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 volumeauto_time
- Congested travel time (minutes)@free_flow_time
- Free flow travel time (minutes)@capacity
- Link capacity (vehicles/hour)@ft
- Facility type codelength
- 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 identifierline.mode.id
- Mode character (‘b’, ‘l’, ‘h’, ‘r’, ‘f’, ‘e’)line.headway
- Service headway in minutesline.vehicle.total_capacity
- Total vehicle capacityline["#description"]
- Line description/nameline["#src_mode"]
- Source mode for fare calculationsline["#faresystem"]
- Fare system ID (1-50)
Transit Segment Attributes ¶
segment.transit_volume
- PRIMARY passenger volume/boardingssegment.transit_boardings
- Alternative boarding attributesegment.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
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