Conference Proceeding
Authors: Fangda Zhang (University of Massachusetts Amherst) , Shannon Roberts (University of Massachusetts Amherst) , Claudia Goldman (General Motors Advanced Technical Center Israel)
Ridesplitting is both common and important as it facilitates daily transportation needs. Alongside an increase in ridesplitting is the introduction of automated driving systems, which together, bring out the possibility of automated ridesplitting. However, previous studies have identified resistance in the acceptance of automated driving systems. In light of past research on automated driving systems, we used a survey to compare people’s preferences of automated ridesplitting to non-automated ridesplitting. Statistical and text mining techniques were leveraged to analyze the results. We found similarities in the numeric responses of important factors concerning automated and non-automated ridesplitting whereas there were large differences between automated and nonautomated ridesplitting in the text responses. Additionally, people prioritized cost and time in both automated and non-automated ridesplitting. These results can be used in the design of future ridesplitting services, especially with respect to increasing acceptance of and trust in automated ridesplitting services.
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How to Cite: Zhang, F. , Roberts, S. & Goldman, C. (2019) “A Survey Study Measuring People's Preferences Towards Automated and Non-Automated Ridesplitting”, Driving Assessment Conference. 10(2019). doi: https://doi.org/10.17077/drivingassessment.1680