# Bus Travel Time Prediction Based on the Similarity in Drivers' Driving Styles
## 3 Methodology
### Driver Driving Style Classification Method  
In order to better distinguish the driving styles of bus drivers, we also consider the characteristics of space and time. First, travel times are categorized. Specifically, a day is divided into three time periods: 7:00-9:00, 9:00-16:00, and 16:00-19:00. The purpose of this time division is to ensure that the travel time of bus drivers has a similar pattern in the same time period, as the time spent on the same road section varies at different time periods [7]. For example, some drivers need to spend 8-10 min driving through a certain road segment during the morning rush hour from 7:00 to 9:00, while they only need 5-8 min during off-peak hours from 9:00 to 16:00 in the same road segment. There are even some drivers who can drive through this section in less than 5 min.  
Secondly, each bus route is divided into sections. In this step, we consider the road section between two adjacent bus stops as the basic prediction unit. We classify the driving style of the drivers based on the travel time between two adjacent stations (sum of driving time and waiting time). For example, a driver who arrives at a bus stop at a scheduled time can be defined as having a normal driving style. A driver with a mild driving style will arrive later than the scheduled time, while a driver with an aggressive driving style will arrive earlier than the scheduled time. This tendency will gradually become larger with the increase in the distance travelled, so eventually the bus behind will catch up with or overtake the bus in front after a few stops. Similarly, a bus's waiting time at the bus stop can also reflect the driving style of the driver. Different drivers have different reactions to the speed of passengers' movements when they get on the bus. For example, if an impatient driver urges passengers to hurry up and get on the bus at the stop, then the stopping time of this type of driver at the stop will be relatively shorter. A gentle driver generally does not urge passengers but waits quietly for passengers to get on the bus calmly, so this type of driver will wait at the stop for a relatively long time. Drivers with a driving style between the two mentioned above will judge whether to urge passengers or not depending on the time. When there is plenty of time, they will not urge passengers, while when time is tight, they will urge passengers to accelerate boarding.  
In this work, we use the hierarchical clustering analysis model to classify the driving styles of bus drivers. Hierarchical clustering (HC) is a statistical method used to divide objects into groups with similar meanings. It attempts to find groups that minimize differences within groups and maximize differences between external groups. When we do not know the number of groups in advance but want to create groups and analyze group members, we usually use hierarchical clustering analysis [18]. A hierarchical clustering analysis starts with a single point as a cluster and then continuously merges two clusters until only one cluster is left [37]. This method is described in Algorithm 1.  
Figure 2: An overview of our approach. Dataset \(D_{2}\) is generated by dataset \(D_{1}\) after hierarchical clustering. HC—hierarchical cluster; SVM—support vector machine.