Driver Behaviour during Control Transitions between Adaptive Cruise Control and Manual Driving: Empirics and Models

Silvia Varotto

Research output: ThesisDissertation (TU Delft)

14 Downloads (Pure)

Abstract

Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion and accidents. Field operational Tests have shown that drivers may prefer to deactivate ACC systems that are inactive at low speeds in dense traffic conditions and before changing lanes. These transitions between automated and manual driving are called control transitions. Notwithstanding the potential effects on traffic operations, most car-following and lane-changing models currently used to evaluate the impact of ACC do not describe control transitions. The main objectives of this thesis were to gain empirical insights into driving behaviour during control transitions from full-range ACC to manual driving and to model driver decisions to resume manual control in full-range ACC. To achieve these objectives, empirical data were collected in driver simulator and on-road experiments. Findings in these experiments showed that control transitions influence significantly the driver behaviour characteristics for a few seconds after manual control is resumed. Based on the empirical findings and on the Risk Allostasis Theory (RAT), this thesis developed a modelling framework describing the underlying decision-making process of drivers with full-range ACC at an operational level. This continuous-discrete choice model addresses interdependencies across driver decisions to resume manual control and to regulate the ACC target speed in terms of causality, unobserved driver characteristics, and state dependency. The results reveal that driver decisions with full-range ACC can be interpreted based on the RAT. The choice model can be used to forecast driver response to a driving assistance system that adapts its settings to prevent control transitions while guaranteeing safety and comfort. The model can also be implemented into a microscopic traffic flow simulation to evaluate the impact of ACC on traffic flow efficiency and safety, accounting for control transitions and target speed regulations.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • van Arem, B., Supervisor
  • Hoogendoorn, S.P., Supervisor
  • Farah, H., Advisor
Award date3 Dec 2018
Publisher
Print ISBNs978-90-5584-240-7
DOIs
Publication statusPublished - 2018

Keywords

  • Control transitions
  • Adaptive Cruise Control
  • On-road experiment
  • Driver simulator experiment
  • Driver behaviour
  • Continuous-discrete choice model

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