This EArly-Concept Grant for Exploratory Research (EAGER) collaborative research project will explore a new and promising travel demand management strategy, inspired by various cap-and-trade schemes aiming to reduce greenhouse gas and air pollutant emissions. Traffic congestion continues to threaten the economic prosperity and quality of life around the world. It is widely acknowledged that demand management strategies could help alleviate traffic congestion, and if properly implemented, they could be effective and cost-efficient. The cap-and-trade schemes considered in this research seek to couple direct travel demand restrictions with a trading mechanism. Because such a scheme typically involves creating mobility credits and trading them in a market, it is also known as a tradable credit scheme. As an early exploration of this idea, the project will directly involve economists that will provide input to each research task and as part of the research analytical tools to answer critical design and implementation issues will be sought. Agent-based simulation will be used as the main evaluation tool for the proposed analytical framework and design concepts. Based on this simulation platform, the research will compare tradable credit schemes with traditional travel demand management strategies such as congestion pricing, and validate the effectiveness and practicability of the proposed schemes with varying behavioral travel assumptions.
If successful, the project could provide a meaningful bridge between transportation and economics on the issue of cap-and-trade and research findings would be shared to advance both fields. The work could shift the current paradigm associated with traffic congestion management policies. The findings from this research could also enhance choices among these policies and help provide for their prioritization. Accordingly, the research will be incorporated in education activities at both universities by offering new materials and case studies within the transportation curricula. Finally, research results will be broadly disseminated through a variety of media.
Traffic congestion continues to threaten economic prosperity and quality of life around the world. It is widely acknowledged that demand management is an indispensable ingredient in the recipe for solving the traffic congestion puzzle, and likely to be one of the more effective and cost-efficient if properly implemented. This research explores a new and promising travel demand management strategy, inspired by various cap-and-trade schemes aiming to reduce greenhouse gas and air pollutant emissions. The cap-and-trade schemes considered in this research seek to couple direct travel demand restriction with a trading mechanism. Because such a scheme typically involves creating mobility credits and trading them in a market, it is also known as tradable credit scheme. Broader impacts The project supplements the current paradigm of thinking in travel demand management with the idea of tradable credit schemes. It forges the collaborations between two fields, namely transportation systems and economics, on the subject of travel demand management in general and tradable credit scheme in particular. The project not only led to a successful workshop participated by economists, transportation researchers, and local practitioners, but also produced joint work involving economists. The project influences transportation systems education programs at two major research universities by offering fresh materials and case studies to expand their curricula. Intellectual Merits The proposed project develops analytical tools to address several critical design and implementation questions regarding tradable credit schemes. The main results are summarized below. The project proposes and analyzes a new tradable credit scheme that rewards only those who contribute to congestion relief (e.g. by choosing transit or traveling during off-peak time) with mobility credits. The analyses indicate that very simple designs of the scheme could reduce congestion significantly, and properly distribute the benefits among all the commuters through the credit trading. The project develops several new numerical methods for solving both descriptive and prescriptive models of morning commute problem with heterogeneous users. These tools can be used to evaluate how a given travel demand management scheme might impact the welfare of individual users, and to design optimal congestion pricing or tradable credit schemes. The project conducts a hypothetical case study built upon empirical data from Florida to compare socioeconomic impacts of gasoline tax, mileage fee and tradable mobility credits or permits for regulating the vehicle miles traveled in Florida. It also compares congestion pricing and tradable credit schemes in managing network mobility under demand or supply uncertainty. The project analyzes tradable credit schemes on networks with two types of players, namely, a finite number of Cournot-Nash players and an infinite number of (infinitesimal) Wardrop-equilibrium players. The former are transportation and logistics companies while the latter are individual travelers. Both types of players exist in the real world and hence should be considered in designing a tradable credit scheme. The project also explores a couple of applications of tradable credit schemes, including replacing congestion pricing with parking permits reservation, and implementation of staggered work times (in which firms receive mobility credits to trade-off their workers’ travel delays and productivity losses).
