A System Dynamics Approach To Policy Assessment For Transporation System And Case Study

"How to use policy guide transportation develop in a rational trend", the issue has always been the hot topic in government policy makers and academic research institutions. But we cannot just stay in the decentralization level to predict and evaluate the effect when the "most likely" policy is implemented. Research on advanced theory and methodology tools for policy support is necessary. In this paper, a system dynamics model is developed to simulate private car development, energy consumption and emission in China and Beijing under different policy scenarios. The model is designed to perform what-if analysis, allowing users to enter their own policy choices and assumptions and quickly generate results.By carding the basic ideas of current policies, two approachs is developed to solve the problem"How to use policy guide private car develop in a rational trend".(1) Correctly guiding the private car purchase.(2) Correctly guiding the private car usage. Literature review shows that:current transporation model research lacks the feedback between transports other factors. We select system dynamics method to make improvement. Literature review on system dynamics models shows that:current models are too simplicisy to solve our problem, many important indicators are exogenous variables, so the feedback loops between population, economy, environment, and transportation is lacked. We built a SD model which includes over20thousands variables to endogenous compute these variables and made these endogenous variables quantitative linked by a lot of feedback loops.This paper aimed at the key problem of policy-making., built SD model to cope with complex scenario analysis of transportation in China and Beijing. As the influence of multifactor on private ownership and usage should be analyzed from an integration perspective in a complex system, the model was divided into four sub modules: population, economic, transportation, and environment, and these modules are linked by a lot of feedback loops. The model endogenously simulates dozens of key variables from1990-2050, including the private car ownership, private car sales, private car scrappage, private car age cohorts, private car ownership and sales by different price scales, private car energy consumption and emission. To prove the reliability of this model, the simulate variables are compared with history data from1990to2013. The model is designed to do what-if analysis, allowing users to enter his/her own policy choices and assumptions, then quickly generating results. The policy suggestion based on the simulation results is recommended in this paper. For China,(1) high price large cars will develop dramatically in new car sales market. The car’s price which between100K to160K will dominate the new car sales market in2017. In2026, the car’s price which between160k to230k will dominate the new car sales market;(2)the renewable energy cars will not step into the mainstream market according to existing subsidies in the short term. The burden of energy consumption and emission reduction will shouldered by traditional gasoline car fuel efficient technology development;(3)More financial ways of support are needed to use as renewable cars subsidies. Considering the amount of energy saving and CO2emission reduction, the cost of subsidies on renewable energy cars will benefit China a lot in mid and long term. For Beijing,(1) other auxiliary policies must be considered besides the vehicle purchase restriction policy;(2) scrappage will increase rapidly during2011-2020(12th and13th five-year plan period);(3) the concept of trip mode should be changed by residents to reduce the car trips in Beijing.In the end, the paper concludes that:(1) the influence of multifactor policy on private ownership and usage should be analyzed from an integration perspective in a complex system which enclude population, economy, environment and transportation;(2) causal loop diagram by feedback loops and delay analysis by stocks and information and material delay functions are important tools for system thinking, so the population, economy, environment and transportation should be specialized modeled and linked together;(3) discovering the decision rules of the policy makers in a system and representing them in model is challenging and requires skillful combination of theory, experiment, and observation.While there are many theories about the degree of sophistication and rationality of human decision, all models must conform to basic principles, and all equations must be dimensionally consistent without the use of arbitrary factors with no real world meaning.