A simulation platform for shared mobility services
Principal Investigator: Dr. Jintao KE (Assistant Professor from Department of Civil Engineering)
This project is showcased in the second exhibition – Digitization in Innovation Wing Two
• Smart mobility, smart transportation, and smart city
• Urban computing and transportation big data analytics
• Artificial intelligent for transportation
• Operations research and operational management for on-demand mobility
Personal homepage: https://sites.google.com/view/kejintao
How it can be used?
Researchers can make use of this simulation platform to train and test optimization, machine learning and reinforcement learning algorithms for designing better operating strategies, such as order dispatching, vehicle repositions and dynamic pricing. The simulation platform can also assist the transport department of Hong Kong government in evaluating and designing policies for Hong Kong taxi markets, including vehicle fleet size control and pricing regulations. The ultimate goal of developing this simulation platform is to help taxi operators and government to better manage and operate taxis and ride-hailing vehicles (such as Uber) so as to achieve a sustainable, efficient, and environmentally friendly on-demand transportation systems in Hong Kong.
Finished orders during different period: This part shows the number of finished orders and cancelled orders during different period.
Evaluation metrics: This part shows the different metrics of our simulator, they are matching rate, pickup ratio, delivery ratio and idle ratio respectively.
Transportation: This part we plan to show the carrying passenger of different kinds of transportation.
Order finished status: This part will show the order status per day.
Different line color: This part shows the meaning of different line in the middle map animation.
Bridge flow rank: This part we plan to show the bridge flow rank of Manhattan.
Six metrics explanation