Forecasting Ride Demand

Forecasting any kind of demand by consumers is always of interest, so this likely has applications beyond just ride ride prediction.

Hail Technology: Deep Learning May Help Predict When People Need Rides 

Penn State News   By Matt Swayne

Pennsylvania State University (Penn State) researchers analyzing a large dataset of ride requests to Didi Chuxing, a Chinese car-hailing company, found computers may be better at forecasting demand for taxi and ride-sharing services. The team used two types of neural networks to extract patterns of taxi demand, and then to predict the demand patterns with significantly better accuracy than current technology, explains Penn State's Huaxiu Yao. When users need a ride they make a request via a computer application, and the researchers think tapping these requests, instead of relying on ride data only, reflects overall demand better. With the historical data, which includes the request's time and location, the computer could anticipate how demand will change over time, and the researchers were able to visualize how that demand evolved by plotting it on a map. "Basically, we used a very complicated neural net to simulate how people digest information, in this case, the image of the traffic patterns," notes Penn State professor Jessie Li.  ... "