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Promoting zero-emissions vehicles using robust multi-period tradable credit scheme

机译：运用稳健的多期可交易信贷计划推广零排放汽车

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This study designs a robust multi-period tradable credit scheme (TCS) to incentivize travelers to shift from internal combustion engine vehicles (ICEVs) to zero-emissions vehicles (ZEVs) over a long-term planning horizon to reduce vehicular emissions. The need for robust design arises because of uncertainty in forecasting travel demand over a planning horizon in the order of several years. The robust multi-period TCS design is formulated as a bi-level model. In the upper level, the central authority (CA) determines the TCS parameters (credit allocation and charging schemes) by vehicle type to minimize the worst-case vehicular emissions rate, i.e. the maximum vehicular emissions rate under the possible travel demand scenarios. The upper-level model is a mixed-integer nonlinear program. In the lower level, travelers minimize their generalized travel costs under the TCS parameters obtained in the upper level. These parameters are used to determine the vehicle type choice, between ICEVs and ZEVs, using a binomial logic function, and influence route selection based on the difference in credits charged on links for these two vehicle types. The lower-level model is a mathematical program with equilibrium constraints. The bi-level model is solved using a cutting plane method. Numerical experiments illustrate that the incentive to shift to ZEVs is fostered by allocating more credits and charging fewer credits to ZEV travelers compared to ICEV travelers. Further, the proposed TCS design reduces volatility in the realized vehicular emissions rates under different travel demand scenarios compared to a TCS design that does not consider demand uncertainty.
机译：这项研究设计了一个强大的多时期可交易信贷计划（TCS），以激励旅行者在长期规划的范围内从内燃机车辆（ICEV）转向零排放车辆（ZEV），以减少车辆排放。由于在数年左右的计划范围内预测旅行需求的不确定性，因此需要强大的设计。健壮的多周期TCS设计被表述为双层模型。在上层，中央机构（CA）通过车辆类型确定TCS参数（信贷分配和收费方案），以使最坏情况下的车辆排放率（即在可能的出行需求情景下）的最大车辆排放率最小化。上层模型是混合整数非线性程序。在较低级别中，根据在较高级别中获得的TCS参数，旅行者将其一般旅行费用降至最低。这些参数用于使用二项式逻辑函数确定ICEV和ZEV之间的车辆类型选择，并根据这两种车辆类型的链接所收取的积分差异来影响路线选择。下层模型是具有平衡约束的数学程序。使用切割平面方法求解双层模型。数值实验表明，与ICEV旅行者相比，向ZEV旅行者分配更多的积分和向ZEV旅行者收取较少的积分可以促进转向ZEV的动机。此外，与不考虑需求不确定性的TCS设计相比，拟议的TCS设计降低了在不同出行需求场景下已实现的车辆排放率的波动性。

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