Supplementary material for the paper: Creating the illusion of sportiness: Evaluating modified throttle mapping and artificial engine sound for electric vehicles

doi: 10.4121/16644697.v2
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/16644697
Datacite citation style:
Melman, Timo; Visser, Peter; Mouton, Xavier; de Winter, Joost (2021): Supplementary material for the paper: Creating the illusion of sportiness: Evaluating modified throttle mapping and artificial engine sound for electric vehicles. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/16644697.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2021-09-30 (latest)
version 1 - 2021-09-21
Delft University of Technology logo
usage stats
1959
views
595
downloads
licence
cc-0.png logo CC0
This file contains the data and the Matlab script used to analyse and generate the figures for the manuscript named: Creating the illusion of sportiness: Evaluating modified throttle mapping and artificial engine sound
for electric vehicles. Published in the Journal of Advanced Transportation.

Specifically,
- 'Matlab Analysis' folder contains the data and the Matlab script for the analysis. The script named "Sportiness_DrivingSimulator_Analysis_clean.m" automatically generates all figures and tables used in the journal paper.
- 'Videos' folder contains an example video (and sound) of each condition used the experiment.
- 'Additional result tables' folder contains 3 additional result tables
- 'Senso_pedals_info' file contains some information about the driving pedals used in this driving simulator experiment.

Abstract of journal paper:

Modern computerized vehicles offer the possibility to change vehicle parameters with the aim of creating a novel driving experience, such as an increased feeling of sportiness. For example, electric vehicles can be designed to provide an artificial sound, and the throttle mapping can be adjusted to give drivers the illusion that they are driving a sports vehicle (i.e., without altering the vehicle’s performance envelope). However, a fundamental safety-related question is how drivers perceive and respond to vehicle parameter adjustments. As of today, human-subject research on throttle mapping is unavailable, whereas research on sound enhancement is mostly conducted in listening rooms, which provides no insight into how drivers respond to the auditory cues. This study investigated how perceived sportiness and driving behavior are affected by adjustments in vehicle sound and throttle mapping. Through a within-subject simulator-based experiment, we investigated (1) Modified Throttle Mapping (MTM), (2) Artificial Engine Sound via a virtually elevated rpm (AES), and (3) MTM and AES combined, relative to (4) a Baseline condition, and (5) a Sports car that offered increased engine power. Results showed that, compared to Baseline, AES and MTM-AES increased perceived sportiness and yielded a lower speed variability in curves. Furthermore, MTM and MTM-AES caused higher vehicle accelerations than Baseline during the first second of driving away from a standstill. Mean speed and comfort ratings were unaffected by MTM and AES. The highest sportiness ratings and fastest driving speeds were obtained for the Sports car. In conclusion, the sound enhancement not only increased the perception of sportiness but also improved drivers’ speed control performance, suggesting that sound is used by drivers as functional feedback. The fact that MTM did not affect the mean driving speed indicates that drivers adapted their ‘gain’ to the new throttle mapping and were not susceptible to risk compensation.



history
  • 2021-09-21 first online
  • 2021-09-30 published, posted
publisher
4TU.ResearchData
format
Excel Worksheet: .xlsx Matlab Data: .m Images: .jpg Plain text: .txt Matroska video: .mkv
organizations
Department of Cognitive Robotics, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology

Group Renault, Chassis Systems Department, Guyancourt, France

Department of Computer and System Engineering, ENSTA ParisTech, Palaiseau Cedex, France

DATA

files (2)