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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guidotti, R. Sassi, A. Berlingerio, M. Pascale, A. Ghaddar, B. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Comput. Sci., Univ. of Pisa, Pisa, Italy (Guidotti, R.) || IBM Res., Dublin, Ireland (Berlingerio, M.; Pascale, A.; Ghaddar, B.) || Dept. of Eng. Sci. & Methods, Univ. of Modena & Reggio Emilia, Modena, Italy (Sassi, A.) |
| Abstract | Carpooling, i.e. the sharing of vehicles to reach common destinations, is often performed to reduce costs and pollution. Recent works on carpooling and journey planning take into account, besides mobility match, also social aspects and, more generally, non-monetary rewards. In line with this, we present a data-driven methodology for a more enjoyable carpooling. We introduce a measure of enjoyability based on people's interests, social links, and tendency to connect to people with similar or dissimilar interests. We devise a methodology to compute enjoyability from crowd-sourced data, and we show how this can be used on real world datasets to optimize for both mobility and enjoyability. Our methodology was tested on real data from Rome and San Francisco. We compare the results of an optimization model minimizing the number of cars, and a greedy approach maximing the enjoyability. We evaluate them in terms of cars saved, and average enjoyability of the system. We present also the results of a user study, with more than 200 users reporting an interest of 39% in the enjoyable solution. Moreoever, 24% of people declared that sharing the car with interesting people would be the primary motivation for carpooling. |
| Starting Page | 842 |
| Ending Page | 847 |
| File Size | 1015528 |
| Page Count | 6 |
| File Format | |
| ISSN | 21530017 |
| e-ISBN | 9781467365963 |
| DOI | 10.1109/ITSC.2015.142 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-09-15 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Automobiles Trajectory Optimization Twitter Computational modeling |
| Content Type | Text |
| Resource Type | Article |
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