cff-version: 1.2.0 abstract: "

This research is based on data gathered in 2020 at Delft University of Technology. This dataset is from a driving simulator experiment, whose goal was to study human drivers' behaviour in mixed traffic, which has both human-driven vehicles and connected and automated vehicles (CAVs).


The driving simulator used is located at the Transport & Planning department of Delft University in the Netherlands. It operates using the SCANeR (v1.9) software by AV Simulation. It is a fixed base driving simulator equipped with a Fanatec steering wheel and pedals, a dashboard mock-up, and three 4 K high-resolution screens which approximately provide 180° vision.


The dataset consists of 36 participants, over different ages and both males and females.


The route in the driving simulator consisted of a motorway with a defined speed limit of 100 km/h. On the motorway, drivers also experienced dynamic speed limit sections, where a decreasing speed limit from 100 to 70 to 50, and again back to 100 was applied. A depiction of the route is attached in this dataset information.


Each driver drove 7 scenarios. The scenarios were defined using two variables: the penetration rate of CAVs (0%, 10% and 40%) and the distance of speed limit information provision to CAVs (300 m, 600 m, and 900 m).


More details about the experiment set-up itself can be found in the master thesis: http://resolver.tudelft.nl/uuid:b2bf818d-1cc9-40fb-8515-eef9b8eb348a


Attached files:

Processed dataset

ReadMe file

Data processing scripts


File formats:

Data /.csv

Data /.xlsx

Jupyternotebooks /.ipynb

" authors: - family-names: Reddy given-names: Nagarjun orcid: "https://orcid.org/0000-0002-9523-4453" - family-names: Farah given-names: Haneen orcid: "https://orcid.org/0000-0002-2919-0253" title: "Driving simulator dataset on human driven vehicles' speed compliance under variable speed limits in mixed traffic with automated vehicles" keywords: version: 1 identifiers: - type: doi value: 10.4121/91308654-6467-49c5-be0f-12b056e42ec7.v1 license: CC BY 4.0 date-released: 2025-03-13