Smart City Gnosys

Smart city article details

Title	A Game Theory-Based Pricing Technique For Ridesharing Pairings
ID_Doc	1880
Authors	Magsino E.R.; Ching G.R.C.; Espiritu F.M.M.; Go K.D.
Year	2023
Published	1st International Conference in Advanced Innovation on Smart City, ICAISC 2023 - Proceedings
DOI	http://dx.doi.org/10.1109/ICAISC56366.2023.10085412
Abstract	As more people dwell in urban cities, intelligent transportation systems must cater to the ever increasing demand of public transport. The various modes of transportation should allow affordable and comfortable travel from one point to another in an urban city to discourage people in owning their own vehicle that may result to more traffic congestions and detrimental environmental effects. In this study, we employ empirical urban mobility datasets to evaluate a proposed Game Theory-based pricing method that can be used in ridesharing of two passengers to reduce traveling cost, while keeping the driver revenue approximately equal. We consider passenger pairings where a second commuter's origin and destination points are after the first commuter passenger, thereby, creating an overlapped and shared travel distance between the two commuters. From extensive simulations, our Game Theory-based pricing scheme resulted in (1) approximately 30% less number of active taxi trips needed to transport people from origin to destination places, (2) slight increase in the travel distance of each passenger due to the optimization of shortest path that can cater both commuters (nearly 8% on the average for the three cities), (3) reduced average passenger fare (at least 15% fare reduction) when compared to solo riding, (4) little to no driver revenue increase, and (5) lower passenger fare rate, i.e., cost per kilometer. © 2023 IEEE.
Author Keywords	Game Theory; Passenger Pairing; Ridesharing; Smart Cities

Similar Articles

Id	Similarity	Authors	Title	Published
9772	0.91	Xiao X.; Xu Y.	Application Of A Path-Based Ridesharing User Equilibrium Model Of Drivers Matching Passengers From Multiple Od Pairs To Smart City	Proceedings of SPIE - The International Society for Optical Engineering, 13224 (2024)
11602	0.891	Li J.; Allan V.H.	Balancing Taxi Distribution In A City-Scale Dynamic Ridesharing Service: A Hybrid Solution Based On Demand Learning	2020 IEEE International Smart Cities Conference, ISC2 2020 (2020)
56095	0.889	Luo K.; Agarwal C.; Das S.; Guo X.	The Multi-Vehicle Ride-Sharing Problem	WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining (2022)
24104	0.886	Radakovic D.; Singh A.; Varde A.S.; Lal P.	Enriching Smart Cities By Optimizing Electric Vehicle Ride-Sharing Through Game Theory	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 2022-October (2022)
37504	0.881	Altshuler T.; Altshuler Y.; Katoshevski R.; Shiftan Y.	Modeling And Prediction Of Ride Sharing Utilization Dynamics	Applied Swarm Intelligence (2024)
19510	0.874	Hsieh F.-S.	Development And Comparison Of Ten Differential-Evolution And Particle Swarm-Optimization Based Algorithms For Discount-Guaranteed Ridesharing Systems	Applied Sciences (Switzerland), 12, 19 (2022)
18636	0.873	Gavalas D.; Konstantopoulos C.; Pantziou G.	Design And Management Of Vehicle-Sharing Systems: A Survey Of Algorithmic Approaches	Smart Cities and Homes: Key Enabling Technologies (2016)
58246	0.872	Abdelmoumene H.; Boussahoul S.	Towards Optimized Dynamic Ridesharing System Through Multi-Objective Reinforcement Learning	2024 IEEE International Multi-Conference on Smart Systems and Green Process, IMC-SSGP 2024 (2024)
8894	0.869	Chen Z.; Li P.; Xiao J.; Nie L.; Liu Y.	An Order Dispatch System Based On Reinforcement Learning For Ride Sharing Services	Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020 (2020)
1995	0.868	Sun Y.; Mu C.; Sun J.; He Y.	A Greedy Algorithm-Based Approach For Dynamic Carpooling Matching And Route Selection In Ride-Hailing	Proceedings - 2023 19th International Conference on Mobility, Sensing and Networking, MSN 2023 (2023)