Towards Data-Driven On-Demand Transport

Abstract

On-demand transport has been disrupted by Uber and other providers, which are challenging the traditional approach adopted by taxi services. Instead of using fixed passenger pricing and driver payments, there is now the possibility of adaptation to changes in demand and supply. Properly designed, this new approach can lead to desirable tradeo s between passenger prices, individual driver profits and provider revenue. However, pricing and allocations—known as mechanisms—are challenging problems falling in the intersection of economics and computer science. In this paper, we develop a general framework to classify mechanisms in on-demand transport. Moreover, we show that data is key to optimizing each mechanism and analyze a dataset provided by a real-world on-demand transport provider. This analysis provides valuable new insights into eÿcient pricing and allocation in on-demand transport.

Authors and Affiliations

Malcolm Egan, Jan Drchal, Jan Mrkos, Michal Jakob

Keywords

Related Articles

Inpainting large missing regions based on Seam Carving

Inpainting techniques are developed to recover missing image information. Existing inpainting approaches are: Partial Differential Equations Based Inpainting (PDE-BI) and Exemplar-Based Inpainting (EBI). PDE-BI methods u...

An energy-efficient framework for multimedia data routing in Internet of Things (IoTs)

The Internet of Things (IoTs) is an integrated network including physical devices, mobile robots, cameras, sensors, vehicles, etc. There are many items embedded with electronics, software to support a lot of applications...

Tele-Monitoring the Battery of an Electric Vehicle

Nowadays, transportation is one of the main air pollution sources and has a significant impact on human health and environmental quality. The electric vehicle is a zero emission vehicle powered by an electric motor with...

Comparative Study on Power Gating Techniques for Lower Power Delay Product, Smaller Power Loss, Faster Wakeup Time

The power gating is one of the most popular reduction leakage techniques. We make comparison among various power gating schemes in terms of power delay product, energy loss, and wake-up time using the 45-nm Predictive Te...

An Introduction of Real-time Embedded Optimisation Programming for UAV Systems under Disaster Communication

For disaster communications, it is very challenging for the contemporary wireless technology and infrastructure to meet the demands for connectivity. Modern wireless networks should be developed to satisfy the increasing...

Download PDF file
  • EP ID EP46080
  • DOI http://dx.doi.org/10.4108/eai.27-6-2018.154835
  • Views 323
  • Downloads 0

How To Cite

Malcolm Egan, Jan Drchal, Jan Mrkos, Michal Jakob (2018). Towards Data-Driven On-Demand Transport. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 5(14), -. https://europub.co.uk./articles/-A-46080