trafficwaves.github.io/test.html at main · trafficwaves/trafficwaves.github.io · GitHub

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<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <!-- Important for mobile responsiveness -->
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Traffic Wave Dynamics</title>
  <link href="https://fonts.googleapis.com/css2?family=Lora:wght@400;700&display=swap" rel="stylesheet">
  <style>
    /* Global Styles */
    body {
      font-family: 'Lora', serif;
      display: flex;
      flex-direction: row;
      margin: 20px;
      /* Optional: set a max-width to keep content narrower on very wide screens */
      max-width: 1200px;
      margin-left: auto;
      margin-right: auto;
    }

    .controls {
      flex: 1;
      margin-right: 20px;
      /* On really small screens, keep some padding so it doesn't bump against edges */
      box-sizing: border-box;
    }

    .visualization {
      flex: 1;
      border: 1px solid #ccc;
      padding: 20px;
      text-align: center;
      box-sizing: border-box;
    }

    /* Buttons */
    .button {
      background-color: #007BFF;
      color: white;
      padding: 10px 15px;
      border: none;
      border-radius: 5px;
      font-size: 16px;
      cursor: pointer;
      margin: 5px;
      font-family: 'Lora', serif;
    }

    .button:hover {
      background-color: #0056b3;
    }

    .input-field {
      margin: 10px 0;
    }

    .input-field label {
      display: block;
      font-size: 16px;
      margin-bottom: 5px;
    }

    .input-field select {
      padding: 8px;
      font-size: 14px;
      width: 200px;
    }

    #cluster-section, #index-section {
      margin-top: 20px;
    }

    #index-container {
      margin-top: 20px;
    }

    canvas {
      margin-top: 20px;
      max-width: 100%;
      max-height: 600px; /* Let the canvas be auto-height, so it scales on mobile */
    }

    /*
      Media Query:
      Switch to column layout on smaller screens (e.g., below 768px).
      Adjust as needed.
    */
    @media (max-width: 768px) {
      body {
        flex-direction: column;
        margin: 0; /* or keep some margin if you prefer */
      }

      .controls, .visualization {
        flex: none;
        width: 100%;
        margin: 0; /* Remove side margin so they take full width on mobile */
        margin-bottom: 20px; /* add some spacing at the bottom */
      }
    }
  </style>
  <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body onload="preloadLane1()">
  <!-- Controls Panel -->
  <div class="controls">
    <h1> Gallery of Traffic Wave Dynamics</h1>
    <p>
      This is the gallery of the wave components identified from
      <a href="https://i24motion.org" target="_blank" style="color: #3498db; text-decoration: none;">I-24 MOTION INCEPTIONv1</a> data.
      Visit <a href="https://trafficwaves.github.io/demo" target="_blank" style="color: #3498db; text-decoration: none;">this demo</a> for
      2-hour demo of the speed field data from the I-24 MOTION INCEPTIONv1 dataset.
    </p>
    <p>
      You can select the lane number (defualt lane 1, i.e. <a href="https://www.tn.gov/tdot/traffic-design/high-occupancy-vehicle-hov-lane.html"  style="color: #3498db; text-decoration: none;">HOV lane </a>) and then click on the "Load Lane Data" button to view the clusters of wave components by the number of bifurcations,
      the number of mergers, and wave length.
    </p>
    <!-- Lane Selection -->
    <div class="input-field">
        <label for="lane-select">Select Lane:</label>
        <select id="lane-select">
          <option value="1">1</option>
          <option value="2">2</option>
          <option value="3">3</option>
          <option value="4">4</option>
        </select>
      </div>
      <button class="button" onclick="loadLaneCSV()">Load Lane Data</button>
    <p>
      The visualization panel <a href="https://trafficwaves.github.io//#visualization-panel">Go to Cluster Visualization</a>
      is a simplified scatter plot of the wave length (mile, in Y-axis)
      vs. the number of bifurcations (in X-axis).
    </p>
    <p>
      You can have an idea of how complex each wave component is (based on the number of bifurcations) and how long it is (wave length).
    </p>
    <p style="background-color: #FEEEB6; padding: 10px; border-radius: 5px;">
      Highlight: Wave topology can range from remarkably simple to incredibly complex.
       Some waves travel over three miles without any bifurcations before merging, while others can bifurcate more than 10 times along their propagation!
    </p>
    <p>
      Click on any point on the "Cluster Visualization" plot to view the corresponding detailed wave component in the SVG format.
    </p>
    <p style="background-color: #FEEEB6; padding: 12px; border-radius: 5px; font-size: 20px; font-weight: bold;">
      Enjoy the beauty of the wave dynamics!
    </p>
      <p>
        For technical details, please refer to the paper:
        <a href="https://arxiv.org/abs/2409.00326" target="_blank" style="color: #3498db; text-decoration: none;">Scalable analysis of stop-and-go waves</a>.
      </p>
      <p>
        If you find this resource useful, please consider citing the paper:
      </p>
      <div style="background-color: #f4f4f4; border-left: 4px solid #3498db; padding: 10px; margin: 15px 0; font-family: 'Courier New', monospace; font-size: 0.95em; overflow-x: auto;">
        <pre style="margin: 0; white-space: pre-wrap;">
    @article{ji2026scalable,
      title={Scalable analysis of stop-and-go waves: Representation, measurements and insights},
      author={Ji, Junyi and Gloudemans, Derek and Wang, Yanbing and Zach{\'a}r, Gergely and Barbour, William and Sprinkle, Jonathan and Piccoli, Benedetto and Work, Daniel B},
      journal={Transportation Research Part C: Emerging Technologies},
      volume={182},
      pages={105385},
      year={2026},
      publisher={Elsevier}
    }
        </pre>
      </div>
    <p>
        Contact <a href="mailto:
        junyi.ji@vanderbilt.edu" style="color: #3498db; text-decoration: none;"> Junyi Ji</a> at Vanderbilt University if you have any questions or suggestions.
    </p>

