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A ridesplitting market equilibrium model with utility-based compensation pricing
Transportation ( IF 4.3 ) Pub Date : 2022-09-28 , DOI: 10.1007/s11116-022-10339-z
Qing-Long Lu , Moeid Qurashi , Constantinos Antoniou

The paper develops a theoretic equilibrium model for ridesplitting markets with specific considerations of origin-destination demand patterns, competition with other transport modes, characteristics of en route matching, and spatial allocation of ridesplitting vehicles, to adequately portray the intertwined relationships between the endogenous variables and decisions. The operation property of the market under distance-based unified pricing is analyzed through the response of system performance indicators to the decisions. Moreover, a gradient descent algorithm is derived to find optimal operating strategies in the monopoly scenario and social optimum scenario. Leveraging the tight connection between trip’s utility and level of service (LoS), the paper then proposes a utility-based compensation pricing method to alleviate the inequity issue in ridesplitting, which results from the variance in waiting time and detour time and the implementation of unified pricing. Specifically, the trip fare of those with an initial utility smaller than a threshold will be compensated following a predefined compensation function. We compare its effectiveness and influence in different scenarios through numerical experiments at Munich. The results show that the proposed pricing method can improve the LoS and equity without losing any profit and welfare, and can even achieve increments in maximum profit and social welfare under certain conditions.



中文翻译:

基于效用补偿定价的拼车市场均衡模型

本文建立了拼车市场的理论均衡模型,具体考虑了起点-目的地需求模式、与其他交通方式的竞争、途中匹配的特征以及拼车车辆的空间分配,以充分描绘内生变量与决定。通过系统性能指标对决策的响应,分析了基于距离的统一定价下市场的运行特性。此外,还导出了梯度下降算法以在垄断场景和社会最优场景中寻找最优运营策略。利用旅行的实用性和服务水平 (LoS) 之间的紧密联系,然后,本文提出了一种基于效用的补偿定价方法,以缓解因等待时间和绕行时间的差异以及统一定价的实施而导致的拼车中的不公平问题。具体而言,初始效用小于阈值的人的行程费用将按照预定义的补偿函数进行补偿。我们通过慕尼黑的数值实验比较了它在不同场景下的有效性和影响。结果表明,所提出的定价方法可以在不损失任何利润和福利的情况下提高LoS和公平性,在一定条件下甚至可以实现最大利润和社会福利的增量。那些初始效用小于阈值的人的行程费用将按照预定义的补偿函数进行补偿。我们通过慕尼黑的数值实验比较了它在不同场景下的有效性和影响。结果表明,所提出的定价方法可以在不损失任何利润和福利的情况下提高LoS和公平性,在一定条件下甚至可以实现最大利润和社会福利的增量。那些初始效用小于阈值的人的行程费用将按照预定义的补偿函数进行补偿。我们通过慕尼黑的数值实验比较了它在不同场景下的有效性和影响。结果表明,所提出的定价方法可以在不损失任何利润和福利的情况下提高LoS和公平性,在一定条件下甚至可以实现最大利润和社会福利的增量。

更新日期:2022-09-30
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