Abstract
Recently, many ride sharing systems have been commercially introduced (e.g., Uber, Flinc, and Lyft) forming a multi-billion dollars industry. The main idea is to match people requesting a certain ride to other people who are acting as drivers on their own spare time. The matching algorithm run by these services is very simple and ignores a wide sector of users who can be exploited to maximize the benefits of these services. In this demo, we demonstrate SHAREK; a driver-rider matching algorithm that can be embedded inside existing ride sharing services to enhance the quality of their matching. SHAREK has the potential to boost the performance and widen the user base and applicability of existing ride sharing services. This is mainly because within its matching technique, SHAREK takes into account user preferences in terms of maximum waiting time the rider is willing to have before being picked up as well as the maximum cost that the rider is willing to pay. Then, within its course of execution, SHAREK applies a set of smart filters that enable it to do the matching so efficiently without the need to many expensive shortest path computations.
| Original language | English |
|---|---|
| Title of host publication | 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 |
| Publisher | Association for Computing Machinery |
| ISBN (Electronic) | 9781450345897 |
| DOIs | |
| Publication status | Published - 31 Oct 2016 |
| Externally published | Yes |
| Event | 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 - Burlingame, United States Duration: 31 Oct 2016 → 3 Nov 2016 |
Other
| Other | 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 |
|---|---|
| Country | United States |
| City | Burlingame |
| Period | 31/10/16 → 3/11/16 |
Fingerprint
Keywords
- Dynamic Matching
- Indexes
- Realtime systems
- Ride Sharing
- Road-network
ASJC Scopus subject areas
- Earth-Surface Processes
- Computer Science Applications
- Modelling and Simulation
- Computer Graphics and Computer-Aided Design
- Information Systems
Cite this
A demonstration of SHAREK : An efficient matching framework for ride sharing systems. / Alarabi, Louai; Cao, Bin; Zhao, Liwei; Mokbel, Mohamed; Basalamah, Anas.
24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016. Association for Computing Machinery, 2016. 95.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A demonstration of SHAREK
T2 - An efficient matching framework for ride sharing systems
AU - Alarabi, Louai
AU - Cao, Bin
AU - Zhao, Liwei
AU - Mokbel, Mohamed
AU - Basalamah, Anas
PY - 2016/10/31
Y1 - 2016/10/31
N2 - Recently, many ride sharing systems have been commercially introduced (e.g., Uber, Flinc, and Lyft) forming a multi-billion dollars industry. The main idea is to match people requesting a certain ride to other people who are acting as drivers on their own spare time. The matching algorithm run by these services is very simple and ignores a wide sector of users who can be exploited to maximize the benefits of these services. In this demo, we demonstrate SHAREK; a driver-rider matching algorithm that can be embedded inside existing ride sharing services to enhance the quality of their matching. SHAREK has the potential to boost the performance and widen the user base and applicability of existing ride sharing services. This is mainly because within its matching technique, SHAREK takes into account user preferences in terms of maximum waiting time the rider is willing to have before being picked up as well as the maximum cost that the rider is willing to pay. Then, within its course of execution, SHAREK applies a set of smart filters that enable it to do the matching so efficiently without the need to many expensive shortest path computations.
AB - Recently, many ride sharing systems have been commercially introduced (e.g., Uber, Flinc, and Lyft) forming a multi-billion dollars industry. The main idea is to match people requesting a certain ride to other people who are acting as drivers on their own spare time. The matching algorithm run by these services is very simple and ignores a wide sector of users who can be exploited to maximize the benefits of these services. In this demo, we demonstrate SHAREK; a driver-rider matching algorithm that can be embedded inside existing ride sharing services to enhance the quality of their matching. SHAREK has the potential to boost the performance and widen the user base and applicability of existing ride sharing services. This is mainly because within its matching technique, SHAREK takes into account user preferences in terms of maximum waiting time the rider is willing to have before being picked up as well as the maximum cost that the rider is willing to pay. Then, within its course of execution, SHAREK applies a set of smart filters that enable it to do the matching so efficiently without the need to many expensive shortest path computations.
KW - Dynamic Matching
KW - Indexes
KW - Realtime systems
KW - Ride Sharing
KW - Road-network
UR - http://www.scopus.com/inward/record.url?scp=85011044840&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85011044840&partnerID=8YFLogxK
U2 - 10.1145/2996913.2996983
DO - 10.1145/2996913.2996983
M3 - Conference contribution
BT - 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016
PB - Association for Computing Machinery
ER -