TY - GEN
T1 - Passenger search by spatial index for ridesharing
AU - Cho, Chung Wen
AU - Wu, Yi Hung
AU - Yen, Chieh
AU - Chang, Chun Yen
PY - 2011
Y1 - 2011
N2 - Ridesharing has the great opportunity to reduce the consumption of energy and the emission of harmful gases, and to let people share the traffic costs with others. Most of the current ridesharing systems simply provide a number of candidates for users to choose. Time-consuming negotiation often discourages people from ridesharing. We propose a novel approach that assigns users to form ridesharing groups according to their routes and payments. Given a driver, our goal is to find a group of passengers who will pay the driver the most. Under the payment scheme, the passengers who share rides on the same route will equally share the expense with the driver. For the prompt response to an online system, our approach aims for the near-optimal group, where the available seats on the driver route are occupied by passengers as many as possible. Compared with the previous methods, the experiment results show that our approach incurs a little overhead but obtains answers of good quality, measured by the driver's saving, under various parameter settings.
AB - Ridesharing has the great opportunity to reduce the consumption of energy and the emission of harmful gases, and to let people share the traffic costs with others. Most of the current ridesharing systems simply provide a number of candidates for users to choose. Time-consuming negotiation often discourages people from ridesharing. We propose a novel approach that assigns users to form ridesharing groups according to their routes and payments. Given a driver, our goal is to find a group of passengers who will pay the driver the most. Under the payment scheme, the passengers who share rides on the same route will equally share the expense with the driver. For the prompt response to an online system, our approach aims for the near-optimal group, where the available seats on the driver route are occupied by passengers as many as possible. Compared with the previous methods, the experiment results show that our approach incurs a little overhead but obtains answers of good quality, measured by the driver's saving, under various parameter settings.
KW - Divide-and-conquer
KW - Payment
KW - R-tree
KW - Ridesharing
UR - http://www.scopus.com/inward/record.url?scp=84862937395&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862937395&partnerID=8YFLogxK
U2 - 10.1109/TAAI.2011.23
DO - 10.1109/TAAI.2011.23
M3 - Conference contribution
AN - SCOPUS:84862937395
SN - 9780769546018
T3 - Proceedings - 2011 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2011
SP - 88
EP - 93
BT - Proceedings - 2011 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2011
T2 - 16th Annual Conference on Technologies and Applications of Artificial Intelligence, TAAI 2011
Y2 - 11 November 2011 through 13 November 2011
ER -