database improvements for motor vehicle/bicycle crash analysis - electronic drawing tablet

by:ITATOUCH     2020-04-29
database improvements for motor vehicle/bicycle crash analysis  -  electronic drawing tablet
Cycling in the background is healthy, but it needs to be safer for more people.
The police collision template is designed to report collisions between motor vehicles, but does not report collisions between vehicles/bicycles.
If the bike is a bookcrash-
The scene details exist and they are not entered into the spreadsheet.
Purpose to evaluate which bicyclescrash-
Scene data can be added to a spreadsheet for analysis.
Methods the warning templates of 50 states were analyzed.
Report on 3350 motor vehicle/bicycle crashes (2011)
Got the New York City area and 300 cases (
With drawings and on roads with shared lanes, bike lanes and no bicycle regulations).
New bicycle repainted in the crash-crash-
The scene details are encoded and entered into an existing spreadsheet.
The association between the severity of injury and the bikecrash-
Scenario code is evaluated using multivariate logistic regression.
As a result, the police template only includes pedals-
Bicycles and helmetsBicycle-crash-
The scene encoding variables of the template can include: 4 bicycle environments, 18 vehicle impacts-points (opened-
Doors and mirrors)
4 bike impact-
Points, motor vehicle/bicycle collision mode, bicycle environment and bicycle/related motor vehicle categories.
A test that included these variables showed that, with a slightly injured bicycle as a control group, people riding bicycles on roads off the driveway were less likely to be seriously injured (OR, 0. 40, 95% CI 0. 16 to 0. 98)
Compared with people who ride bicycles without bicycle facilities.
Conclusion additional bikes should be included in the police Templatecrash-
Enter the scene code for the spreadsheet.
Collision analysis can then be performed on bicycle environment, motor vehicle potential impact point/door/mirror, bicycle potential impact point, motor vehicle features, location and damage, including big data.
Cycling in the background is healthy, but it needs to be safer for more people.
The police collision template is designed to report collisions between motor vehicles, but does not report collisions between vehicles/bicycles.
If the bike is a bookcrash-
The scene details exist and they are not entered into the spreadsheet.
Purpose to evaluate which bicyclescrash-
Scene data can be added to a spreadsheet for analysis.
Methods the warning templates of 50 states were analyzed.
Report on 3350 motor vehicle/bicycle crashes (2011)
Got the New York City area and 300 cases (
With drawings and on roads with shared lanes, bike lanes and no bicycle regulations).
New bicycle repainted in the crash-crash-
The scene details are encoded and entered into an existing spreadsheet.
The association between the severity of injury and the bikecrash-
Scenario code is evaluated using multivariate logistic regression.
As a result, the police template only includes pedals-
Bicycles and helmetsBicycle-crash-
The scene encoding variables of the template can include: 4 bicycle environments, 18 vehicle impacts-points (opened-
Doors and mirrors)
4 bike impact-
Points, motor vehicle/bicycle collision mode, bicycle environment and bicycle/related motor vehicle categories.
A test that included these variables showed that, with a slightly injured bicycle as a control group, people riding bicycles on roads off the driveway were less likely to be seriously injured (OR, 0. 40, 95% CI 0. 16 to 0. 98)
Compared with people who ride bicycles without bicycle facilities.
Conclusion additional bikes should be included in the police Templatecrash-
Enter the scene code for the spreadsheet.
Collision analysis can then be performed on bicycle environment, motor vehicle potential impact point/door/mirror, bicycle potential impact point, motor vehicle features, location and damage, including big data.
Methods Study status and MMUCC crash report template to analyze data in New York Motor Vehicle/bike crash report text and drawings to determine which bikescrash-
Scene data can be added to the police accident report template as a spreadsheet encoding variable for improved security analysis.
The crash report template content comparison template is obtained from motor vehicles, state websites and various state departments with templates.
31. 32 templates for research in order to obtain information (
That is to say, what information is requiredin-
Spaces and small boxes with code)
Includes 49 full crash templates with dates 2000-2013, 2 full crash templates with dates 1988-1991, and MMUCC templates.
Then, compare the status template to determine which bikescrash-
Request or not request scenario information on each status template.
New York Motor Vehicle/bicycle accident selected for analysis (300 cases)
Obtained a full crash report of 3350 motor vehicle/bicycle collisions in the New York area in 2011 with x/y coordinates (crash location)
New York State Department of Transport (NYSDOT).
Using the geographic code provided in the spreadsheet file, we first identified motor vehicle/bicycle accidents that occurred only in New York (n=1080).
