Intercity travel congestion during the main national holidays takes place every year at different places around the world. Charge reduction measurements on existing toll roads have been implemented to promote an efficient use of the expressways and to reduce congestion on the public transit networks. However, some of these policies have had negative effects. A more comprehensive understanding of the determinants of holiday intercity travel patterns is critical for better policymaking. This paper aims to investigate the effectiveness of the road toll discount policy on mode choice behavior for intercity travel. A mixed logit model is developed to model the mode choices of intercity travelers, which is estimated based on survey data about intercity journeys from Beijing during the 2017 Chinese Spring Festival holiday. The policy impact is further discussed by elasticity and scenario simulations. The results indicate that the expressway toll discount does increase the car use and decrease the public transit usage. Given the decreased toll on expressways, the demand tends to shift from car to public transit, in an order of coach, high-speed rail, conventional rail, and airplane. When it comes to its effect on socio-demographic groups, men and lower-income travelers are identified to be more likely to change mode in response to variation of road toll. Finally, policy effectiveness is found to vary for travelers in different travel distance groups. Conclusions provide useful insights on road pricing management.

The implementation of expressway toll-free policy during holidays in China has caused serious congestion and frequent accidents on expressways. Many studies have explored the policy's macroscopic outcome and its countermeasures for policy managers, while limited attention has been paid to the influence mechanism of the policy on the individuals' travel behavior, especially the mode choice behavior. More insight into the dynamic effects of individuals reacting to policy measure is needed. This study aims at analyzing the adaption progress of the individual's mode choice behavior and estimating the time-varying influence of the traffic policy on the mode split. With assumptions travelers' adapting behavior conform to the inertia and myopia principles, a Logit dynamic evolutionary model for mode choice is proposed. A unique globally stable equilibrium state for the model is derived with the strict mathematical analysis. As an application, the influence of the expressway toll-free policy on mode split is evaluated. The travel cost structure, the sensitivity of the travel distance and traffic supply, and the evolutionary dynamics of the mode split are analyzed in scenarios with and without the expressway toll-free policy. The result indicates that travel distance and network's total supply amount remarkably affect the implementation effect of the policy.

China is one of the biggest energy consumers and carbon emitters in the world. Understanding the factors affecting carbon emissions is critical for policymakers to control the rising trend of carbon emissions. This paper investigates the relative importance of carbon emissions drivers in China. Literature review has been carried out to determine a set of predominant independent variables; the LASSO model is then introduced to rank the relative importance among the set of independent variables. The results find that 1) carbon emissions were mainly driven by economic growth and energy consumption followed by population size and industrialization; and 2) income growth slowed down carbon emissions during the studied period, but it is the least significant factor among the other factors. The ranking allows policy makers to focus on the most critical contributors to carbon emissions and gives policymakers more flexibility in determining policy interventions.