Ridesharing is the sharing of trip segments from one place to another among multiple travelers, obviating others’ needs to drive themselves. By having more than one occupant sharing a vehicle, ridesharing aims to reduce personal resources and costs, such as fuel and trip-related costs, and driver stress. The objective of this paper is to model the social preferences of rideshare passengers. We identify challenges and barriers people face in ridesharing with respect to whom they share the ride with and model these social preferences to determine the probability of matching for rideshare demand forecasting. An online survey instrument was designed and distributed among the people residing in the United States to uncover their preferences for ridesharing, in addition to the attributes of potential rideshare passengers. Furthermore, using the survey data, a discrete choice model with latent variables was estimated to uncover the relationship between social preferences and matching. We identified 13 attitudinal dimensions characterizing social preference from the survey responses. These 13 variables were further distilled into four latent variables using factor analysis. Four models were estimated for each latent dimension to predict the probabilities of a person pleasantly experiencing his/her shared rides in social aspects from his/her attributes and preferences. Based on the estimated choice model, we developed a matching index derived from preference probabilities that give a compatibility ratio between riders.

中文翻译：

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在拼车匹配中理解和建模乘客的社会偏好

拼车是在多个旅行者之间共享从一个地方到另一个地方的旅行段，从而避免了其他人自己开车的需要。通过让多个乘客共享一辆汽车，拼车旨在减少个人资源和成本，例如燃料和旅行相关成本以及驾驶员压力。本文的目的是对拼车乘客的社会偏好进行建模。我们确定人们在拼车中面临的挑战和障碍，以及他们与谁拼车，并对这些社会偏好进行建模，以确定拼车需求预测的匹配概率。一个在线调查工具被设计并分发给居住在美国的人，以揭示他们对拼车的偏好，以及潜在拼车乘客的属性。此外，使用调查数据，估计具有潜在变量的离散选择模型，以揭示社会偏好与匹配之间的关系。我们从调查回复中确定了表征社会偏好的 13 个态度维度。使用因子分析将这 13 个变量进一步提炼为四个潜在变量。为每个潜在维度估计了四个模型，以根据一个人的属性和偏好来预测一个人在社交方面愉快地体验他/她的共享骑行的概率。基于估计的选择模型，我们开发了一个匹配指数，该指数源自偏好概率，给出了乘客之间的兼容性比率。我们从调查回复中确定了表征社会偏好的 13 个态度维度。使用因子分析将这 13 个变量进一步提炼为四个潜在变量。为每个潜在维度估计了四个模型，以根据一个人的属性和偏好来预测一个人在社交方面愉快地体验他/她的共享骑行的概率。基于估计的选择模型，我们开发了一个匹配指数，该指数源自偏好概率，给出了乘客之间的兼容性比率。我们从调查回复中确定了表征社会偏好的 13 个态度维度。使用因子分析将这 13 个变量进一步提炼为四个潜在变量。为每个潜在维度估计了四个模型，以根据一个人的属性和偏好来预测一个人在社交方面愉快地体验他/她的共享骑行的概率。基于估计的选择模型，我们开发了一个匹配指数，该指数源自偏好概率，给出了乘客之间的兼容性比率。为每个潜在维度估计了四个模型，以根据一个人的属性和偏好来预测一个人在社交方面愉快地体验他/她的共享骑行的概率。基于估计的选择模型，我们开发了一个匹配指数，该指数源自偏好概率，给出了乘客之间的兼容性比率。为每个潜在维度估计了四个模型，以根据一个人的属性和偏好来预测一个人在社交方面愉快地体验他/她的共享骑行的概率。基于估计的选择模型，我们开发了一个匹配指数，该指数源自偏好概率，给出了乘客之间的兼容性比率。