# Using Connected Vehicle Data to Evaluate National Trip Trends
## 5 National Trip Trends Summary Statistics  
Table 2 shows the summary statistics for the estimated trip length (ETL) and trip duration (TD) using December 2022 CV data. The table provides estimates of the mean, 85 th, and 95 th percentiles by vehicle type (ICEV, HV, and EV). Data from nearly 947 million combined vehicle trips is used to estimate these trip statistics. Table 3 shows a similar table with only the mean and 85 th percentile results from a follow-up analysis of the 2017 NHTS [26]. In general, both the trip length and duration estimates from CV data match very closely with the NHTS. A side-by-side bar plot comparing the mean and 85 th percentile trip lengths is presented in Figure 1 for visualization purposes. The mean trip length for ICEV differs by only 0.7 mi (Figure 1a), whereas the 85 th percentile differs by only 0.1 mi (Figure 1b). The estimations using CV data are slightly higher for EV--1.1 and 1.8 mi difference in mean and 85 th percentile trip length, respectively. This is likely due to the higher penetration of both vehicles and charging infrastructure in 2022 compared with 2017. \begin{table}
\begin{tabular}{c c} \hline \hline
**Attribute** & **Description** \\ \hline Anonymized Journey Identifier & Allows classification of CV records into journeys \\ Vehicle Classification Code & Allows classification of CV journeys by fuel type—EV, HV or ICEV \\ Estimated Trip Length & Cumulative sum of pairwise consecutive waypoint distances \\ Trip Duration & Cumulative sum of pairwise gaps in consecutive waypoint timestamps \\ Origin Census & Census Blockgroup ID within which a journey’s first waypoint lies \\ Detection Census Blockgroup ID & Census Blockgroup ID within which a journey’s final waypoint lies \\ Origin Ignition Status & Ignition Status at journey’s first waypoint \\ Destination Ignition Status & Ignition Status at journey’s final waypoint \\ Origin Timestamp & Timestamp recorded by journey’s first waypoint \\ Destination Timestamp & Timestamp recorded by journey’s final waypoint \\ Maximum Distance & Maximum value of shortest great-circle distance between two consecutive waypoints on \\  & a journey \\ Maximum Time Gap & Maximum gap in time observed between two consecutive waypoints on a journey \\ \hline \hline \end{tabular}
\end{table} 
Table 1: CV Trip Attributes Derived from Raw CV Trajectory Data. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Vehicle Type**} & \multirow{2}{*}{**Trips**} & \multicolumn{2}{c}{**Mean**} & \multicolumn{2}{c}{**85 th Percentile**} & \multicolumn{2}{c}{**95 th Percentile**} \\ \cline{3-6}  & & **ETL (mi)** & **TD (min)** & **ETL (mi)** & **TD (min)** & **ETL (mi)** & **TD (min)** \\ \hline ICEV & 937,912,748 & 8.3 & 18.5 & 14.6 & 32.5 & 30.6 & 57.8 \\ HV & 2,056,404 & 7.6 & 16.7 & 13.7 & 30.0 & 29.3 & 52.6 \\ EV & 6,940,148 & 6.9 & 16.6 & 13.0 & 29.5 & 27.7 & 51.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary Statistics using December 2022 CV Data. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Vehicle**} & \multicolumn{2}{c}{**Mean**} & \multicolumn{2}{c}{**85 th Percentile**} \\ \cline{2-5}  & **ETL (mi)** & **TD (min)** & **ETL (mi)** & **TD (min)** \\ \hline ICEV & 9.0 & 19.8 & 14.7 & 30 \\ HEV & 9.6 & 20.7 & 16.0 & 31 \\ PHEV & 10.4 & 21.6 & 17.8 & 35 \\ EV & 8.0 & 19.1 & 14.8 & 30 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary Statistics using 2017 NHTS [26]. There are slight variations among the HV estimations, which could be due to the CV data using a single category for hybrid vehicles and the NHTS separating hybrids and plug-in hybrids, as well as a change in HV market penetration rates. Mean ICEV trip lengths and trip durations for CV data and NHTS are within 7.8% and 6.6% of each other, respectively. Similarly, 85 th percentile ICEV trip lengths and trip durations are within 0.7% and 8.3%, respectively. Figure 2 compares the percentage of trips by estimated trip length between CV and NHTS [1].