A Nash equilibrium formulation of a tradable credits scheme for incentivizing transport choices: From next-generation public transport mode choice to HOT lanes. (July 2017) - Lahlou, Salem; Wynter, Laura
Highlights: A tradable credits scheme for incentivizing transport choices in a binary atomic game framework is proposed. We prove that the game admits a potential function, and that efficient Nash equilibria exist and can be reached using standard learning algorithms. We show how the properties of the equilibria can be controlled by the transport authority through appropriate parameter tuning. Abstract: We consider a tradable credits scheme for binary transport games where one option is faster (or more comfortable) than the other, but its quality of service suffers when usage is high. Applications can be found in mode choice (public transit versus road transport), premium (i.e., express bus) versus ordinary public transit, and fast (e.g., high-occupancy toll, or HOT) versus regular lanes on expressways. We are motivated in particular by the choice between public transport and use of the road network as a privilege to be discouraged. In a future where GPS-based time-distance-place road charging exists, such next-generation transport management strategies become realizable as the choice to drive or not can be linked to a fixed fee toll, or indeed to a tradable credits scheme. When public transport payment uses the same smart card as the road usage fee (via tolls or tradable credits) usage of the two may be linked. In this setting, a public transport vs. road-use tradable credit scheme becomes feasible. In this case, individuals wishing to choose the faster option must obtain credits from other commuters via credit trading, rather than pay a direct toll or fee. Such a scheme creates a kind of equity, in the sense that lower-income commuters have an economic incentive to resort to the slower or less comfortable choice. We study the underlying market and its effects on individuals' utilities; we use an atomic game framework so as to model explicitly the exchange process across users. The market we define determines the quantities of users choosing each option, as opposed to the prices themselves. Using the properties of potential games, we show that under mild assumptions, efficient Nash equilibria exist and can be reached using simple learning algorithms. We show that these equilibria can satisfy the transport authority's requirements, and thus drive the transport system to a state where a desired proportion of individuals resort to each of the two options, when the scheme's parameters are well tuned.