Hybrid Mechanisms for On-Demand Transport
- Submitting institution
-
University of Aberdeen
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 140667298
- Type
- D - Journal article
- DOI
-
10.1109/TITS.2018.2886579
- Title of journal
- Transactions on Intelligent Transportation Systems
- Article number
- -
- First page
- 4500
- Volume
- 20
- Issue
- 12
- ISSN
- 1524-9050
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the first to describe an optimal hybrid pricing mechanism for determining taxi journey pricing based on data, which could be used by services such as Uber and Lyft. This work builds on a series of papers appearing in prestigious conferences such as ECAI. The mechanism is evaluated both by examining its theoretical properties and empirically (via simulation on real world data), and is the first work to provide an understanding as to why systems such as Uber function well when compared to existing mechanisms such as standard taxis.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
