风险感知视角下弹性停车激励机制泊位定价方法

以弹性停车激励机制为背景，应用条件风险价值函数刻画个体共享泊位的风险感知特征，提出基于风险感知收益最优的泊位定价方法，探究共享停车供需关系对最优租赁价格的影响规律，并以美国加州大学伯克利分校为例，灵敏度分析各关键参数对共享停车政策效能的正负导向效用。研究表明：基于风险感知收益最优的泊位定价方法能根据外部停车需求约束差异寻找出适度的“竞争性”价格，在确保停车泊位有效利用的同时，引导个体积极参与泊位共享过程，避免因损失厌恶情绪影响弹性停车激励机制的顺利推行。泊位的最优租赁价格将随着停车场回收情况而有所波动，若回收的共享泊位数量过多，该方法则倾向于提高租赁价格，以对冲回收成本；反 之，会以牺牲部分停车场利润为代价，设定较低的租赁价格，保障共享泊位的利用效率。

Parking Pricing Method Based on Flexible Parking Incentive Mechanism and Risk Perception

This paper applies the flexible incentive parking mechanism to optimize the parking prices and uses the function of conditional value at risk to describe the risk perception characteristics of individual shared parking spaces. The study explores the influence of supply-demand relationship on the optimal rental prices of shared parking spaces, and takes the University of California, Berkeley as an example to analyze the positive and negative guiding effects of key parameters on the efficiency of shared parking policy. The results show that the parking pricing method based on the optimal risk perceived returning can find the appropriate "competitive" price in response to the difference of external parking demand constraints. The optimal pricing ensures the effective use of parking spaces, encourages the individual to actively participate in the shared parking process and avoids the impact of loss aversion on the implementation of flexible parking incentive mechanism. The optimized rental price of parking spaces would have some fluctuations when some parking spaces no longer open to the public. If the shared parking spaces decreased significantly, this method tends to increase the rental price to balance the cost and benefit. On the contrary, the method would suggest reducing some profits of parking spaces and setting a relatively lower rental price to maintain a good utilization efficiency of shared parking spaces.