Optimizing a link-based travel incentive scheme integrating personal carbon trading for low-carbon commuting

The pressing need to reduce greenhouse gas emissions and optimize traffic demand underlines the importance of effective travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which diminish a heavy financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters using low-carbon travel routes. The revenue obtained from the sale of carbon emission reductions, resulting from changes in commuter routes, serves as a partial budget for the incentives under PCTTI. To determine the optimal incentives, we developed an incentive scheme optimization model based on a bi-level programing model. Numerical analysis reveals the substantial potential of PCTTI to reduce carbon emissions and travel costs in the road traffic system, but also highlights the sensitivity of these results to the carbon trading price and the commuters' value of time. Specifically, the effectiveness of PCTTI diminishes when the carbon price drops below $6.494 per ton or when commuters' value of time exceeds $3.99 per hour. These results indicate that the PCTTI mechanism offers a scalable and economically sustainable approach to enhance travel demand management and achieve environmental benefits.