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Tradable Mobility Credits and Permits: Shaping the Future of Urban Transportation

Currently, travelers don’t use public transportation systems as efficiently as they could. To fix this problem, strategies have been developed that aim to manage the demand for transportation in a way that spreads out the number of people using it, at different times and across different modes of transportation. The goal is to use the transportation infrastructure in the best way possible and reduce negative effects such as traffic congestion, economic losses, energy consumption, and pollution.

One approach to demand management is called Tradable Credit and Permit Schemes (TCS/TPS). TCS/TPS are demand management policies in which the authority sets a cap on access to the transportation network. Each traveler receives an initial allocation for free and can freely trade it with the other travelers. The market regulates the price to pay to travel on a given route at a given time with a given mode. Unlike congestion pricing, there is no flow of money from the travelers to the authority, i.e. no tax is collected.

The DIT4TRAM report is a review of different research on TCS/TPS and suggests future research directions. The report specifically focuses on how to incorporate multiple modes of transportation, shared mobility services, and different representations of traffic congestion.

State of the art

By reviewing the existing literature, we first noticed that the definitions of credits and permits are not consistent across all the contributions. We, therefore, propose to draw the following line between credit and permit: a credit is universal, in the sense that one cannot differentiate two credits as they have the same value and purpose. Conversely, a permit is specific to a time slot and a link. There is one market for a TCS, whereas for a TPS there are as many markets and prices as different types of permits. We schematically summarize the TCS/TPS frameworks in the image below.

The amount of scientific attention devoted to TPS is significantly lower than for TCS. One could argue that TPS are disadvantageous because they require a multitude of permits, which makes acquisition and trading mechanisms arguably hard to implement. In a TCS, the authority does not choose which alternative is more expensive than another by setting the credit charges for the different options. In a TPS, it only decides on the number of permits to be issued. The first gap we identified is the representation of the congestion. The second limitation is the restriction of most studies to transportation by private cars. Some papers account for public transportation as an alternative and several recent contributions consider mobility-on-demand concepts (e.g., carpooling).

What should future research study?

After reviewing the literature about TCS/TPS, we identified two major research directions: the congestion representation and the integration of different transportation modes. Those aspects are either no present or under-represented in the current state-of-the-art, while we believe they are necessary to design and forecast the effects of comprehensive tradable credit and permit schemes as a policy measure.

To address the first point, we identify two potential solutions: working with the Macroscopic Fundamental Diagram (MFD) to account for congestion dynamics at a large urban scale and feed analytical discussions, and using a traffic simulator to estimate the impact of TCS/TPS under complex configurations. The multimodal aspect of the transportation networks and especially the integration of the on-demand mobility forms are lacking in the current literature. Ride-hailing and ride-pooling might foster the reduction of personal car usage as it provides a solution to reach destinations not covered by public transports. However, at the same time, they might increase the congestion with empty vehicles driving without passengers between two locations.

The DIT4TraM project aims to revolutionize traffic and mobility management by using swarm intelligence and self-learning systems. One of its goals is to develop decentralized demand management strategies for Amsterdam, The Netherlands. This includes the conceptual and algorithmic design of TCS/TPS, which will be evaluated for their effectiveness in reducing congestion and promoting sustainable transportation.

Read the full report in Downloads section or following this link.