In the map of bicycle facilities in New York City, a map was generated specifying roads for four different bicycle environments ((1)roads; (2)sharrows—
Name of bicycle template on the street; (3)bike lanes; and (4)cycle tracks—
Guardrail next to the sidewalk, special path for bicycles)
The crash site is superimposed on this map.
From NYSDOT, a full copy of the report was requested for 46 crashes on sharrows (
All sharrow crashes)
, 79 crashes on roads with bike lanes (
Crash of all cycle tracks)
188 crashes on roads with bike lanes (
Crash on all bike lanes)
In addition, using the probability bike scheme, 188 accidents occurred on roads without bicycle facilities to match the number of accidents on roads with bicycle lanes (n=501 crashes).
NYSDOT sent us 600 full crash reports (
Private information for editors)
To better guarantee that we will have 300 crash reports with charts (
83 of the 600 crash reports did not have a crash map).
Up to 300 accidents are due to the amount of time it takes to re-analyze each accident.
For analysis, the selected crashes include all crashes on the road with sharrow (n=44)
, All crashes on roads with bike lanes (n=65)
, And use the probability sampling procedure to randomly sample collisions on roads with bicycle lanes (n=95)
And random samples of crashes on roads without bicycle regulations (n=96).
Using the text and graphics in the crash report and Google street view, motor vehicle/bicycle collisions are redrawn due to collisions, turns, and inside and outside the environment, each of the 300 motor vehicle/bicycle accidents has been redrawn, including the street and its direction, number of lanes, parking, bike environment (if any), car location and bike location (figure 2).
Then, an X was drawn to identify the collision position on the car and bike and a Google Street View saved in the collision scene was drawn.
Download figureOpen in the new tabDownload powerpoint figure 2 to draw a vehicle/bike crash map.
The picture shows a one-way street in the north with three lanes of traffic (Up arrow symbol)
, Bus lane, bicycle lane, cars parked parallel on both sides (□).
The picture also shows a one-way street, a lane in the East (
Right arrow symbol)
, Bicycle lanes, cars parked in parallel on both sides (□).
The vehicle was drawn into a rectangular shape and the bike hit the back door opened on the driver's side.
Various charts describing the direction of the turn and the position of the impact are collected from the status template and the web (head-
Collision of two arrows pointing to each other)
And a similar turn/impact chart was merged.
Different turns/impact maps match the 300 redrawn collision maps (
Including vehicle and bicycle steering)
, Group all similar charts most relevant to motor vehicle/bike collision turns to get manageable numbers (10).
For example, if only two of the 300 bike collision scenarios are related to the turn/collision chart, then both cases will be merged with another similar scenario (figure 3).
Download the new tabDownload figureOpen powerpointFigure3 crash mode encoding (turn/impact).
If there is an environment, the location of bicyclist is also related to the cycling environment.
Then, if the person riding the bike is :(1)
On roads that do not have a designated bicycle environment; (2)
On a road with sharks. (3)
Streets and bicycle lanes with bicycle lanes; (4)
On a street with a bicycle lane, but outside the lane; (5)
On the street and in the bicycle lane where there is a bicycle lane; and (6)
On the street with a bike lane, but outside the bike lane.
The 300 redraw vehicle/bike collision then provides the following for each collision :(1)
Motor vehicle impact point; (2)
Bicycle impact point; (3)
Steering direction of vehicles and bicycles (crash patterns); and (4)
The location of Bicyclist and the entrance and exit of the bicycle environment.
The top 11 in VINs and motor vehicle configuration 17 Motor Vehicle Code VIN were required to display general motor vehicle features in 300 crashes, but not the owner's identity.
Using the numbers and pictures of motor vehicles on the network, the type of motor vehicle is re-classified as bicycle collision/Related features according to expert judgment ((1)car sedan; (2)
(Car)SUV); (3)hatchback; (4)van; (5)pick-up truck; (6)medium truck; (7)large truck; and (8)bus).
The content can then be used for analysis to determine whether a type of vehicle is more likely to collide with a bicycle.
The content in the different motor vehicle/bicycle crash report formats from NYSDOT obtained collision reports available to the public in all three formats.
These reports include :(1)
Original warning report with text and chart (
Private information for editors); (2)spreadsheet; and (3)
Shorter typing report
With these three formats, we can determine and compare the level of detail in each format.
Statistical analysis using new bicyclescrash-
300 scene variables entered in the existing spreadsheet for New York Vehicle/bicycle accidents.
This analysis provides an opportunity to begin an assessment of whether these bicycles are availablecrash-
Scene variables may be worth it.
