30 citations · 43 across the 3 of their papers we have counts for
5 papers
Competitive ride-sourcing market with a third-party integrator
Yaqian Zhou, Hai Yang, Jintao Ke +2
Recently, some transportation service providers attempt to integrate the ride services offered by multiple independent ride-sourcing platforms, and passengers are able to request r…
Optimizing Online Matching for Ride-Sourcing Services with Multi-Agent Deep Reinforcement Learning
Jintao Ke, Feng Xiao, Hai Yang +1
Ride-sourcing services are now reshaping the way people travel by effectively connecting drivers and passengers through mobile internets. Online matching between idle drivers and w…
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
Huaxiu Yao, Fei Wu, Jintao Ke +6
Taxi demand prediction is an important building block to enabling intelligent transportation systems in a smart city. An accurate prediction model can help the city pre-allocate re…
PCA-Based Missing Information Imputation for Real-Time Crash Likelihood Prediction Under Imbalanced Data
Jintao Ke, Shuaichao Zhang, Hai Yang +1
The real-time crash likelihood prediction has been an important research topic. Various classifiers, such as support vector machine (SVM) and tree-based boosting algorithms, have b…
Ridesourcing Car Detection by Transfer Learning
Leye Wang, Xu Geng, Jintao Ke +4
Ridesourcing platforms like Uber and Didi are getting more and more popular around the world. However, unauthorized ridesourcing activities taking advantages of the sharing economy…