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Network Analysis Reference

This page provides comprehensive technical reference documentation for TM2PY network analysis capabilities.

Highway Network Attributes

Complete Attribute Reference

Source: Actual TM2PY Bay Area database export
File: scripts/emme_link_attributes.txt

The TM2PY highway network contains 85 link attributes extracted from the actual Bay Area EMME database:

Core Performance Attributes

  • auto_volume - Total automobile volume
  • auto_time - Congested travel time (minutes)
  • @free_flow_time - Free flow travel time (minutes)
  • @capacity - Link capacity (vehicles/hour)
  • @ft - Facility type code
  • length - Link length (miles)

Vehicle Type Flows

  • @flow_da - Drive alone flow
  • @flow_sr2 - Shared 2-person flow
  • @flow_sr3 - Shared 3+ person flow
  • @flow_trk - Truck flow

Cost and Performance

  • @cost_da - Drive alone cost
  • @bridgetoll_da - Bridge toll costs
  • @reliability - Reliability measure

→ View complete attribute list

Database Structure

Location: E:\2015-tm22-dev-sprint-04\emme_project\Database_highway\emmebank
Network Size: 839,834 links per scenario
Scenarios: 6 time periods (EA, AM, MD, PM, EV, EA2)

Facility Type Classification

Code Facility Type Description
1 Freeway Interstate highways and freeways
2 Freeway Principal arterial - freeway facilities
3 Arterial Principal arterial roads
4 Arterial Minor arterial roads
5 Collector Major collector roads
6 Collector Minor collector roads
7 Local Local streets and roads
8 Connector Highway ramps and connectors
99 Other Special facilities and other links

Transit Network Attributes

Complete Attribute Reference

Source: TM2PY source code analysis

Transit Line Attributes

  • line.id - Transit line identifier
  • line.mode.id - Mode character (‘b’, ‘l’, ‘h’, ‘r’, ‘f’, ‘e’)
  • line.headway - Service headway in minutes
  • line.vehicle.total_capacity - Total vehicle capacity
  • line["#description"] - Line description/name
  • line["#src_mode"] - Source mode for fare calculations
  • line["#faresystem"] - Fare system ID (1-50)

Transit Segment Attributes

  • segment.transit_volume - PRIMARY passenger volume/boardings
  • segment.transit_boardings - Alternative boarding attribute
  • segment.dwell_time - Dwell time at stops (minutes)
  • segment.link.length - Segment length (miles)

Transit Mode Classification

Code Mode Description
b Local Bus Local bus service (modes 10-99)
e Express Bus Express bus service (modes 80-99)
l Light Rail Light rail transit (modes 110-119)
h Heavy Rail Heavy rail/subway (modes 120-129)
r Commuter Rail Commuter rail service (modes 130-139)
f Ferry Ferry service (modes 100-109)

Analysis Tools

Network Summary Script

Location: scripts/network_summary.py

Enhanced script providing comprehensive highway network analysis:

  • Input Validation: 5-phase validation of database structure and data quality
  • Highway Analysis: VMT, VHT, delay calculations by facility type and time period
  • Comprehensive Logging: Detailed progress reporting and diagnostic information

📖 → View Complete Usage Guide

Transit Network Attributes

Transit Network Structure

Location: E:\2015-tm22-dev-sprint-04\emme_project\Database_transit\emmebank
Scenarios: 6 time periods matching highway (EA, AM, MD, PM, EV, EA2)
Network Elements: Transit lines, segments, and nodes

Transit Line Attributes

Primary Service Attributes: - line.id - Unique line identifier - line.headway - Service headway (minutes between vehicles) - line.vehicle.total_capacity - Total vehicle capacity (standing + seated) - line.vehicle.seated_capacity - Seated vehicle capacity only - line.mode - Service mode (bus, rail, etc.)

