EAGER/Collaborative Research: Towards Dynamic Social Ride-sharing: An Essential Component in Envisioned Smart Communities

先前的工作已经证明了共享出行的潜在经济和环境效益；然而，拼车并没有被大多数旅行者所接受，因为之前的努力旨在最大化参与者的数量，而没有考虑到旅行者的社会属性。提倡共享出行的主要挑战之一是如何减少社会障碍。利用信息技术和社交媒体的进步来建设智慧社区，随着社会对出行行为的态度逐渐形成，拼车及其社会体验应该被视为智慧社区中可行的、可能占主导地位的交通方式。这个早期概念的探索性研究资助（EAGER）项目将解决目前拼车的社会障碍，并将提供更有吸引力的拼车匹配，从而提高用户参与度。虽然用户可能会容忍旅行时间的轻微妥协，以换取更好的社交体验，但社交拼车的规模经济将导致智能城市和社区交通系统的更好表现。该项目将支持实现社会乘车共享系统，该系统可以用于验证部署社会交通的长期研究目标。本研究的目的是为支持社交拼车提供理论基础。用户的社会属性和偏好将由两种创新模式共同决定：空间活动模式和社会活动模式。建立概率位置聚类模型，识别异常非通勤出行的空间活动模式。该项目利用关键词搜索方法和主题识别来估计旅行者的社会活动和社会活动模式的旅行目的。将开发新的优化模型，用于从社交媒体和乘车共享数据中估计旅行模式，包括使用最先进的矩阵估计技术来推断旅行模式的各个方面，例如按类型，一天中的时间，每周中的哪一天等进行常规和特殊模式（异常）旅行。这一步特别具有创新性，因为这些估算方法是交通领域的新方法，它们的成功应用将有利于研究界。以最大化乘客满意度和出行效率为目标，发展社会化拼车的新理论。一个生活实验室将与当地实体合作，展示研究产品的试点实施。

Prior work has demonstrated the potential economic and environmental benefits of ride-sharing; however, ride-sharing has not been adopted by the majority of travelers, since previous efforts aimed to maximize the number of participants but failed to take travelers social attributes into account. One of the major challenges in advocating ride-sharing is how to reduce social barriers. Taking advantage of advances in information technology and social media for building smart communities, and with emerging social attitudes regarding travel behavior, ride-sharing along with its social experience should be considered as a viable and possibly dominant mode of transportation in smart communities. This EArly-concept Grant for Exploratory Research (EAGER) project will address the current social barriers to ride-sharing and will provide more appealing ride matches leading to increased user participation. While a slight compromise in travel time may be tolerated by users in exchange of better social experience, the economy of scale in social ride-sharing would result in better performance of transportation systems in smart cities and communities. The project will support the realization of asocial ride-sharing system that can serve in validating the long-term research goals of deploying Social Transportation. The goal of this research is to develop theoretical foundations for supporting social ride-sharing. Users social attributes and preferences will be jointly determined by two innovative patterns: the spatial-activity pattern and the social-activity pattern. A probabilistic location clustering model will be built to identify abnormal non-commuting travels for the spatial-activity pattern. This project leverages a key word-search approach and topic recognition to estimate travelers social activities and travel purposes for the social-activity pattern. Novel optimization models for estimation of travel pattern from social media and ride-sharing data will be developed, to include using state-of-the-art matrix estimation techniques to infer various aspects of travel pattern, such as regular and special-pattern (anomalous) trips by type, time of day, day-of-week, etc. This step is particularly innovative in that these estimation methods are new to the transportation field, and their successful application would be beneficial to the research community. New theory will be developed for social ride-sharing in maximizing both riders satisfaction and trip efficiency. A living lab will be used in collaboration with local entities to demonstrate the pilot implementation of the research product.