TransModeler-VRC-Visualization

Corridor Travel Time Analyzer

A client-side web application for analyzing transit and vehicle travel times along transportation corridors using VRC sensor data. Compare multiple scenarios with interactive visualizations showing segment-level and corridor-level performance metrics.

Corridor Travel Time Analyzer

Features

📊 Multi-Scenario Comparison

Upload and compare multiple VRC Sensor Reports simultaneously
Side-by-side visualization of baseline, build, and alternative scenarios
Support for CSV and Excel file formats

🚌 Flexible Vehicle Filtering

Transit Only: Analyze bus/transit vehicle travel times
All Vehicles: Include all traffic
Trucks Only: Focus on commercial vehicle movements

📈 Comprehensive Analysis

Segment-Level Analysis: Travel time by individual corridor segments
Corridor-Level Analysis: End-to-end travel time distributions
Time Series: 15-minute median travel times throughout the peak period
Statistical Summaries: Mean, median, P10, and P90 travel times

🎨 Interactive Visualizations

Bar charts comparing median travel times by segment
Box plots showing travel time distributions
Time series plots tracking performance over time
Summary tables with key statistics

🔒 Privacy-Focused

100% Client-Side Processing: All data stays in your browser
No server uploads or data transmission
Works completely offline after initial load

Quick Start

Live Demo

Open tt_analyzer.html in any modern web browser. No installation required!

Basic Workflow

Load Segment Catalog
- Upload your segment catalog Excel file (Direction, Segment Number, Placement, Sensor ID, Location)
- Defines the corridor structure and sensor order
Add Scenarios
- Upload VRC Sensor Report files (one per scenario)
- Label each scenario (e.g., “NoBuild”, “Build”, “Alternative”)
- Add or remove scenarios as needed
Configure Analysis
- Select vehicle filter (Transit only / All vehicles / Trucks only)
- Set corridor matching mode (strict or allow missing sensors)
- Define time window (default: 2-5 PM)
Process & Visualize
- Click “Process data” to analyze
- Switch between visualization tabs
- Download processed data as CSV

File Structure

corridor-tt-analyzer/
├── tt_analyzer.html       # Main application file
├── styles.css             # Dark theme styling
├── app.js                 # Core analysis logic
└── README.md             # This file

Input File Formats

Segment Catalog (Excel/CSV)

Defines the corridor structure with columns:

Direction	Segment Number	Placement	Sensor ID	Location
Northbound	2	Start	2905	North of Hampden Ave
Northbound		End	2969	South of Amherst Ave
Northbound	3	Start	2969	South of Amherst Ave
…	…	…	…	…

Direction: Northbound or Southbound
Segment Number: Sequential segment identifiers
Placement: Start or End of segment
Sensor ID: Unique sensor identifier
Location: Human-readable location description

VRC Sensor Report (CSV/Excel)

Multi-section format with blocks beginning with “Sensor ID XXXX”:

Sensor ID 2905
Time        Vehicle    Transit    Speed (mph)    Occupants
2:03:45 PM  101        1          35             2
2:05:12 PM  102        1          38             15
...

Sensor ID 2969
Time        Vehicle    Transit    Speed (mph)    Occupants
2:06:30 PM  101        1          33             2
...

Required columns:

Time: Timestamp (formats: “h:mm:ss A” or “h:mm A”)
Vehicle: Vehicle ID (numeric)
Transit: Binary flag (1 = transit, 0 = other)
Truck: Binary flag (1 = truck, 0 = other) [optional]

How It Works

Data Processing Pipeline

Segment Catalog Loading
- Parses Excel/CSV with segment definitions
- Forward-fills blank direction cells
- Assigns segment numbers to End placements
- Builds corridor order (NB ascending, SB descending)
VRC Report Parsing
- Reads multi-section sensor reports
- Extracts activations (sensor hits by vehicle)
- Normalizes timestamps and vehicle IDs
- Filters by vehicle type and time window
Travel Time Computation
- Link Travel Times: Time between consecutive sensors
- Corridor Travel Times: End-to-end journey times
- Deduplicates first hit per vehicle/direction/sensor
- Uses upstream segment for link labeling
Statistical Analysis
- Groups by scenario, direction, and segment
- Computes median, mean, P10, P90 percentiles
- Bins data into 15-minute intervals
- Generates summary statistics
Visualization
- Interactive Plotly.js charts
- Responsive design with tab navigation
- Real-time updates on direction/segment selection

Technology Stack

Frontend: Vanilla JavaScript (ES6+)
Parsing:
- PapaParse for CSV files
- SheetJS for Excel files
Date/Time: Day.js
Visualization: Plotly.js
Styling: Custom CSS with dark theme

Browser Compatibility

Tested and working on:

✅ Chrome 90+
✅ Firefox 88+
✅ Edge 90+
✅ Safari 14+

Advanced Features

Corridor Matching Modes

Allow missing middle sensors (default):

Vehicles must touch first and last sensors
Can skip intermediate sensors
More permissive for real-world GPS gaps

Touch every sensor in order (strict):

Vehicles must hit all sensors sequentially
Ensures complete corridor coverage
Useful for quality control

Link Segment Labeling

Travel time for a link between segments N and N+1 is labeled with the departing segment number (N), representing the upstream segment in the direction of travel.

Time Window Filtering

Default: 2:00 PM - 5:00 PM (afternoon peak)
Customizable start/end hours
Filters based on departure times

Data Export

Link Data CSV: Individual segment travel times

Columns: scenario, direction, segment, bin_15min, depart_ts, arrive_ts, travel_time_s, vehicle_id

Corridor Data CSV: End-to-end corridor runs

Columns: scenario, direction, depart_ts, arrive_ts, corridor_tt_s, visited_count, visited_sensors, bin_15min, corridor_tt_min

Troubleshooting

No segments showing in charts

✅ Check that segment catalog has both Start and End rows
✅ Verify sensor IDs match between catalog and VRC reports
✅ Ensure VRC data has vehicles with transit=1 (if using transit filter)

Missing segment 9 or segment 2

✅ Verify End rows have corresponding sensors in the catalog
✅ Check that sensors appear in VRC activations data

Scenario upload disappeared

✅ Check browser console for JavaScript errors
✅ Verify file format is CSV or Excel (.xlsx, .xls)
✅ Ensure VRC report has “Sensor ID XXXX” headers

Charts not displaying

✅ Click “Process data” after uploading files
✅ Check that scenarios have uploaded successfully
✅ Try refreshing the page and re-uploading

Development

Local Setup

# Clone the repository
git clone https://github.com/yourusername/corridor-tt-analyzer.git
cd corridor-tt-analyzer

# Open in browser
open tt_analyzer.html
# or
python -m http.server 8000
# then navigate to http://localhost:8000

Code Structure

app.js main sections:

State management (lines 1-15)
Utility functions (lines 17-73)
File readers (lines 75-101)
Domain parsers (lines 103-235)
Travel time computation (lines 237-430)
Aggregations (lines 432-520)
Plotting functions (lines 522-700)
UI event handlers (lines 702-890)

Contributing

Contributions are welcome! Please:

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

MIT License - see LICENSE file for details

Acknowledgments

Built for transportation planners and traffic engineers analyzing corridor performance using VRC sensor data. Inspired by Python-based travel time analysis workflows.

Contact

Questions? Issues? Open a GitHub issue or reach out to [your-email@example.com]

Note: This tool processes sensitive transportation data locally in your browser. No data is transmitted to external servers. Always follow your organization’s data handling policies.

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