4 results found
Karamanis R, Anastasiadis E, Angeloudis P, et al., 2020, Assignment and pricing of shared rides in ride-sourcing using combinatorial double auctions, IEEE Transactions on Intelligent Transportation Systems, ISSN: 1524-9050
Transportation Network Companies employ dynamic pricing methods at periods of peak travel to incentivise driver participation and balance supply and demand for rides. Surge pricing multipliers are commonly used and are applied following demand and estimates of customer and driver trip valuations. Combinatorial double auctions have been identified as a suitable alternative, as they can achieve maximum social welfare in the allocation by relying on customers and drivers stating their valuations. A shortcoming of current models, however, is that they fail to account for the effects of trip detours that take place in shared trips and their impact on the accuracy of pricing estimates. To resolve this, we formulate a new shared-ride assignment and pricing algorithm using combinatorial double auctions. We demonstrate that this model is reduced to a maximum weighted independent set model, which is known to be APX-hard. A fast local search heuristic is also presented, which is capable of producing results that lie within 10% of the exact approach for practical implementations. Our proposed algorithm could be used as a fast and reliable assignment and pricing mechanism of ride-sharing requests to vehicles during peak travel times.
Karamanis R, Angeloudis P, Sivakumar A, et al., 2018, Dynamic pricing in one-sided autonomous ride-sourcing markets, 21st IEEE International Conference on Intelligent Transportation Systems (ITSC), Publisher: IEEE, Pages: 3645-3650, ISSN: 2153-0009
Dynamic pricing has been used by Transportation Network Companies (TNCs) to achieve a balance between the volume of ride requests with numbers of available drivers on two-sided TNC markets. Given the desire to reduce operating costs and the emergence of Autonomous Vehicles (AVs), the introduction of TNC-owned AV fleets could convert such services into one-sided markets, where operators have full control of service supply. In this paper we investigate the impact of utility-based dynamic pricing for Autonomous TNCs (ATNCs) in one-sided markets. We test the method using an Agent-Based Model (ABM) of Greater London in conditions of monopoly and competition, focusing on a statically priced ATNC service that offers a mix of private and shared ride services. Public transport is considered as an alternative mode of transportation in both scenarios. Results indicate that in monopoly, dynamic pricing provides higher revenues than static pricing at non-peak hours when average waiting times are low. On the contrary, in competition, dynamic pricing is superior at peak hours where increased waiting times are observed, thus increasing the value of low waiting time rides. Overall, in both market structures, it is found that shared trips are more popular in dynamic pricing compared to static pricing.
Karamanis R, Angeloudis P, Sivakumar A, et al., Market dynamics between public transport and competitive ride-sourcing providers, 7th Symposium of the European Association for Research in Transportation, Publisher: hEART
Karamanis R, Niknejad A, Angeloudis P, A Fleet Sizing Algorithm for Autonomous Car Sharing, Transportation Research Board 96th Annual Meeting
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