The frequency of motor vehicle impact points, bicycle environment, bicycles inside and outside the environment, types of motor vehicles and collision modes (
Transfer/impact chart)were analysed.
Because the existing spreadsheet includes variables reported by the police for minor injuries to cyclists and seriously injured cyclists, it's time
In order to obtain the number of bicycles on all streets of New York, the light injury bicycle was used as a control group and the serious injury/death bicycle was used as a case group.
According to the number of injuries/deaths, then the group consists of: Group 1 (control group)—
Including non-minor injuries
Disability injury (n=99); and Group 2 (case group)—
Serious injuries include incapacitated injuries, possible injuries, and deaths (n=191).
By T-test of quantitative variables and x-2 test of qualitative variables, the variables were compared according to the type of injury.
Logistic regression was also performed on independent variables estimated to have seriously affected the injury;
There are 95% CIs ORs reported.
Two models were constructed to check the association between potential impact points of a motor vehicle, input/output (
Whether the collision occurs inside or outside the bike lane or the bike lane)
And the severity of the injury
Models 1A and 1B are unadjusted models.
In model 2A, potential confounding factors, including age, were adjusted (years)
Gender, road conditions (
Dry, wet, muddy, snow/ice, snow mud, flood, others)
, Collision mode, type of motor vehicle (
Motorcycle, car/Van
Other, unknown) trucks, buses, bicycles, pedestrians
Conditions of light (
Day, dawn, dusk, darkness
The road is bright and dark. road unlighted)
And Crossroads
We performed sensitivity analysis by excluding collisions where vehicles are listed as unknown in existing spreadsheets (Models 1B and 2B).
Thus, the 2B model does not include possible hitsand-
The operation crashes, where the driver of the vehicle will leave the scene.
Spss v was used for all analyses. 21 (
Chicago, Illinois, USA).
The crash report template content comparison template is obtained from motor vehicles, state websites and various state departments with templates.
31. 32 templates for research in order to obtain information (
That is to say, what information is requiredin-
Spaces and small boxes with code)
Includes 49 full crash templates with dates 2000-2013, 2 full crash templates with dates 1988-1991, and MMUCC templates.
Then, compare the status template to determine which bikescrash-
Request or not request scenario information on each status template.
New York Motor Vehicle/bicycle accident selected for analysis (300 cases)
Obtained a full crash report of 3350 motor vehicle/bicycle collisions in the New York area in 2011 with x/y coordinates (crash location)
New York State Department of Transport (NYSDOT).
Using the geographic code provided in the spreadsheet file, we first identified motor vehicle/bicycle accidents that occurred only in New York (n=1080).
In the map of bicycle facilities in New York City, a map was generated specifying roads for four different bicycle environments ((1)roads; (2)sharrows—
Name of bicycle template on the street; (3)bike lanes; and (4)cycle tracks—
Guardrail next to the sidewalk, special path for bicycles)
The crash site is superimposed on this map.
From NYSDOT, a full copy of the report was requested for 46 crashes on sharrows (
All sharrow crashes)
, 79 crashes on roads with bike lanes (
Crash of all cycle tracks)
188 crashes on roads with bike lanes (
Crash on all bike lanes)
In addition, using the probability bike scheme, 188 accidents occurred on roads without bicycle facilities to match the number of accidents on roads with bicycle lanes (n=501 crashes).
NYSDOT sent us 600 full crash reports (
Private information for editors)
To better guarantee that we will have 300 crash reports with charts (
83 of the 600 crash reports did not have a crash map).
Up to 300 accidents are due to the amount of time it takes to re-analyze each accident.
For analysis, the selected crashes include all crashes on the road with sharrow (n=44)
, All crashes on roads with bike lanes (n=65)
, And use the probability sampling procedure to randomly sample collisions on roads with bicycle lanes (n=95)
And random samples of crashes on roads without bicycle regulations (n=96).
Using the text and graphics in the crash report and Google street view, motor vehicle/bicycle collisions are redrawn due to collisions, turns, and inside and outside the environment, each of the 300 motor vehicle/bicycle accidents has been redrawn, including the street and its direction, number of lanes, parking, bike environment (if any), car location and bike location (figure 2).
Then, an X was drawn to identify the collision position on the car and bike and a Google Street View saved in the collision scene was drawn.
Download figureOpen in the new tabDownload powerpoint figure 2 to draw a vehicle/bike crash map.
The picture shows a one-way street in the north with three lanes of traffic (Up arrow symbol)
, Bus lane, bicycle lane, cars parked parallel on both sides (□).
The picture also shows a one-way street, a lane in the East (
Right arrow symbol)
, Bicycle lanes, cars parked in parallel on both sides (□).