Calculated Service Metrics: - Hourly Total Capacity: 60 × total_capacity ÷ headway - Hourly Seated Capacity: 60 × seated_capacity ÷ headway - Service Frequency: 60 ÷ headway (vehicles per hour)

Transit Segment Attributes

Ridership Data: - segment.transit_volume - PRIMARY passenger boardings per hour - segment.dwell_time - Vehicle dwell time at stops (minutes) - segment.transit_time_func - Transit travel time function code

Geographic Attributes: - segment.i_node.id - Origin node ID
- segment.j_node.id - Destination node ID - segment.link.length - Segment length (miles)

Additional Data Fields: - segment.data1 - Custom data field 1 - segment.data2 - Custom data field 2
- segment.data3 - Custom data field 3

Transit Mode Classification

TM2PY Mode Coding: | Mode ID | Mode Type | Description | Service Characteristics | |---------|-----------|-------------|------------------------| | 10-39 | Local Bus | Local bus service | Frequent stops, moderate speed | | 40-79 | Limited Bus | Limited-stop bus | Fewer stops, higher speed | | 80-99 | Express Bus | Express bus service | Minimal stops, freeway operation | | 100-109 | Ferry | Ferry service | Water-based transit | | 110-119 | Light Rail | Light rail transit | Electric rail, grade separation | | 120-129 | Heavy Rail | Heavy rail/subway | Grade-separated rapid transit | | 130-139 | Commuter Rail | Commuter rail | Regional rail service |

Transit Performance Metrics

Ridership Metrics: - Line Boardings: Sum of segment.transit_volume across all segments - Segment Boardings: Individual segment.transit_volume values - Daily Boardings: Sum across all time periods for all-day totals

Capacity Utilization: - Load Factor: boardings ÷ hourly_total_capacity - Seated Load Factor: boardings ÷ hourly_seated_capacity - Peak Load Point: Maximum boardings along line route

Service Productivity: - Boardings per Route Mile: total_boardings ÷ total_route_length - Passengers per Vehicle Hour: boardings ÷ (vehicles_per_hour) - Revenue per Mile: Ridership-based efficiency metric

Coverage Metrics: - Route Miles: Total length of transit routes - Line Count: Number of unique transit lines - Segment Count: Number of route segments with service

Analysis Tools

Network Summary Script

Location: scripts/network_summary.py

Enhanced script providing comprehensive multimodal network analysis:

  • Input Validation: 6-phase validation of highway and transit database structure
  • Highway Analysis: VMT, VHT, delay calculations by facility type and time period
  • Transit Analysis: Boarding volumes, ridership patterns, and service performance
  • Comprehensive Logging: Detailed progress reporting and diagnostic information

Performance Metrics

Highway Network Metrics

  • VMT: Vehicle Miles Traveled = Volume × Link Length
  • VHT: Vehicle Hours Traveled = Volume × Travel Time
  • Delay: Additional time due to congestion = Volume × (Congested Time - Free Flow Time)
  • Speed: Average travel speed = VMT / VHT

Transit Performance Metrics

Core Ridership Metrics: - Boardings: segment.transit_volume - Passengers boarding at each segment - Line Boardings: Sum(segment.transit_volume) - Total boardings per line - Daily Boardings: Sum across all time periods for all-day totals - Mode Boardings: Aggregated ridership by service type

Capacity and Service Metrics: - Line Capacity: 60 × vehicle.total_capacity ÷ headway (passengers/hour) - Seated Capacity: 60 × vehicle.seated_capacity ÷ headway (seated passengers/hour) - Service Frequency: 60 ÷ headway (vehicles per hour) - Load Factor: boardings ÷ line_capacity (utilization ratio)

Productivity and Efficiency: - Boardings per Route Mile: total_boardings ÷ route_length - Passenger Miles: boardings × segment_length - Revenue Miles: Total route distance operated - Passengers per Vehicle Hour: Service efficiency metric

Geographic Coverage: - Route Miles: Sum(segment.link.length) by line/mode - Service Area: Geographic extent of transit coverage - Stop Density: Stops per route mile - Network Connectivity: Transfer opportunities and accessibility

Usage Guidelines

For Developers

  • Reference attribute files when writing analysis code
  • Use consistent transit attribute naming: transit_volume is primary boarding attribute
  • Follow multimodal analysis patterns established in network summary script
  • Implement proper validation for both highway and transit databases

For Analysts

  • Use network summary script for comprehensive multimodal performance analysis
  • Access detailed attribute documentation for custom analysis
  • Validate results against expected ranges for Bay Area highway and transit networks
  • Consider both modes when evaluating transportation system performance

For Documentation Maintenance

  • Keep attribute files synchronized with database changes
  • Update transit mode classifications as service types evolve
  • Maintain consistency between highway and transit documentation standards
  • Document any changes to ridership data sources or calculation methods