At the peak of the Covid-19 pandemic in 2020, Australian transport agency Transport for New South Wales (NSW) had to restore public confidence in the state's transportation network and curb the spread of the disease. One of the ways it did that was to analyse the travel history recorded by Opal transit cards – with an individual's permission – and inform the commuter if the regular buses and train services that they had been taking were Covid-safe. Chris Bennetts, executive director for digital product delivery at Transport for NSW, said those insights were derived using a machine learning model that predicts how full a bus or train carriage was going to be at a given time. Based on the predictions, commuters would be advised if they could continue using their regular services or switch to a different service or mode of transport. "That was interesting for us because it was our first foray into personalisation to offer more choices for customers," said Bennetts.

Railway operators in the Tokyo area are in the final stages of preparations for the Olympics and Paralympics this summer. East Japan Railway Co., or JR East, is scheduled to open a new station on its Yamanote Line for the first time in 49 years in March. Takanawa Gateway Station, located close to a public viewing event site for the Olympics, is expected to be used by many passengers during the quadrennial sports event. JR East touts Takanawa Gateway as a "future station" that showcases cutting-edge Japanese technologies such as an autonomous security robot and a convenience store without shop assistants. By the end of this month, all train cars for the Yamanote Line will have space available for wheelchair users.

Freight train services in a railway network system are generally divided into two categories: one is the unscheduled train, whose operating frequency fluctuates with origin-destination (OD) demands; the other is the scheduled train, which is running based on regular timetable just like the passenger trains. The timetable will be released to the public if determined and it would not be influenced by OD demands. Typically, the total capacity of scheduled trains can usually satisfy the predicted demands of express cargos in average. However, the demands are changing in practice. Therefore, how to distribute the shipments between different stations to unscheduled and scheduled train services has become an important research field in railway transportation. This paper focuses on the coordinated optimization of the rail express cargos distribution in two service networks. On the premise of fully utilizing the capacity of scheduled service network first, we established a Car-to-Train (CTT) assignment model to assign rail express cargos to scheduled and unscheduled trains scientifically. The objective function is to maximize the net income of transporting the rail express cargos. The constraints include the capacity restriction on the service arcs, flow balance constraints, logical relationship constraint between two groups of decision variables and the due date constraint. The last constraint is to ensure that the total transportation time of a shipment would not be longer than its predefined due date. Finally, we discuss the linearization techniques to simplify the model proposed in this paper, which make it possible for obtaining global optimal solution by using the commercial software.