The vehicle was drawn into a rectangular shape and the bike hit the back door opened on the driver's side.
Various charts describing the direction of the turn and the position of the impact are collected from the status template and the web (head-
Collision of two arrows pointing to each other)
And a similar turn/impact chart was merged.
Different turns/impact maps match the 300 redrawn collision maps (
Including vehicle and bicycle steering)
, Group all similar charts most relevant to motor vehicle/bike collision turns to get manageable numbers (10).
For example, if only two of the 300 bike collision scenarios are related to the turn/collision chart, then both cases will be merged with another similar scenario (figure 3).
Download the new tabDownload figureOpen powerpointFigure3 crash mode encoding (turn/impact).
If there is an environment, the location of bicyclist is also related to the cycling environment.
Then, if the person riding the bike is :(1)
On roads that do not have a designated bicycle environment; (2)
On a road with sharks. (3)
Streets and bicycle lanes with bicycle lanes; (4)
On a street with a bicycle lane, but outside the lane; (5)
On the street and in the bicycle lane where there is a bicycle lane; and (6)
On the street with a bike lane, but outside the bike lane.
The 300 redraw vehicle/bike collision then provides the following for each collision :(1)
Motor vehicle impact point; (2)
Bicycle impact point; (3)
Steering direction of vehicles and bicycles (crash patterns); and (4)
The location of Bicyclist and the entrance and exit of the bicycle environment.
The top 11 in VINs and motor vehicle configuration 17 Motor Vehicle Code VIN were required to display general motor vehicle features in 300 crashes, but not the owner's identity.
Using the numbers and pictures of motor vehicles on the network, the type of motor vehicle is re-classified as bicycle collision/Related features according to expert judgment ((1)car sedan; (2)
(Car)SUV); (3)hatchback; (4)van; (5)pick-up truck; (6)medium truck; (7)large truck; and (8)bus).
The content can then be used for analysis to determine whether a type of vehicle is more likely to collide with a bicycle.
The content in the different motor vehicle/bicycle crash report formats from NYSDOT obtained collision reports available to the public in all three formats.
These reports include :(1)
Original warning report with text and chart (
Private information for editors); (2)spreadsheet; and (3)
Shorter typing report
With these three formats, we can determine and compare the level of detail in each format.
Using the text and graphics in the crash report and Google street view, motor vehicle/bicycle collisions are redrawn due to collisions, turns, and inside and outside the environment, each of the 300 motor vehicle/bicycle accidents has been redrawn, including the street and its direction, number of lanes, parking, bike environment (if any), car location and bike location (figure 2).
Then, an X was drawn to identify the collision position on the car and bike and a Google Street View saved in the collision scene was drawn.
Download figureOpen in the new tabDownload powerpoint figure 2 to draw a vehicle/bike crash map.
The picture shows a one-way street in the north with three lanes of traffic (Up arrow symbol)
, Bus lane, bicycle lane, cars parked parallel on both sides (□).
The picture also shows a one-way street, a lane in the East (
Right arrow symbol)
, Bicycle lanes, cars parked in parallel on both sides (□).
The vehicle was drawn into a rectangular shape and the bike hit the back door opened on the driver's side.
Various charts describing the direction of the turn and the position of the impact are collected from the status template and the web (head-
Collision of two arrows pointing to each other)
And a similar turn/impact chart was merged.
Different turns/impact maps match the 300 redrawn collision maps (
Including vehicle and bicycle steering)
, Group all similar charts most relevant to motor vehicle/bike collision turns to get manageable numbers (10).
For example, if only two of the 300 bike collision scenarios are related to the turn/collision chart, then both cases will be merged with another similar scenario (figure 3).
Download the new tabDownload figureOpen powerpointFigure3 crash mode encoding (turn/impact).
If there is an environment, the location of bicyclist is also related to the cycling environment.
Then, if the person riding the bike is :(1)
On roads that do not have a designated bicycle environment; (2)
On a road with sharks. (3)
Streets and bicycle lanes with bicycle lanes; (4)
On a street with a bicycle lane, but outside the lane; (5)
On the street and in the bicycle lane where there is a bicycle lane; and (6)
On the street with a bike lane, but outside the bike lane.
The 300 redraw vehicle/bike collision then provides the following for each collision :(1)
Motor vehicle impact point; (2)
Bicycle impact point; (3)
Steering direction of vehicles and bicycles (crash patterns); and (4)
The location of Bicyclist and the entrance and exit of the bicycle environment.
