TY - JOUR
T1 - Human satisfaction as the ultimate goal in ridesharing
AU - Levinger, Chaya
AU - Hazon, Noam
AU - Azaria, Amos
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/11
Y1 - 2020/11
N2 - Transportation services play a crucial part in the development of modern smart cities. In particular, on-demand ridesharing services, which group together passengers with similar itineraries, are already operating in several metropolitan areas. These services can be of significant social and environmental benefit, by reducing travel costs, road congestion and CO2 emissions. The deployment of autonomous cars in the near future will surely change the way people are traveling. It is even more promising for a ridesharing service, since it will be easier and cheaper for a company to handle a fleet of autonomous cars that can serve the demands of different passengers. We argue that user satisfaction should be the main objective when trying to find the best assignment of passengers to vehicles and the determination of their routes. Moreover, the model of user satisfaction should be rich enough to capture the traveling time, cost, and other factors as well. We show that it is more important to capture a rich model of human satisfaction than peruse an optimal performance. That is, we developed a practical algorithm for assigning passengers to vehicles, which outperforms brute-force assignment algorithms that use a simpler satisfaction model. To the best of our knowledge, this is the first paper to exclusively concentrate on a rich and realistic general function of user satisfaction as the objective, which is (arguably) the most important aspect to consider for achieving a widespread adaption of ridesharing services.
AB - Transportation services play a crucial part in the development of modern smart cities. In particular, on-demand ridesharing services, which group together passengers with similar itineraries, are already operating in several metropolitan areas. These services can be of significant social and environmental benefit, by reducing travel costs, road congestion and CO2 emissions. The deployment of autonomous cars in the near future will surely change the way people are traveling. It is even more promising for a ridesharing service, since it will be easier and cheaper for a company to handle a fleet of autonomous cars that can serve the demands of different passengers. We argue that user satisfaction should be the main objective when trying to find the best assignment of passengers to vehicles and the determination of their routes. Moreover, the model of user satisfaction should be rich enough to capture the traveling time, cost, and other factors as well. We show that it is more important to capture a rich model of human satisfaction than peruse an optimal performance. That is, we developed a practical algorithm for assigning passengers to vehicles, which outperforms brute-force assignment algorithms that use a simpler satisfaction model. To the best of our knowledge, this is the first paper to exclusively concentrate on a rich and realistic general function of user satisfaction as the objective, which is (arguably) the most important aspect to consider for achieving a widespread adaption of ridesharing services.
KW - Human–agent interaction
KW - Modeling human behavior
KW - Ride-sharing
KW - Smart-cities
UR - http://www.scopus.com/inward/record.url?scp=85085273995&partnerID=8YFLogxK
U2 - 10.1016/j.future.2020.05.028
DO - 10.1016/j.future.2020.05.028
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AN - SCOPUS:85085273995
SN - 0167-739X
VL - 112
SP - 176
EP - 184
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -