AI and big trip data for understanding willingness to rideshare
- When:
- Thursday 28 July 2022
- Time:
- 15:00 - 16:30 (BST)
- Where:
- Online (via Zoom) GET DIRECTIONS
Dr Ziqi Li, Lecture in GIScience, University of Glasgow, will present at this UBDC research seminar.
Abstract
Carpool-style ridesharing, compared to traditional solo ride-hailing, can reduce traffic congestion, cut per-passenger carbon emissions, reduce parking infrastructure, and provide a more cost-effective way to travel. Despite these benefits, ridesharing only occupies a small percentage of the total ride-hailing trips in cities. This study integrates big trip data with machine learning and explainable AI (XAI) to understand the factors that influence willingness to take shared rides. We used the City of Chicago as a case study, and results show that users tend to adopt ridesharing for longer distance trips, and the cost of a trip remains the most important factor. We identified a strong diurnal pattern that people prefer to request shared trips during the morning and afternoon peak hours. We also found socio-economic disparities: users who requested trips from neighbourhoods with a high percentage of non-white, a low median household income, a low percentage of bachelor’s degrees, and high vehicle ownership are more likely to share a ride. The findings and the XAI-based analytical framework presented in this study can help transportation network companies and local governments suggest new strategies and policies to promote the adoption of ridesharing for more sustainable and efficient city transportation.
Biography
Ziqi is a Lecturer in GIScience in the School of Geographical and Earth Sciences at the University of Glasgow. He is generally interested in methodological developments and practical applications of spatial statistics and machine learning and has over 20 peer-reviewed publications in these areas. His current interest is in the integration of big data and explainable AI to better understand geospatial phenomena and processes.
Registration
Registration for this online event is available via Eventbrite and full details and instructions for joining will be circulated post-registration.
