With the improvement of China’s carbon emission trading system, the spillover effect between carbon and energy markets is becoming more and more prominent. This paper selects four representative pilot carbon markets, including Beijing (BEA), Guangdong (GDEA), Hubei (HBEA) and Shanghai (SHEA). And three representative energy markets, including Crude Oil Futures (SC), power index (L11655) and China Securities new energy index (NEI). Combining the rolling window technology with DY spillover index, set a 50-weeks rolling window to measure the spillover index, and deeply analyze the time-varying two-way spillover effect between China’s carbon and energy markets. The results show that the spillover effect between China’s carbon and energy markets has significant time variability and two-way asymmetry. The time-varying spillover effect of different carbon pilot markets on the energy market has regional heterogeneity. The volatility spillover effect of Beijing and Shanghai carbon markets mainly comes from the crude oil futures market, Guangdong carbon market mainly comes from the new energy market, and Hubei carbon market mainly comes from crude oil and electricity market. The above research results contribute to the prevention of potential risk spillover between carbon and energy markets, which can promote the establishment of China’s unified carbon market and the prevention of systemic financial risks in energy market.
In order to alleviate the problem of the oversaturation of intersections, a traffic control method using a main-signal and pre-signals to periodically control the direction of dynamic waiting lanes was proposed in this paper. Based on the research on vehicle delay at intersections with dynamic waiting lanes and constraint relationships among a set of timing elements of the main-signal and pre-signal, a coordinated control model of a main-signal and pre-signal was built to minimize the average delay. Finally, a case study was performed to show that the proposed model is feasible. The objective optimization was performed by using a genetic algorithm to determine the main-signal and pre-signal timing scheme of the case study intersection, and then the average delay before and after installing dynamic waiting lanes was calculated and analyzed. The proposed method was found to be effective in reducing the intersection delay by 31.8% compared with the present situation of the intersection. Subsequently, the traffic volumes in the directions with dynamic waiting lanes installed were changed. It was demonstrated that with increasing traffic volumes, the effectiveness of the model to reduce intersection delay would be significant.
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