Towards Understanding the Impact of Human Mobility Patterns on Taxi Drivers' Income Based on GPS Data: A Case Study in Wuhan - China

Taxi trajectories can reflect human mobility over urban roads' network. Although taxi drivers cruise the same city roads, there is an observed variation in their daily incomes. To reveal the reasons behind this issue, this study introduces a method for investigating and understanding the impact of human mobility patterns (taxi drivers' behavior) on drivers' income. Firstly, a method for classifying taxi drivers into three income levels according to their daily income is introduced. Secondly, cruising trips and stopping spots are extracted for each income level. Thirdly, a comparison on the income levels of drivers in terms of spatial and temporal patterns on cruising trips and stopping spots is applied. The comparison applied various methods including mash map matching method and DBSCAN clustering method. Finally, an overall analysis and discussion on the results are introduced. The results showed that there is a relationship between human mobility patterns and taxi drivers' income. High-income drivers based on their experience earn more compared to other drivers as they know which places are more active to cruise and to stop and at what times. This study provides suggestions and insights to taxi companies and taxi drivers to increase their daily income and enhance the efficiency of the taxi industry.