时 间：6月14日上午10点半
腾讯会议号：159-441-111
地 点：九里校区零号楼0411室（听众）
主 题：Passenger Mobility Analysis based on Car-hailing Platform Data and Artificial Intelligence Algorithms
内 容：The ride-hailing service platforms have grown tremendously around the world and attracted a wide range of research interests. This talk will introduce some recent progress we have made on two key issues of ride-hailing service: demand forecasting and order matching. A key to ride-hailing service platforms is how to realize accurate and reliable demand prediction. However, most of the existing studies focus on the region-level demand prediction while only a few attempts to address the problem of origin-destination (OD) demand prediction. In our recent studies, from the graph aspects, we construct the dynamic OD graphs to describe the ride-hailing demand data. We propose two novel neural architectures named the Dynamic Node-Edge Attention Network (DNEAT) and the Dynamic Auto-structuring Graph Neural Network (DAGNN) to address the unique challenges of OD demand prediction from the demand generation and attraction perspectives. Online matching between idle drivers and waiting passengers is another key component in a ride-sourcing system. We proposed two ideas to improve the matching efficiency: early driver matching and delayed passenger matching. The first idea considers the vehicles whose destinations are close to the passenger’s origin, then the passenger’s waiting time may be shorter, and the vehicle’s pick-up distance and fuel consumption can be saved. The second one assumes that a specific passenger request can benefit from a delayed matching since he/she may be matched with closer idle drivers after waiting for a few seconds. The problems are solved by reinforcement learning methods. Through extensive empirical experiments with well-designed simulators, we show that the proposed frameworks can remarkably improve system performances.
主讲人简介：毕业于清华大学，获得土木工程学士学位和交通工程硕士学位，并于香港科技大学获得交通工程博士学位。现任西南财经大学人工智能与管理科学研究中心主任，大数据研究院副院长。国家级人才、国家自然科学基金优秀青年基金获得者。研究方向主要包括人工智能算法与数据挖掘、复杂交通系统建模优化、金融风控与智能投顾、区块链等。先后主持和参与了NSFC-RGC香港-内地联合基金， NSFC-广东大数据科学中心项目，国家重点研发计划等10余项重要国家和省部级课题。在管理科学与工程、交通科技及数据挖掘领域著名国际期刊和会议如Transportation Science，Transportation Research Part A、B、C、D, IEEE TKDE、ISTTT等发表论文60余篇。
主办：经济管理学院 运营管理创新研究团队
承办：服务科学与创新四川省重点实验室
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