Crash Trends in the MAG Region, 1999 - 2012

Crash Type Yearly Monthly Weekday Hourly 2012 Collision
Manner
Injuries + Fatalities
Per 100K Population
Injuries + Fatalities
on Arterials
& Local Roads
All 1999-2012 2012 2012 2012 All, Fatal, Injury NA 1999-2012
Vehicle - Pedestrian 1999-2012 2012 2012 2012 NA 2012, 2008-2012 1999-2012
Vehicle - Bicycle 1999-2012 2012 2012 2012 NA 2012, 2008-2012 1999-2012

 

 
 

Urban Freeway System

Crash Severity Annual Totals Crash Rates
All 1999-2012 1999-2011
Injured 1999-2012 1999-2011
Killed 1999-2012 1999-2011
Injured OR Killed 1999-2012 1999-2011

 

 
 
 
 
 

Arterial and Local Road Crashes

Crash Type All Crashes Intersection Crashes Segment Crashes
All 1999-2012 1999-2012 1999-2012
Vehicle - Pedestrian 1999-2012 1999-2012 1999-2012
Vehicle - Bicycle 1999-2012 1999-2012 1999-2012

 

 
 
 
 

Traffic Violations and Seat Belt Usage

Age Groups Fatalities Injuries
Teen Driver (15-19 years) 1999-2012 2010-2012 1999-2012 2010-2012
Older Driver (65+ years) 1999-2012 2010-2012 1999-2012 2010-2012

 

 

Comparison of MAG Region to the Rest of Arizona

Crash Type All Crashes Injuries Fatalities
All 1999-2012 1999-2012 1999-2012
Vehicle - Pedestrian 1999-2012 1999-2012 1999-2012
Vehicle - Bicycle 1999-2012 1999-2012 1999-2012

 

 
 
 
 

Crash Trends in the MAG Region – Notes:

  1. The crash data used in this analysis comes from the ALISS database maintained by ADOT

  2. Only crashes that involve at least one motorized vehicle and result in either an injury or property damages of at least $1000 are reported by police for inclusion in ALISS

  3. Freeway crash rates are calculated using the total number of vehicle miles traveled


  4. The annual freeway crash total trends for Loops 101 and 202, between 1999 and 2007, also reflect the gradually increasing freeway mileage during the construction phases of these freeway corridors.


  5. The Vehicle-Pedestrian and Vehicle-Bicycle crash statistics are presented as a ratio, based on 100,000 population, for each local jurisdiction. An inherent assumption here for gauging road risk is that the level of pedestrian/bicyclist activity in each community is directly proportional to the population. Although this is not a perfect metric, this is the best we can do at this time due to lack of pedestrian and bicyclist data.