  Urban traffic analysis is crucial for traffic forecasting systems, urban
planning and, more recently, various mobile and network applications. In this
paper, we analyse urban traffic with network and statistical methods. Our
analysis is based on one big bus dataset containing 45 million bus arrival
samples in Helsinki. We mainly address following questions: 1. How can we
identify the areas that cause most of the traffic in the city? 2. Why there is
a urban traffic? Is bus traffic a key cause of the urban traffic? 3. How can we
improve the urban traffic systems? To answer these questions, first, the
betweenness is used to identify the most import areas that cause most traffics.
Second, we find that bus traffic is not an important cause of urban traffic
using statistical methods. We differentiate the urban traffic and the bus
traffic in a city. We use bus delay as an identification of the urban traffic,
and the number of bus as an identification of the bus traffic. Third, we give
our solutions on how to improve urban traffic by the traffic simulation on road
networks. We show that adding more buses during the peak time and providing
better bus schedule plan in the hot areas like railway station, metro station,
shopping malls etc. will reduce the urban traffic.
