Optimal Control for Speed Harmonization of Automated Vehicles

Andreas A. Malikopoulos, Seongah Hong, B. Brian Park, Joyoung Lee, Seunghan Ryu

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


This paper addresses the problem of controlling the speed of a number of automated vehicles before they enter a speed reduction zone on a freeway. We formulate the control problem and provide an analytical, closed-form solution that can be implemented in real time. The solution yields the optimal acceleration/deceleration of each vehicle under the hard safety constraint of rear-end collision avoidance. The effectiveness of the solution is evaluated through a microscopic simulation testbed and it is shown that the proposed approach significantly reduces both fuel consumption and travel time. In particular, for three different traffic volume levels, fuel consumption for each vehicle is reduced by 19-22% compared to the baseline scenario, in which human-driven vehicles are considered, by 12-17% compared to the variable speed limit algorithm, and by 18-34% compared to the vehicular-based speed harmonization (SPD-HARM) algorithm. Similarly, travel time is improved by 26-30% compared to the baseline scenario, by 3-19% compared to the VSL algorithm, and by 31-39% compared to the vehicular-based SPD-HARM algorithm.

Original languageEnglish (US)
Article number8464283
Pages (from-to)2405-2417
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number7
StatePublished - Jul 2019

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


  • Vehicle speed control
  • automated vehicles
  • energy usage
  • optimal control
  • speed harmonization


Dive into the research topics of 'Optimal Control for Speed Harmonization of Automated Vehicles'. Together they form a unique fingerprint.

Cite this