Car-Following Properties of a Commercial Adaptive Cruise Control System: A Pilot Field Test

Narayana Raju*, Wouter Schakel, Nagarjun Reddy, Yongqi Dong, Haneen Farah

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
66 Downloads (Pure)

Abstract

Automated driving systems, which can take over certain dynamic driving tasks from the driver, are becoming increasingly available in commercial vehicles. One of these automated driving systems widely introduced in commercial vehicles is Adaptive Cruise Control (ACC). This system is designed to maintain certain desired driving speeds and time headways as chosen by drivers and based on the settings available within the system. The properties and actual performance of these systems will affect the traffic flow and its stability. However, the specific properties and their workings are rarely publicly available. Therefore, the main aim of this paper is to test the actual performance of a commercial ACC system under different desired speed and distance gap settings, as well as driving modes in a car-following situation. For this purpose, a pilot field test was conducted in the Netherlands in which two identical commercial vehicles equipped with ACC systems were driven simultaneously. The first vehicle was used to create a prespecified speed profile by adapting the ACC system settings manually, while the second vehicle followed the lead vehicle when the ACC system was engaged to test its actual performance. The main findings indicate that the different system settings affect the car-following indicators, and system response times were found to be comparable to human response times. The eco mode was found to affect some of the car-following indicators, and it does not deteriorate safety below the safety level of driving with short headway setting in drive mode.
Original languageEnglish
Pages (from-to)128-143
Number of pages16
JournalTransportation Research Record
Volume2676
Issue number7
DOIs
Publication statusPublished - 2022

Keywords

  • operations
  • automated/autonomous vehicles
  • vehicle-highway automation
  • autonomous

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