vmt-age.qmd

---
title: "Vehicle Miles Traveled (VMT) by Age"
---

This page shows median cumulative vehicle miles traveled (VMT) by vehicle age. Each chart displays the 50th quantile (median) of total mileage for a given combination of powertrain and vehicle type as vehicles age over time. Lines in the charts below are smoothed using loess smoothihng. The "Data" tab shows the raw data, which also includes the 25th and 75th quantiles. See the [about](about.html#depreciation) page for more details. Note the [observation counts](about.html#listing-counts) by powertrain and vehicle type as some combinations have few observations.

```{r}
#| include: false

source("setup.R")

# Convert age from months to years
data <- vmt_age |>
  mutate(age_years = age_bin / 12)

# Helper function to apply loess smoothing to a group
smooth_group <- function(df, x_col, y_col, span = 0.5) {
  if (nrow(df) < 10) {
    df$miles_smooth <- df[[y_col]]
    return(df)
  }
  tryCatch(
    {
      fit <- suppressWarnings(loess(df[[y_col]] ~ df[[x_col]], span = span))
      df$miles_smooth <- predict(fit)
      df
    },
    error = function(e) {
      df$miles_smooth <- df[[y_col]]
      df
    }
  )
}

# Apply smoothing to all data
data <- data |>
  group_by(powertrain, vehicle_type, quantile) |>
  group_modify(~ smooth_group(.x, "age_years", "miles")) |>
  ungroup()

# Filter to 50th quantile for charts
chart_data <- data |>
  filter(quantile == 50)

# Helper function to create a chart for a given facet
make_chart <- function(data, facet_var, facet_value, line_var) {
  plot_data <- data |>
    filter(.data[[facet_var]] == facet_value)

  plot_data |>
    group_by(.data[[line_var]]) |>
    e_charts(age_years) |>
    e_line(miles_smooth, symbol = "none", smooth = FALSE) |>
    e_tooltip(
      trigger = "axis",
      formatter = htmlwidgets::JS(
        "
        function(params) {
          var result = params[0].axisValueLabel + '<br/>';
          params.forEach(function(item) {
            result += item.marker + ' ' + item.seriesName + ': ' +
                      Math.round(item.value[1]).toLocaleString() + '<br/>';
          });
          return result;
        }
      "
      )
    ) |>
    e_x_axis(name = "Age (years)") |>
    e_y_axis(name = "Miles") |>
    e_legend(
      show = TRUE,
      orient = "horizontal",
      left = "center",
      bottom = 0,
      width = "70%",
      selector = list(
        list(type = "all", title = "All"),
        list(type = "inverse", title = "Inverse")
      ),
      selectorPosition = "start"
    ) |>
    e_grid(bottom = 100) |>
    e_color(background = "transparent") |>
    e_toolbox_feature(feature = "dataZoom") |>
    e_toolbox_feature(feature = "saveAsImage")
}
```

## By Vehicle Type

*Click legend items to show/hide lines.*

::: {.grid}

::: {.g-col-6}

### Car

```{r}
make_chart(chart_data, "vehicle_type", "Car", "powertrain")
```

:::

::: {.g-col-6}

### CUV

```{r}
make_chart(chart_data, "vehicle_type", "CUV", "powertrain")
```

:::

::: {.g-col-6}

### SUV

```{r}
make_chart(chart_data, "vehicle_type", "SUV", "powertrain")
```

:::

::: {.g-col-6}

### Pickup

```{r}
make_chart(chart_data, "vehicle_type", "Pickup", "powertrain")
```

:::

::: {.g-col-6}

### Minivan

```{r}
make_chart(chart_data, "vehicle_type", "Minivan", "powertrain")
```

:::

:::



## By Powertrain

*Click legend items to show/hide lines.*

::: {.grid}

::: {.g-col-6}

### Gasoline

```{r}
make_chart(chart_data, "powertrain", "Gasoline", "vehicle_type")
```

:::

::: {.g-col-6}

### Flex Fuel (E85)

```{r}
make_chart(chart_data, "powertrain", "Flex Fuel (E85)", "vehicle_type")
```

:::

::: {.g-col-6}

### Hybrid Electric (HEV)

```{r}
make_chart(chart_data, "powertrain", "Hybrid Electric (HEV)", "vehicle_type")
```

:::