    <p>
      To explore wave components by date, first select a date, then choose a cluster of interest. Click "Next" to view detailed wave components by clicking the buttons under "Available Indices".
      This will display all wave components for the selected date, lane, and cluster, along with information on wave length, number of bifurcations, and number of mergers.
    </p>
    <p>
      Click on the button to view the detailed wave component in the SVG format.
    </p>
    <!-- Date Selection -->
    <div class="input-field">
      <label for="date-select">Select Date:</label>
      <select id="date-select">
        <option value="2022-11-22">2022-11-22</option>
        <option value="2022-11-28">2022-11-28</option>
        <option value="2022-11-29">2022-11-29</option>
        <option value="2022-11-30">2022-11-30</option>
        <option value="2022-12-01">2022-12-01</option>
        <option value="2022-12-02">2022-12-02</option>
      </select>
    </div>

    <!-- Cluster Selection -->
    <div id="cluster-section" style="display: none;">
      <h2>Select Cluster</h2>
      <div class="input-field">
        <label for="cluster-select">Select Cluster:</label>
        <select id="cluster-select"></select>
      </div>
      <button class="button" onclick="showIndexSection()">Next</button>
    </div>

    <!-- Index Display -->
    <div id="index-section" style="display: none;">
      <h2>Available Indices</h2>
      <div id="index-container"></div>
    </div>
  </div>


    <!-- Visualization Panel -->
    <div id="visualization-panel" class="visualization">
        <h2 id="visualization-title">Cluster Visualization for Lane 1</h2>

        <!-- Add Lane Selection Inside Visualization -->
        <div class="input-field" style="margin-bottom: 10px;">
        <label for="lane-select-visual">Select Lane:</label>
        <select id="lane-select-visual">
            <option value="1">1</option>
            <option value="2">2</option>
            <option value="3">3</option>
            <option value="4">4</option>
        </select>
        <button class="button" onclick="loadLaneCSVFromVisualization()">Load Lane Data</button>
        </div>

        <canvas id="clusterChart"></canvas>
    </div>


  <script>
    let csvData = [];
    let clusterChart;

    async function preloadLane1() {
      document.getElementById('lane-select').value = '1';
      await loadLaneCSV();
    }
    // Load Lane Data from Visualization Panel
    async function loadLaneCSVFromVisualization() {
    const lane = document.getElementById('lane-select-visual').value;
    document.getElementById('lane-select').value = lane; // Sync with main dropdown
    await loadLaneCSV(); // Reuse the existing loadLaneCSV function
    }
    // Load CSV Data
    async function loadLaneCSV() {
      const lane = document.getElementById('lane-select').value;
      document.getElementById('lane-select-visual').value = lane; // Sync with main dropdown
      document.getElementById('visualization-title').innerText = `Cluster Visualization for Lane ${lane}`;
      if (!lane) {
        alert('Please select a lane first.');
        return;
      }

      const csvFile = `https://trafficwaves.github.io/cc_properties_lane_${lane}.csv`;
      try {
        const response = await fetch(csvFile);
        if (!response.ok) {
          throw new Error(`Failed to load ${csvFile}.`);
        }
        const csvText = await response.text();
        parseCSV(csvText);
      } catch (error) {
        console.error('Error loading CSV:', error);
        alert(`Failed to load CSV file for Lane ${lane}.`);
      }
    }

