Due to the large number of motor vehicles in urban road networks, serious traffic congestion and high proportion of road carbon emissions, failure to take effective measures to manage travel demand will result in waste of road resources and environmental pollution. Considering the complex variability of the actual road network and the heterogeneous characteristics of road travelers, this paper proposes a dynamic traffic network allocation model in the context of carbon trading. The model is a dual dynamic day-by-day model, which considers both the dynamic changes of road network traffic and the dynamic adjustment and changes of carbon quota consumption rate. After 600 days of dynamic evolution, the road network reaches the system optimal state while achieving user equilibrium. Meanwhile, the carbon emission reduction on the road transport network before and after the implementation of carbon trading scheme is compared and analyzed, and the overall carbon emission is reduced by 9.23%. This provides a scientific theoretical basis and a feasible solution for the carbon trading scheme in urban transportation demand management and guiding low-carbon travel.
To evaluate the environmental benefits and operating efficiency of exit lanes for left-turn intersections, a signal optimization model considering emissions and delays is proposed. Considering the three pollutants of CO, HC, and NOx in cars and buses exhaust, VISSIM simulation software is used to obtain second-by-second data of vehicles. The data is used to calculate the second-by-second Vehicle Specific Power and to calibrate the two types of emission factors for each lane group. Cycle length, main-signal and pre-signal control are regarded as constraints, and minimum emissions and delays are regarded as optimization goals. The bi-objective optimization for exit lanes for left-turn intersections is transformed into a single-objective optimization problem through the linear weighted sum method, and the genetic algorithm is used to solve the optimal signal timing scheme. The results show that, compared with conventional intersections, the design of EFL intersections can not only improve operation efficiency, but also reduce emissions. The optimal signal timing scheme for exit lanes for left-turn intersection can reduce the delay by 6.27% and the total emissions by 7.47%; At the same time, when the proportion of left-turn traffic is 35%~40%, the signal optimization model proposed in this paper has the best optimization performance. Effective in relieving traffic pressure and has good environmental benefits.
Considering the subway, private cars, and cycling, the Personal Mobility Carbon Credits Trading scheme is explored in a super network with homogeneous travelers to discuss the impact on travel mode split rate and system carbon emissions. The Personal Mobility Carbon Credits Trading scheme includes the travel route choice behavior and the dynamic credits price evolution, which affect each other. The former is modeled in a super network. The Dial-MSA algorithm is used for flow distribution, and the results are fed back to the dynamic credits price evolution model. Accordingly, the result of dynamic credits price evolution, in turn, affects travel cost and finally governs the result of traffic flow allocation. The results show that the system will reach a stable state in a finite time range. The convergent equilibrium price has nothing to do with the initial price but is related to the number of total credits and the credits allocation scheme. Compared with the equivalent distribution scheme, proportional distribution is more equitable.
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