Arizona Crash Facts 2014

Adot has released Crash Facts 2014 in early June (of 2015), as usual/expected; and I received the database from them very promptly. I have updated the graphical crash map so it now has data from 2009-2014 for ped-MV and bike-MV crashes.

The overall number of crashes ticked up  (unless otherwise stated, all figures are year-over-year; 2013 vs. 2014; and are as was published in Crash Facts 2014 when it was published June 2015):

  • number of MV crashes: 107,477 vs. 109,554  up  modestly 1.93% [1]
  • all Fatalities: 844 vs. 774 sharp drop of 8.83% [2]
  • Total Injuries: 50,389 vs. 50,890 almost flat at up 0.99% [3]

The two most closely-watched traffic safety metrics, the number of fatalities per 100M Vehicle Miles Traveled (VMT), and per 100K population are not yet available but even after the sharp drop will remain  worse for Arizonans than for the US overall.

The results for cyclists showed improvement compared to 2013 but are rather unexplainable —

  • the number of bike-MV crashes:  2,039 vs. 1742 . down  sharply, 15%  [4]
  • number of cyclists injured: 1,679 vs. 1459 down sharply 13% [5]
  • The number of fatalities at 28 was one fewer than the last year’s 29  — but there’s still something unresolved about 2013 fatalities that I’m guessing won’t get straightened out until the FARS final 2013 gets released, normally in December of 2015. In any event the average yearly toll has been about 24. Fatalities, being relatively rare, have quite wide variation, making it hard to discern trends. For example in the most recent 10 year period there have been as many as 36 (in 2005) and as few as 18 (last year). More details on each AZ fatality here.

Longer Trends for cyclist/ped

I have a spreadsheet that tracks  # of cyclist injuries and fatalities for 2001-2014. The number of cyclists injured this past year, 1,459, is well below the 14-year average of 1,616; This drop is a notable mystery.

More broadly, we have no good exposure data; though we can say in that time (which reflects 2001 thru 2013), the population of AZ has grown 24% and driving has increased 19%.  AzStats.xls (current as of 2014 data) or web-viewable on google drive (the google drive version only current thru 2013). Also see the section on long-term trends section of last year’s 2013-data roundup.

There are a series of results at azbikelaw.org/contrib/asdm including classification of each table, and bsap-like results compared over the six most recent years  bsap-data-2014.txt

The Drop in reported Cyclist Crashes?

 

IncidentYear count(*)
2009 2022
2010 1942
2011 1944
2012 2164
2013 2071
2014 1761

 

(these numbers vary slightly, and will be a tiny bit higher, from those published, but you get the idea) Why the drop? Here is a 6 year history… I wanted to check city-by-city, below presented inelegantly is the year-over-year list.

The drop was very broad-based, virtually all larger agencies reports significant declines — Chandler, Gilbert, Glendale, Mesa, Phoenix, Scottsdale, Tempe, Tucson. Only Flagstaff saw any increase (it was a  small change), among the larger agencies. Why?

 