    // Parse CSV
    function parseCSV(csvText) {
      const rows = csvText.trim().split('\n').map(row => row.split(','));
      const headers = rows.shift().map(header => header.trim());

      csvData = rows.map(row => {
        const entry = {};
        headers.forEach((header, index) => {
          entry[header] = row[index]?.trim();
        });
        return entry;
      });

      populateClusterDropdown();
      renderVisualization();
    }

    // Populate Cluster Dropdown
    function populateClusterDropdown() {
      const date = document.getElementById('date-select').value;
      const clusterSelect = document.getElementById('cluster-select');
      clusterSelect.innerHTML = '';

      const uniqueClusters = [...new Set(csvData.filter(row => row.date === date).map(row => row.cluster))];
      uniqueClusters.forEach(cluster => {
        const option = document.createElement('option');
        option.value = cluster;
        option.textContent = `Cluster ${cluster}`;
        clusterSelect.appendChild(option);
      });

      document.getElementById('cluster-section').style.display = 'block';
    }

    // Show Indices
    function showIndexSection() {
      const date = document.getElementById('date-select').value;
      const lane = document.getElementById('lane-select').value;
      const cluster = document.getElementById('cluster-select').value;

      const indexContainer = document.getElementById('index-container');
      indexContainer.innerHTML = '';

      // Filter rows based on selected date and cluster
      const filteredRows = csvData.filter(row => row.date === date && row.cluster === cluster);

      // Sort filtered rows by wave_length (descending order)
      filteredRows.sort((a, b) => parseFloat(b.wave_length) - parseFloat(a.wave_length));

      // Create buttons for each row
      filteredRows.forEach(row => {
        const button = document.createElement('button');
        button.className = 'button';
        button.textContent = `View Index ${row.cc_id} (Wave Length: ${parseFloat(row.wave_length).toFixed(2)} mile, Bifurcations: ${row.num_bifurcations}, Merges: ${row.num_mergers})`;
        button.onclick = () => {
          const filePath = `https://trafficwaves.github.io/${date}/lane_${lane}/${row.cc_id}_15.svg`;
          window.open(filePath, '_blank');
        };
        indexContainer.appendChild(button);
      });

      document.getElementById('index-section').style.display = 'block';
    }
    // Render Visualization with Clickable Points
    function renderVisualization() {
      const ctx = document.getElementById('clusterChart').getContext('2d');
      const groupedData = {};

      csvData.forEach(row => {
        if (!groupedData[row.cluster]) groupedData[row.cluster] = [];
        groupedData[row.cluster].push({
          x: parseFloat(row.num_bifurcations),
          y: parseFloat(row.wave_length),
          date: row.date,
          cc_id: row.cc_id,
          num_bifurcations: row.num_bifurcations,
          num_mergers: row.num_mergers
        });
      });

      const datasets = Object.keys(groupedData).map(cluster => ({
        label: `Cluster ${cluster}`,
        data: groupedData[cluster],
        pointRadius: 5,
      }));

      if (clusterChart) clusterChart.destroy();
      clusterChart = new Chart(ctx, {
        type: 'scatter',
        data: { datasets },
        options: {
          plugins: {
            tooltip: {
              callbacks: {
                label: function(context) {
                  const point = context.raw;
                  return `[${point.date}, index id: ${point.cc_id}, bifurcations: ${point.num_bifurcations}, mergers: ${point.num_mergers}, wave length: ${point.y.toFixed(2)} mile]`;
                }
              }
            }
          },
          scales: {
            x: {
              title: {
                display: true,
                text: 'Number of Bifurcations' // X-axis Title
              }
            },
            y: {
              title: {
                display: true,
                text: 'Wave Length (mile)' // Y-axis Title
              },
              min: 0,
              max: 4
            }
          },
          responsive: true,
          maintainAspectRatio: false,
          onClick: (event, elements) => {
            if (elements.length > 0) {
              const clickedElementIndex = elements[0].index;
              const datasetIndex = elements[0].datasetIndex;
              const clickedPoint = clusterChart.data.datasets[datasetIndex].data[clickedElementIndex];

              if (clickedPoint) {
                const filePath = `https://trafficwaves.github.io/${clickedPoint.date}/lane_${document.getElementById('lane-select').value}/${clickedPoint.cc_id}_15.svg`;
                window.open(filePath, '_blank');
              }
            }
          }
        }
      });
    }

  </script>
</body>
</html>