. A cellular automaton model considering the exclusive lanes of autonomous vehicles on expressway | paper
      CICTP COTA, 2019


  • Member in University of South Florida’s Institute of Transportation Engineers.

  • Awards

  • 2019, China National Scholarship

  • Welcome to this website! No. Visitor Since Jun 2020. Powered by w3.css