*** Code and data underlying the publication: Towards developing socially compliant automated vehicles: Advances, expert insights, and a conceptual framework ***
Authors: Dong, Y., van Arem, B., & Farah, H

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Transport and Planning

Corresponding author: Yongqi Dong
Contact Information:
yongqidong369@gmail.com, qiyuandream@gmail.com


***General Introduction***
This is the source code with processed data of the paper:
Dong, Y., van Arem, B., & Farah, H. (2025). Towards developing socially compliant automated vehicles: Advances, expert insights, and a conceptual framework (Under Review)


Data description: 
The data involves online survey data. Unqualified responses and sensitive data related to job positions have been removed from the collected survey results. The processed data are presented in .CSV and .xlsx files. The provided data can generate the results by using the steps described above.

Code description: Codes are provided in .py files. To run the codes, Python 3.9 (or above) is needed, and relevant packages, e.g., pandas, need to be installed. The processed data files need to be put in the same folder as the code. The Python code can be run on both Windows and Linux systems but they were developed and tested on Windows 10.

Experiment design description: The questionnaire design and detailed questionnaire question lists are provided at https://lnkd.in/gpceU6gQ . The survey can be accessed at https://lnkd.in/evg6Dn9W.


How to use the codes and data to reproduce the figures:

(1) Put the code files and the processed data files in the same folder and simply run the Python code.
(2) For the Sankeymatic diagram to generate Fig. 3 and Fig. 4, one needs to go to https://sankeymatic.com/build/ and copy the relevant source codes in Sankeymatic_data&codesource_Fig3_MethodsUsed.txt and Sankeymatic_data&codesource_Fig4_UseCase.txt, and then simply run and show the plots.
(3) Fig. 7-13 could be generated using the “.xlsx” files in the folder of [TemProcessedDataPlots].
(4) Set up requirements for Python
Python 3.9 (or above)
Relevant packages e.g., pandas.

All relevant figures are also provided in high resolution in the folder of [Figures].
