The last 30 Years of US Motor Vehicle Collision Fatalities: Deaths, Fatal/VMT( per 100M), VMT(per 100M)

Click to enlarge this complicated and noisy chart . Deaths (Red) are measured nominally. Fatality rate (Blue) is Fatalities/100M VMT (Vehicle Miles Traveled). Vehicle Miles Traveled (Purple) is measured as 100M VMT.  To equate scales, fatalities are measured as numbered per the horizontal axis. VMT is effectively measured in trillions as 'y * 100M VMT',  while fatality/VMT is effectively measured in deaths per trillion  as 'y  / 100M VMT'.  These deaths include pedestrian and bicyclist deaths linked to moteor vehicle trauma. Source: https://en.m.wikipedia.org/wiki/Motor_vehicle_fatality_rate_in_U.S._by_year

Introduction: A series on Collision Data for Whatcom County and WA State

Please click to enlarge the charts below:

ABOVE: Screenshot for Governor's Highway Safety Association: US. Pedestrian Fatalities by Year

ABOVE: Screenshot from the FINAL-2018-PSAC-Annual-Report-.pdf for WA State

Click to enlarge the charts above. Below are four links to data posts from collision data for Whatcom County. In researching this topic I have surmised from the WSP Collision database the number of injuries and fatalities in Whatcom County over my 27 month study period (01/01/2017 - 04/01/2019). Because of the long data tables, these articles will not readable on a cell phone screen:

• https://www.bellinghampoliticsandeconomics.com/2019/03/cob-reported-collision-data-2017-2018.html
• https://www.bellinghampoliticsandeconomics.com/2019/04/wsp-collision-data-for-wm-county.html
• https://www.bellinghampoliticsandeconomics.com/2019/04/wsp-collision-data-for-wm-county_13.html
• https://www.bellinghampoliticsandeconomics.com/2019/04/wsp-collision-data-for-wm-county_15.html
• http://www.bellinghampoliticsandeconomics.com/2019/04/the-last-30-years-of-us-motor-vehicle.html

WSP Collision Data for WM County 01/01/2017 - 04/01/2019: A look at "Yield" Citations in Collisions

From the WSP Collision Data for Whatcom County, I am doing my best to summarize the 968 unique 'Citation Charges' from the 7,174 Whatcom County Collisions I am tracking for the 27 month period covering 01/01/2017 - 04/01/2019. "Yield" citations play a big part in collisions in Whatcom. It may be useful to spell out in detail for drivers obligations under the law. Below I parse the top 50 “Yield” violations and then the top 15 "Yield" violations for "intersection", "driveway" ,"ped" ,"stop", "left" and (at bottom) a regex for '4' which gives us the RCW reference used by WSP officer on the scene. Rdata.table code is included for reference.

WSP Collision Data for WM County 01/01/2017 - 04/01/2019: Initial text analysis of MV_Drvr_CitationCharge

From the WSP Collision Data for Whatcom County, I am doing my best to summarize the 968 unique 'Citation Charges' from the 7,174 Whatcom County Collisions I am tracking for the 27 month period covering 01/01/2017 - 04/01/2019 . I have developed some text mining techniques to summarize the 'top citations' and I am interested if this information gives me insight into Whatcom County driver behavior in collisions. If I had to summarize my findings to date, I would comment that the top cause of collisions or dangerous driver behavior can be attributed to:

WSP Collision Data for WM County 01/01/2017 - 04/01/2019

These are stats from the WSP Collision Analysis Tool. The query interface at https://fortress.wa.gov/wsp/collisionanalysistool generates an amazing amount of information on collisions in the state of WA. Some of the address and locations needs some consolidation for cross table output. This data is for WM County from 01/01/2017 - 04/01/2019. I leave the rdata.table commands in place for some of these queries. The WSP Collision Analysis Tool generates a ton of good data. Some in simple and also a more advanced option. It's not perfect and requites some munging. It's just better data than any other motor vehicle trauma and collision interface I have seen. I like this data because I get the real feel when working with it of an officer filling out data on site. I think for this reason, the advanced data interface could be curated and aggregated for productive machine learning routines. This is under construction as of 4/5/2019 and I will be particularly working on this post.  These tables are best not viewed on a cell phone.


CrashSummary1[,.N,.(InjurySeverity)][order(-N)]
             InjurySeverity    N
1:      No Injury Collision 4964
2:   Minor Injury Collision 1681
3: Unknown Injury Collision  385
4: Serious Injury Collision  103
5:          Fatal Collision   41