Travel demand estimation

A Two-Step Model for Predicting Travel Demand in Expanding Subways

In many cities, subways are expanding with new or extended lines being built and put into operations. The prediction of future travel demand in subway with the planned expansion is of significant importance because such information is crucial for new …

Identification and Prediction of Large Crowd Gatherings based on Transportation Big Data

In recent years, with the rapid development of China’s economy and the rapid increase of urban population, the imbalance between supply and demand becomes more notable as various commercial and entertainment activities attract large crowds in urban areas. Although large-scale activities can bring substantial economic benefits to the city and satisfy the spiritual needs of the people, they will also bring tremendous pressure on the transportation facilities around the activity area, leading to negative impacts such as chaotic safety management, traffic congestion.

Modeling real-time human mobility based on mobile phone and transportation data fusion

Faced with severe traffic congestions, the level of traffic planning and organization has been paid much attention. As a crucial and fundamental data for traffic planning and traffic organization, travel demand has been an important research topic …

Vulnerability analysis of urban rail transit networks

The urban rail transit network is an important part of an urban public transportation system. First, we generated the network models of the urban rail networks of Beijing and Shenzhen. We used the subway smart card data to estimate the passenger …

Driver source prediction and visualization system based on mobile phone data

With the development of urbanization never seen before, the condition of traffic congestion, transit service quality and mergency response capability become more severe. Existing research and engineering practice tend to focus on the analysis and control of phenomena, but lack of probing the underlying causes of the problem.The rise of big data and the proposed source prediction methods provide an important foundation for analysis of the traffic problems’ underlying causes and solving the traffic problems from the source.