IncidentYear name count(*)
2013 APACHE JUNCTION 17
2014 APACHE JUNCTION 16
2013 AVONDALE 21
2014 AVONDALE 17
2014 BENSON 1
2013 BUCKEYE 6
2014 BUCKEYE 4
2013 BULLHEAD CITY 7
2014 BULLHEAD CITY 4
2013 CAMP VERDE 1
2014 CAMP VERDE 2
2013 CAREFREE 1
2014 CAREFREE 2
2013 CASA GRANDE 19
2014 CASA GRANDE 16
2013 CAVECREEK 1
2014 CAVECREEK 2
2013 CHANDLER 104
2014 CHANDLER 65
2013 CHINO VALLEY 1
2013 CLIFTON 1
2013 COLORADO CITY 1
2013 COOLIDGE 3
2014 COOLIDGE 4
2013 COTTONWOOD 3
2014 COTTONWOOD 4
2013 DOUGLAS 3
2013 EL MIRAGE 10
2014 EL MIRAGE 6
2013 ELOY 1
2014 ELOY 1
2013 FLAGSTAFF 64
2014 FLAGSTAFF 68
2013 FLORENCE 1
2013 FOUNTAIN HILLS 1
2013 GILBERT 73
2014 GILBERT 58
2013 GLENDALE 85
2014 GLENDALE 74
2013 GLOBE 1
2014 GLOBE 1
2013 GOODYEAR 12
2014 GOODYEAR 12
2013 GUADALUPE 2
2014 GUADALUPE 5
2013 HOLBROOK 1
2014 HOLBROOK 3
2013 KINGMAN 10
2014 KINGMAN 11
2013 LAKE HAVASU CITY 9
2014 LAKE HAVASU CITY 1
2014 LITCHFIELD PARK 2
2013 MARANA 6
2014 MARANA 4
2013 MARICOPA 4
2014 MARICOPA 5
2013 MESA 193
2014 MESA 163
2013 NOGALES 2
2014 NOGALES 2
2013 ORO VALLEY 19
2014 ORO VALLEY 11
2013 PAGE 1
2013 PARADISE VALLEY 3
2014 PARADISE VALLEY 5
2013 PARKER 1
2013 PAYSON 5
2014 PAYSON 5
2013 PEORIA 38
2014 PEORIA 41
2013 PHOENIX 521
2014 PHOENIX 453
2013 PINETOP 1
2014 PINETOP 1
2013 PRESCOTT 13
2014 PRESCOTT 12
2013 PRESCOTT VALLEY 7
2014 PRESCOTT VALLEY 5
2013 QUARTZSITE 1
2013 QUEEN CREEK 1
2014 QUEEN CREEK 2
2014 RED ROCK 1
2013 SAHUARITA 2
2014 SAHUARITA 4
2013 SAN LUIS 4
2014 SAN LUIS 3
2013 SCOTTSDALE 96
2014 SCOTTSDALE 74
2013 SEDONA 11
2014 SEDONA 3
2013 SHOW LOW 1
2014 SHOW LOW 3
2013 SIERRA VISTA 19
2014 SIERRA VISTA 7
2013 SNOWFLAKE 3
2013 SOUTH TUCSON 2
2014 SOUTH TUCSON 4
2014 SPRINGERVILLE 1
2013 SURPRISE 7
2014 SURPRISE 8
2013 TEMPE 240
2014 TEMPE 214
2013 TOLLESON 3
2014 TOLLESON 3
2013 TUCSON 224
2014 TUCSON 161
2013 UNSPECIFIED_999 160
2014 UNSPECIFIED_999 148
2014 WICKENBURG 1
2013 WILLCOX 2
2014 WILLIAMS 1
2014 YOUNGTOWN 2
2013 YUMA 22
2014 YUMA 35

 

 

SELECT IncidentYear,count(*) FROM ( 2012_incident AS i JOIN 2012_person AS p_bike ON i.IncidentID = p_bike.IncidentID) LEFT OUTER JOIN LOVCity ON i.CityId = LOVCity.id WHERE p_bike.ePersonType = 'PEDALCYCLIST' GROUP BY 1;
SELECT IncidentYear, LOVCity.name ,count(*)
FROM (
incident AS i JOIN person AS p_bike ON i.IncidentID = p_bike.IncidentID)
 LEFT OUTER JOIN LOVCity ON i.CityId = LOVCity.id
WHERE p_bike.ePersonType = 'PEDALCYCLIST' AND (IncidentYear=2013 OR IncidentYear=2014) GROUP BY 2,1;

by the way, to get incident counts (instead of person counts) for all years, for all cities do:
SELECT LOVCity.name, IncidentYear ,count(*) FROM incident i LEFT OUTER JOIN LOVCity ON i.CityId = LOVCity.id 
WHERE EXISTS (SELECT 1 FROM unit u WHERE u.IncidentID=i.IncidentID AND u.eUnitType IN ('PEDALCYCLIST')) GROUP BY 1, 2;

Footnotes

Note about published vs. database: the database I have isn’t updated (it’s frozen as of June of the year following) and incidents continue to trick in over the next year…

[1] per database vs. published; 2013 figure is  103 greater than database; this is typically due to a small number of incidents that trickle in after the database is frozen. The 2014 number, happily matches.

select count(1) from 2014_incident; => 107374, 109554

[2] totals match, which is slightly misleading, e.g. pedalcyclists for 2013 were revised, meaning some other category had to change.

SELECT count(1) FROM 2014_person WHERE eInjuryStatus LIKE "FATAL%"; => 844 , 774

[3] per database vs. published; 2013 figure is  92 greater than database. The 2014 number matches exactly. Point of order: they don’t count fatalities as injuries.

select count(1) from 2014_person WHERE InjuryStatus BETWEEN 2 AND 4; => 50297, 50890

[4] the 2013 figure matches exactly, which seems odd/wrong/unlikely because of stragglers. The 2014 figure matches exactly as expected

SELECT count(*) FROM 2014_incident i WHERE EXISTS (SELECT 1 FROM 2014_unit u WHERE u.IncidentID=i.IncidentID AND u.eUnitType IN ('PEDALCYCLIST')); => 2039, 1742

[5] the 2013 figure matches exactly, which seems odd/wrong/unlikely. While the 2014 figure is 7 higher than the database, which is also odd because 2014 numbers should agree.

select count(1) from 2014_person WHERE InjuryStatus BETWEEN 2 AND 4 AND ePersonType = 'PEDALCYCLIST'; => 1679, 1466

 

 

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