# A Spatio-Temporal Schedule-Based Neural Network for Urban Taxi Waiting Time Prediction
## 3 Materials and Methods
### Analysis of Weather Affecting Taxi Passenger Behavior  
Weather conditions are also important factors affecting the residents' daily itineraries. People often choose whether to travel, the choice of means of travel and the arrangement of travel routes according to weather conditions [29]. Different weather will cause different fluctuations in the balance between the supply and demand of taxis and taxi passengers. Moreover, under the same weather, the behavior of passengers in different functional areas is likely to diverge. For example, residents in residential areas might less travel when it rains, thereby reducing the demand for taxis, while the demand for taxis in shopping service areas may surge.  
Generally speaking, weather and temperature are important factors, for example, with sunny days, and residents have many choices of travel modes. People always choose to walk or share bicycles for short distances and choose urban rail transit or buses for longer distances. That is to say, the supply and demand relationship between taxis and passengers is in a relatively balanced situation on a sunny day. However, when the temperature reaches 35 \({}^{\circ}\)C or higher, residents are likely to reduce their trips and prefer taxis as convenient, flexible and not crowded. In rainy weather, residents' travel time will increase, the willingness and frequency of travel will be weakened. At the same time, due to weather, the time and cost of the journey will also increase [30; 31]. The amount of rainfall will also affect the behavior of taxi passengers. Light rain may promote the demand for taxis in large commercial districts, but heavy rain will have the opposite effect. In winter, it is difficult for road residents to travel in snowy cities, and the number of people who choose to travel by taxi will increase. Weather problems have aggravated road congestion and the situations in which vehicles are prone to slip and brake during driving, making it difficult for drivers to drive. Cloudy skies, fog, and nail can also affect the normal work of urban traffic, especially changing the daily demand for taxis by urban residents. When extreme weather occurs, urban traffic will fall into an abnormal state. For example, Wuhan experienced high temperatures, hail, and hurricanes on 11 August 2013, which negatively impacted citizens' travel. In summary, this article divides the weather into ten categories: sunny, high temperature, overcast, light rain, moderate rain, heavy rain, snow, hail, fog, and extreme weather.  
However, considering the relationship between weather and temperature, we only consider weather factors. On the one hand, weather suitable for travel is often accompanied by pleasant temperatures, and weather unsuitable for people to travel is often accompanied by severe temperatures. More importantly, the impact of weather on people's travel is often greater. For example, even if the weather is pleasant, people are often reluctant to go out if it rains or is foggy. In summary, this model mainly uses weather factors to measure the impact of climate on people's travel.