Define the Problem Statement
- Create a polyline feature class using TomTom road network data and SWITRS/TIMS data that joins ‘high injury’ attributes from SWITRS/TIMS data to the road network.
- Provide a summary network which extracts ‘high injury’ cooridors from the entire TomTom road network for the Bay Area
- Summarize SWITRS/TIMS data by Census Block
Data Sources
- TomTom Other Areas (mn_oa03_BayArea)
- TomTom Street Network (mn_nw_BayArea)
- SWITRS/TIMS (2006-2016)
Analysis Parameters
| Variable | Description |
|---|---|
| killed | Number of people killed (includes pedestrians and motorists) |
| Sevinj | Number of people severly injured (includes pedestrians and motorists) |
| Accident Year | Year accident was reported |
| Longitude | Longitude (X coordinate) |
| Latitude | Latitude (Y coordinate) |
Methodology
Create Accident / Incident Point Features
- Make XY Accident Layer from SWITRS/TIMS (2006-2016) (Make XY Event Layer Tool)
- Copy XY Accident Layer to project GDB to create Feature Class
Create High Injury Network Polyline Features
- Definition Query on TomTom Street Network (FRC not in 8)
- Add TomTom road attributes to Accident Feature Class (Near Command)
- Run VZ_Road_Network_Incident_Summary script to create high injury network cooridors
- Aggregate road geometries
- Group by:
- Road Name (where available from TomTom Street Network)
- Highway shield # (Where available from TomTom Street Network)
- KPH (Speed limits as provided by TomTom (Converted to MPH for final output))
- Postal Code (Smallest available geographic identify where available from TomTom Street Network)
- County Name (from TomTom Street Network)
- County FIPS (from TomTom Street Network)
Create High Injury Polygons Features (Using Census Blocks)
TBD
Expected Outcomes (if any)?
Results
| MTC Vision Zero Memorandum | (Internal Agency Staff Only) |
Limitations
- Access to high fidelity, timely pedestrian injury fatality data for all roadways, including non-State-owned public roads.
- Access to detailed roadway characteristics such as speed and volume data, street lighting, and signalized intersections for roadways.
Need to Acquire Better Data Sources on:
Street Characteristics (Lanes, Lighting, Bike Lanes, Street etc),
Signalized Intersections,
Sidewalks,
Injuries,
Deaths,
Traffic Volume,
Traffic Speeds,
Time Period (24 hours),
Facility Types, (Local Streets to Arterials),
Bike Ped Counts,
Walk Score/ Bike Score Areas
Relevant Background Information
FHWA Roadway Safety Data Program
Vision Zero Los Angeles
Vision Zero Portland
Vision Zero SF