During 2014 – 2015, one of the key research problems I was working on was how to understand and design on-demand transport mechanisms. On-demand transport is about how an individual or group can get from point A to point B at a time of their choosing. Common examples are taxi services and now new services such as Uber.
Working in a computer science department, primarily with collaborators Michal Jakob and Nir Oren, I was concerned with how passenger journeys are allocated to drivers and how each journey was priced, together called a mechanism, from an algorithmic perspective. I.e., how can these allocations and pricing be done in a computationally efficient way so that passengers get to where they want to go on time, each driver can earn a living, and service providers (e.g., Uber) can make a profit.
The problem of choosing a mechanism is known in economics as the mechanism selection problem, and must account for a range of technical, social and financial issues. For example, can the available computing resources compute the allocation and pricing quickly enough? Or, are passengers or drivers prepared to bid for a journey (a key problem for auction-based approaches)?
We have explored the problem of mechanism selection in on-demand transport by first enumerating the possible mechanisms and evaluating their performance. We observed in this working paper that each approach (e.g., hackney carriages, taxi dispatcher models, and Uber-type approaches) can be differentiated by limitations on communication and financial exchanges.
After enumerating the possibilities, we have begun to explore how the different mechanisms perform in terms of metrics such as the proportion of passengers served, costs of journeys and provider profit. In particular, we have published work in:
(1) Malcolm Egan, Martin Schaefer, Michal Jakob, and Nir Oren, “A double auction mechanism for on-demand transport networks”, in the Proc. PRIMA 2015: Principles and Practice of Multi-Agent Systems, (2015).
(2) Malcolm Egan, and Michal Jakob, “A profit-aware negotiation mechanism for on-demand transport services”, in the Proc. of the European Conference on Artificial Intelligence (ECAI), (2014)
(3) Malcolm Egan and Michal Jakob, “Market mechanism design for profitable on-demand transport services”, accepted for Transportation Research Part B: Methodological.
A key feature of our article (3) is that we provide and justify an agent-based model for on-demand transport services that captures the preferences of passengers. This means that we do not assume that every passenger will accept whatever they are offered, which is commonly assumed in previous work on on-demand transport mechanisms.
The next step is to continue to study the mechanism selection problem by understanding the requirements and performance of other on-demand transport mechanisms. At the end of the day, we hope that this work will aid new providers and municipalities to decide the kinds of mechanisms they want to support to match the unique economic, social and technical features of their cities. We believe this will provide a means to meet the needs of passengers, drivers, and providers in each city in a sustainable way.
To read more, see the next posts in this series:
- Market-Based On-Demand Transport
- A Simulation Tool for Market-Based On-Demand Transport
- Data-Driven Market Formation in On-Demand Transport