::: {.g-col-6}

### Plug-In Hybrid Electric (PHEV)

```{r}
make_chart(
  chart_data,
  "powertrain",
  "Plug-In Hybrid Electric (PHEV)",
  "vehicle_type"
)
```

:::

::: {.g-col-6}

### Battery Electric (BEV)

```{r}
make_chart(chart_data, "powertrain", "Battery Electric (BEV)", "vehicle_type")
```

:::

::: {.g-col-6}

### BEV (Tesla)

```{r}
make_chart(chart_data, "powertrain", "BEV (Tesla)", "vehicle_type")
```

:::

::: {.g-col-6}

### BEV (Non-Tesla)

```{r}
make_chart(chart_data, "powertrain", "BEV (Non-Tesla)", "vehicle_type")
```

:::

::: {.g-col-6}

### Diesel

```{r}
make_chart(chart_data, "powertrain", "Diesel", "vehicle_type")
```

:::

::: {.g-col-6}

### Fuel Cell

```{r}
make_chart(chart_data, "powertrain", "Fuel Cell", "vehicle_type")
```

:::

:::



## Data: VMT by Age

<center>
<a href="`r url_vmt_age`" style="display: inline-block; padding: 8px 16px; background-color: #0066cc; color: white; text-decoration: none; border-radius: 4px; margin-bottom: 10px;">Download data</a>

<div style="width:900px">

```{r}
data |>
  mutate(
    age_years = round(age_years, 2),
    miles = round(miles, 0),
    miles_smooth = round(miles_smooth, 0)
  ) |>
  select(powertrain, vehicle_type, age_years, quantile, miles, miles_smooth) |>
  rename(
    Powertrain = powertrain,
    `Vehicle Type` = vehicle_type,
    `Age (years)` = age_years,
    Quantile = quantile,
    Miles = miles,
    `Miles (Smoothed)` = miles_smooth
  ) |>
  reactable::reactable(
    searchable = TRUE,
    highlight = TRUE,
    filterable = TRUE,
    defaultPageSize = 10,
    showPageSizeOptions = TRUE,
    pageSizeOptions = c(5, 10, 25, 50)
  )
```

</div>
</center>

## Data: Annual VMT by Type

This table shows the estimated annual vehicle miles traveled (VMT) by vehicle type and powertrain. Annual VMT is calculated as the slope of the linear relationship between vehicle age and cumulative mileage.

<center>
<a href="`r url_vmt_annual_type`" style="display: inline-block; padding: 8px 16px; background-color: #0066cc; color: white; text-decoration: none; border-radius: 4px; margin-bottom: 10px;">Download data</a>

<div style="width:700px">

```{r}
vmt_annual_type |>
  mutate(vmt_annual = round(vmt_annual, 0)) |>
  rename(
    `Vehicle Type` = vehicle_type,
    Powertrain = powertrain,
    `Annual VMT` = vmt_annual
  ) |>
  reactable::reactable(
    searchable = TRUE,
    highlight = TRUE,
    filterable = TRUE,
    defaultPageSize = 10,
    showPageSizeOptions = TRUE,
    pageSizeOptions = c(5, 10, 25, 50)
  )
```

</div>
</center>

## Data: Annual VMT by Model

This table shows the estimated annual vehicle miles traveled (VMT) by make, model, vehicle type, and powertrain. Annual VMT is calculated as the slope of the linear relationship between vehicle age and cumulative mileage.

<center>
<a href="`r url_vmt_annual_model`" style="display: inline-block; padding: 8px 16px; background-color: #0066cc; color: white; text-decoration: none; border-radius: 4px; margin-bottom: 10px;">Download data</a>

<div style="width:900px">

```{r}
vmt_annual_model |>
  mutate(vmt_annual = round(vmt_annual, 0)) |>
  rename(
    Make = make,
    Model = model,
    `Vehicle Type` = vehicle_type,
    Powertrain = powertrain,
    `Annual VMT` = vmt_annual
  ) |>
  reactable::reactable(
    searchable = TRUE,
    highlight = TRUE,
    filterable = TRUE,
    defaultPageSize = 10,
    showPageSizeOptions = TRUE,
    pageSizeOptions = c(5, 10, 25, 50)
  )
```

</div>
</center>