# A Study on Analyzing Travel Characteristics of Micro Electric Vehicles by Using GPS Data
## 3 Methodology
### Travel Behavior Analysis
#### 3.1.2 Methods to Analyze GPS Data  
In this study, GPS data were used to analyze the travel behavior of micro-EVs. Trip and trip chain characteristics were selected as the variables to explain the travel behaviors of micro-EVs because those variables are suitable for determining how much the micro-EVs were used. A trip is defined as a one-way movement from a point of origin to a point of destination. Furthermore, a trip chain is a set of linked trips. A methodology was devised \begin{table}
\begin{tabular}{c c} \hline
**Variable** & **Description** \\ \hline Time & The time at which pertaining data were recorded \\  & (Year/Month/Day/Hour/Minute/Second) \\ \hline Identity & The identity number of the GPS device equipped in the micro-EV \\ \hline Car name & The name of the micro-EV which the GPS device was equipped in \\ \hline Car number & The car number of the micro-EV which the GPS device was equipped in \\ \hline Longitude/Latitude & The longitude and latitude of the micro-EV at the time (\(\circ\)) \\ \hline Altitude & The altitude of the micro-EV at the time (m) \\ \hline Roll/Pitch/Yaw & The value of Roll/Pitch/Yaw of the micro-EV (\(\circ\)) \\ \hline Acceleration & The acceleration of the micro-EV along its three axes (axes: x, y, z) \\ \hline Gyroscope & The angular velocity of the micro-EV’s rotation along its three axes (\(\circ\)/s, axes: x, y, z) \\ \hline \end{tabular}
\end{table} 
Table 4: Data variables recorded by GPS devices. Figure 1: Example of collected micro-EV GPS data (delivery service). \begin{table}
\begin{tabular}{c c c} \hline
**Micro-EV Model** & \multicolumn{2}{c}{**Number of Micro-EVs for Each Service Type and Micro-EV Model Used for the Analysis**} \\ \cline{2-3}  & **Shared Transport Service** & **Delivery Service** & **Public Service** \\ \hline CEVO-C & 37 & 7 & 3 \\ \hline D2 & 17 & 2 & 2 \\ \hline D2C & - & 1 & 3 \\ \hline Twizy & - & 1 & - \\ \hline MASTA MINI & - & - & 1 \\ \hline MASTA VAN & - & 2 & 26 \\ \hline Total & 54 & 13 & 35 \\ \hline \end{tabular}
\end{table} 
Table 3: Number of micro-EVs by service type and micro-EV model used in the analysis. to extract the trip information of the micro-EVs from GPS data. The methodology focused on finding the state in which the vehicle was stopped. This is because trip information can be found when a stationary state is found, as a trip exists between stationary states. The procedure of extracting the trip information of the micro-EVs from GPS data was conducted as below. The first step was to determine the micro-EVs' movement state. It was decided whether a micro-EV was stopped or not at all moments. Considering the error of GPS data, if the speed at every moment was less than 1 m/s, this was defined as the \"stationary\" state. On the other hand, if the speed was 1 m/s or more, it was determined that the micro-EV was moving, and this was defined as the \"moving\" state. Since trips were determined based on the stationary state, the stationary state needed to be accurately determined. If the micro-EV was determined to be moving due to an error in GPS data, although it had stopped, the number of trips was likely to be overestimated. To solve this problem, the stationary state was conservatively judged. If at one moment, the vehicle speed was 1 m/s or more, but there was a stationary state within two seconds before and after this moment, it was determined to be stationary. The second step was to classify trips and trip chains based on the stationary state. Trips were classified based on the stationary states of micro-EVs. However, not all stationary states could be used as a criterion for distinguishing trips, because there were stationary states that were unintentional temporary stops due to traffic conditions and traffic signals, i.e., they did not mark the end of a trip. Therefore, trips were classified based on stationary states that lasted longer than a specific period. Most temporary stops that were not trip ends were caused by traffic control facilities such as traffic lights.