Design of a heuristic environment-friendly road pricing scheme for traffic emission control under uncertainty.


MOE (Ministry of Education) Key Laboratory for Transportation Complex Systems Theory and Technology, Institute of Transportation System Science and Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China. Electronic address: [Email]


Road transportation is one of the main sources of atmospheric emissions in many countries and areas. Road pricing, is not only effective for urban transportation management, but also helpful in reducing the negative externalities caused by transportation. In this study, an inexact two-phase minimal emission programming (TMEP) model is proposed for design of the environment-friendly toll scheme with an acceptable road network performance. Through introduction of fuzzy stochastic programming, multiple uncertainties involved in vehicle emission evaluation are dealt with; the Traffic Performance Index (TPI) based constraints are incorporated to reflect the decision-maker's requirements for network congestion management. The solution method is proposed for generating the range of fuzzy stochastic objectives. An optimal toll scheme associated with the minimal emission based flow pattern is obtained through searching for a set of the best and the worst optimal solutions. A numerical experiment and a real-world road network in Beijing of China are used to illustrate the application of the developed method. In the case study, the toll scheme is obtained at the desired congestion level. The effects of emission and congestion abatement are analyzed under different policy scenarios. The proposed TMEP method can generate the toll scheme with obvious improvements in total emission reduction and congestion mitigation.


Emission uncertainty,Fuzzy-random variable,Road pricing,Traffic performance index,