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Trip planning is an essential function provided by an intelligent transportation system. As many different transport modes have been emerging recently, it becomes a common requirement to mix available transport types to find the most comfort and fastest solutions for getting given destinations. A key challenge for achieving such a desired trip plan is to get quality estimations of all possible traveling services rapidly and accurately. Thanks to the rapid growth of mobile computing, lots of real-time data about traffic status can be collected throw smartphones. Based on such continuously acquired data, we would get quality estimations more accurately and efficiently. Thus, we design and implement a big trajectory data processing platform based on microservices for supporting multimodal trip planning. The paper introduces not only the services and service processes for dealing with the big trajectory data but also the implementation and distributed deployment based on microservices deployed in multiple Dockers. Regarding the loosely-coupled nature of microservices, this platform can provide a flexible way to support trip planning applications consider new available travel modes quickly. Keywords—trip planning; big trajectory data processing; multimodal routing; microservices

A Microservice–based Big Trajectory Data Processing Platform for Multimodal Trip Planning