Analysis of a local search heuristic for facility location problems
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
On a generalization of the stable roommates problem
ACM Transactions on Algorithms (TALG)
VTrack: accurate, energy-aware road traffic delay estimation using mobile phones
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
Accurate, low-energy trajectory mapping for mobile devices
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Automated land use identification using cell-phone records
HotPlanet '11 Proceedings of the 3rd ACM international workshop on MobiArch
Friendship and mobility: user movement in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying important places in people's lives from cellular network data
Pervasive'11 Proceedings of the 9th international conference on Pervasive computing
Sixth sense transport: challenges in supporting flexible time travel
Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications
Human mobility modeling at metropolitan scales
Proceedings of the 10th international conference on Mobile systems, applications, and services
Mining regular routes from GPS data for ridesharing recommendations
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
The 14th international workshop on mobile computing systems and applications (ACM HotMobile 2013)
ACM SIGMOBILE Mobile Computing and Communications Review
| Hi-index | 0.00 |
Ride-sharing on the daily home-work-home commute can help individuals save on gasoline and other car-related costs, while at the same time reducing traffic and pollution in the city. Work in this area has typically focused on technology, usability, security, and legal issues. However, the success of any ride-sharing technology relies on the implicit assumption that human mobility patterns and city layouts exhibit enough route overlap to allow for ride-sharing on the first place. In this paper we validate this assumption using mobility data extracted from city-wide Call Description Records (CDRs) from the city of Madrid. We derive an upper bound on the effectiveness of ride-sharing by making the simplifying assumption that any commuter can share a ride with any other as long as their routes overlap. We show that simple ride-sharing among people having neighboring home and work locations can reduce the number of cars in the city at the expense of a relatively short detour to pick up/drop off passengers; e.g., for a 0.6 km detour, there is a 52% reduction in the number of cars. Smartphone technology enables additional passengers to be picked up along the way, which can further reduce the number of cars, as much as 67%.