Evaluating two automation feedback aids’ influence on the acceptance of automated truck merging systems

Evaluating two automation feedback aids’ influence on the acceptance of automated truck merging systems

de Jonge, Michael (TU Delft Mechanical, Maritime and Materials Engineering)

Happee, R. (mentor)
de Winter, J.C.F. (graduation committee)
Dreger, F.A. (graduation committee)

Delft University of Technology

Mechanical Engineering | Vehicle Engineering

2019-03-12

Merging is one of the most demanding tasks for a truck driver due to the size, weight and limited visual clearance of a truck. Automating the merging procedure can be the solution for a considerable number of accidents by removing the human factor. People have accepted the risk they are in when driving or being driven but acceptance of automated driving systems remains limited. The goal of this study is to evaluate two automation feedback aids’ influence on the acceptance of automated truck merging systems. An automation confidence feedback bar and top view display, visualizing the surrounding traffic were tested. The feedback aids are evaluated on the number of abortions, mental workload, trust in the system, perceived usefulness of the system and system satisfaction.
Acceptance is the degree to which an individual incorporates the system in his/her driving, or, if the system is not available, intends to use it. Drivers of large trucks exhibit heightened criticism of automation due to professional identity, exposure or familiarity with the traditional task, and some degree of technical knowledge of the current system. Introducing automation feedback gives the driver more information on the automation systems’ status. 41 participants experienced 12 simulations of a truck merging on the highway in a fixed base truck simulator. A high (1.5s gap) and medium workload (2.1s gap) condition paired with merging between cars or trucks created four simulation conditions to test each feedback aid condition (no feedback aid, confidence bar and top view). Mental workload was measured by tonic activity of the GSR. Trust, perceived usefulness and system satisfaction were measured with Jian’s trust and Van der Laan’s system acceptance questionnaires after each feedback aid condition. Five participants rated their vulnerability as ’none at all’, their measurements were removed from further analyses of the feedback aids. A total of 41 abortions were obtained from 432 simulations. A significant difference in abortion rate was found between no feedback aid (22 abortions), the confidence bar (13 abortions) and the top view display (6 abortions). No abortion rate difference was found between merging between cars and trucks caused by visual obstruction. Participants’ mental workload and trust did not change between the feedback aid conditions. Participants rated both feedback aids as more useful and satisfying than driving without a feedback aid with the top view display being favoured over the confidence bar. No correlations were found between driver’s license years and trust, perceived usefulness or system satisfaction in any of the feedback aid conditions. Both feedback aids increased the acceptance of automated truck merging systems. The number of abortions decreased and willingness to use increased by adding either the feedback aids. The top view display showed the largest improvement in acceptance but more extensive research is needed in both feedback aids to assess their benefits in automated driving systems.

Intelligent Vehicles
Autonomous driving
Truck merging
Human factors
Human Machine Interface Design
human machine interaction
Acceptance
Merging
Truck driver

http://resolver.tudelft.nl/uuid:3edbc911-49bc-45db-a252-15d5ce38f9df

Student theses

master thesis

© 2019 Michael de Jonge