Incentive-based Travel Behavior Change Mechanisms to Mitigate System-Level Greenhouse Gas Emissions

Passenger car travel is one of the largest contributors to greenhouse gas emissions in the United States. Given climate change concerns, reducing greenhouse gas emissions associated with passenger car travel is crucial and urgent. Two important factors that affect car emissions are: (i) vehicle specific characteristics such as the weight, age, and fuel efficiency of the vehicle, and (ii) trip characteristics such as distance driven and traffic conditions (i.e., frequency of acceleration and braking). Reducing these emissions can be achieved by promoting sustainable travel choices using various behavior change strategies. Traditionally, behavior change strategies have focused on shifting users to transit or active travel modes. Limited research has been conducted to understand the potential reduction in system-level emissions by switching users to more eco-friendly routes (characterized by lower greenhouse gas emissions). To address this gap, this study designs a smartphone application-based incentive framework to nudge users to switch to eco-friendly routes through a combination of monetary and non-monetary incentives. Monetary incentives in this study are designed to be present on every road, are budget constrained, and the exact value of the incentives is dependent on system-level greenhouse gas emissions. To model this, a bi-level transportation network design problem that optimizes for the system-level greenhouse gas emissions is utilized. In the upper-level problem, a multi-objective optimization model is used to minimize the total system greenhouse gas emissions with the quantity of monetary incentives on a road as its decision variables. The lower-level problem solves for user equilibrium that describes network performance based on individual behavior under monetary and non-monetary incentives. Numerical experiments are conducted on networks of different sizes (Sioux Falls and Chicago Sketch) and using different demand patterns. These experiments seek to assess the impacts of the proposed incentive framework on the spatial distribution of vehicles and to estimate the cost of implementing such mechanisms at a network level. Further, they aim to analyze the efficacy of using mobile apps to deliver monetary and non-monetary incentives on system-level greenhouse gas emissions.