Trip Distribution

Modeled average trip lengths for the base year were compared to the 2012 Household Travel Survey. The model was validated for for distance, time, and generalized cost using the following measures:

• Average Trip Lengths
• Trip Length Frequencies

Average Trip Lengths

The following figure shows the average trip lengths the modeled and observed time, distance, and generalized cost.

Code

viewof varSelect = Inputs.select(new Map([['Generalized Cost','GC'], ['Distance', 'Dist'], ['Time', 'Time']]), {value: 'Variable', label: "Variable"})

viewof purpSelect  = Inputs.select(new Map([['Internal Trip Purposes', 'MainPurposes'], ['External Trip Purposes', 'Externals']]), {value: 'PurpType', label: "Purpose Set"});

Code

dataLT = transpose(dataStats)
filtered_data = dataLT.filter(function(dataL) {
    return varSelect == dataL.Variable &&
           purpSelect == dataL.PurpType;
})

Code

import {GroupedBarChart} from "@d3/grouped-bar-chart"
import {Legend, Swatches} from "@d3/color-legend"
import {howto, altplot} from "@d3/example-components"

Plot

Code

//https://observablehq.com/@d3/grouped-bar-chart
key = Legend(chart.scales.color, {title: "Data Source"})

Code

chart = GroupedBarChart(filtered_data, {
    x: d => d.Purpose,
    y: d => d.AVG_TRIP_LEN,
    z: d => d.DataSource,
    yLabel: "Average Trip Length",
    zDomain: ['Model','Observed'],
    height: 500,
    colors: ["#376092", "#77933c"]
})

Figure 1: Average Trip Length between model and observed.

Table

Code

Inputs.table(filtered_data)

Trip Length Frequencies

Modeled trip lengths for the base year were compared to the 2012 Household Travel Survey. The following figures shows the modeled and observed time and distance average trip lengths and trip length frequencies.

Code

optionsTripPurp = 
[
    ['Home-Based Work'                   , 'HBW'    ],
    ['Home-Based Shopping'               , 'HBShp'  ],
    ['Home-Based Other'                  , 'HBOth'  ],
    ['Home-Based School - Primary'       , 'HBSchPr'],
    ['Home-Based School - Secondary'     , 'HBSchSc'],
    ['Non-Home-Based Work'               , 'NHBW'   ],
    ['Non-Home-Based Non-Work'           , 'NHBNW'  ],
    ['Light Trucks'                      , 'LT'     ],
    ['Medium Trucks'                     , 'MD'     ],
    ['Heavy Trucks'                      , 'HV'     ],
    ['Internal-to-External'              , 'IX'     ],
    ['External-to-Internal'              , 'XI'     ]
]

viewof vTripPurp = Inputs.select(new Map(optionsTripPurp), {value: 'HBW', label: "Trip Purpose:"})

viewof vTlfType = Inputs.select(new Map([['Generalized Cost','GC'],['Distance','Dist'],['Time','Time']]), {value: 'Dist', label: "Variable:"})

Code

freqT = transpose(freq)

freqT_filtered_Obs = freqT.filter(function(freqData) {
    return vTripPurp == freqData.TRIPPURP &&
    vTlfType == freqData.TLFTYPE &&
    'freqObs' == freqData.freqSource;
})

freqT_filtered_Mod = freqT.filter(function(freqData) {
    return vTripPurp == freqData.TRIPPURP &&
    vTlfType == freqData.TLFTYPE &&
    'freqMod' == freqData.freqSource;
})

Code

key2 = Legend(chart.scales.color, {title: "Data Source"})

Code

Plot.plot({
  grid: true,
  aspectRatio: 0.5,
  x: {label: 'Distance/Time/Cost', tickFormat: d => d},
  y: {label: 'Frequency', tickFormat: f => `${Math.round(f * 100)}%`},
  marginRight: 60,
  marginLeft: 60,
  style: {
    fontSize: 15
  },
  marginTop: 60,
  marginBottom: 60,
  marks: [
    Plot.line(
      freqT_filtered_Mod, {x: 'BIN', y: 'freq', stroke: "#376092", strokeWidth: 4}),
    Plot.line(
      freqT_filtered_Obs, {x: 'BIN', y: 'freq', stroke:  "#77933c", strokeWidth: 4}),
    Plot.frame({strokeOpacity: 0.2}),
    ]
});

Figure 2: Trip Length Frequencies between Model and Observed.