The top 11 in VINs and motor vehicle configuration 17 Motor Vehicle Code VIN were required to display general motor vehicle features in 300 crashes, but not the owner's identity.
Using the numbers and pictures of motor vehicles on the network, the type of motor vehicle is re-classified as bicycle collision/Related features according to expert judgment ((1)car sedan; (2)
(Car)SUV); (3)hatchback; (4)van; (5)pick-up truck; (6)medium truck; (7)large truck; and (8)bus).
The content can then be used for analysis to determine whether a type of vehicle is more likely to collide with a bicycle.
The content in the different motor vehicle/bicycle crash report formats from NYSDOT obtained collision reports available to the public in all three formats.
These reports include :(1)
Original warning report with text and chart (
Private information for editors); (2)spreadsheet; and (3)
Shorter typing report
With these three formats, we can determine and compare the level of detail in each format.
Statistical analysis using new bicyclescrash-
300 scene variables entered in the existing spreadsheet for New York Vehicle/bicycle accidents.
This analysis provides an opportunity to begin an assessment of whether these bicycles are availablecrash-
Scene variables may be worth it.
The frequency of motor vehicle impact points, bicycle environment, bicycles inside and outside the environment, types of motor vehicles and collision modes (
Transfer/impact chart)were analysed.
Because the existing spreadsheet includes variables reported by the police for minor injuries to cyclists and seriously injured cyclists, it's time
In order to obtain the number of bicycles on all streets of New York, the light injury bicycle was used as a control group and the serious injury/death bicycle was used as a case group.
According to the number of injuries/deaths, then the group consists of: Group 1 (control group)—
Including non-minor injuries
Disability injury (n=99); and Group 2 (case group)—
Serious injuries include incapacitated injuries, possible injuries, and deaths (n=191).
By T-test of quantitative variables and x-2 test of qualitative variables, the variables were compared according to the type of injury.
Logistic regression was also performed on independent variables estimated to have seriously affected the injury;
There are 95% CIs ORs reported.
Two models were constructed to check the association between potential impact points of a motor vehicle, input/output (
Whether the collision occurs inside or outside the bike lane or the bike lane)
And the severity of the injury
Models 1A and 1B are unadjusted models.
In model 2A, potential confounding factors, including age, were adjusted (years)
Gender, road conditions (
Dry, wet, muddy, snow/ice, snow mud, flood, others)
, Collision mode, type of motor vehicle (
Motorcycle, car/Van
Other, unknown) trucks, buses, bicycles, pedestrians
Conditions of light (
Day, dawn, dusk, darkness
The road is bright and dark. road unlighted)
And Crossroads
We performed sensitivity analysis by excluding collisions where vehicles are listed as unknown in existing spreadsheets (Models 1B and 2B).
Thus, the 2B model does not include possible hitsand-
The operation crashes, where the driver of the vehicle will leave the scene.
Spss v was used for all analyses. 21 (
Chicago, Illinois, USA).
Analysis of the results of the New York State Police and MMUCC collision template and 300 motor vehicle/bicycle collisions (
Impact point, Crash mode, content inside and outside the environment, VINs, and report format)
Car/bike specific crash variables are shown as a spreadsheet-
Encoded data that can be used for analysis.
The content analysis of the existing collision report template of the National Police template shows that the pedal-cyclist (
Mark in non-down
Motor Vehicle 2)and helmet (
Except for three states with motorcycle helmets)
Standard but other bikescrash-
Include scene categories in inconsistency (table 1).
The drawing of the car has 8 to 16 potential impact points, but does not include open doors or side mirrors.
States with motorcycle/foot bike drawings include Nevada (
8 Potential impact points), Arizona (
6 Potential impact points)
, North Carolina and South Carolina (
4 Potential impact points).
Only a few states include pedals.
The action, position, reflective clothing, light, direction, or action of riding a bicycle.
Some states publish electronic citations using online templates, but some do not include the bike category.
Standardized MMUCC includes a motor vehicle diagram (
12 potential impact points)
Motorcycle drawings (
12 potential impact points)
Reflective clothes and lighting.
In the template that lists bicycle facilities, only bicycle lanes or shared use paths are included.
View this table: View the inline View popupTable1 status template with New York City bicycle information motor vehicle/bicycle accident selected for analysis of three hundred vehicle/bicycle accident Studies and Analysis in New York City, to test if there is a bikecrash-
Entering the scene variables of the collision spreadsheet may help to analyze vehicle/bicycle collisions.
Motor vehicle/bicycle collisions are redrawn due to environmental, impact points, and traffic accidents. Although the bicycle environment may exist, unless there is a side-path method, cyclists do not have to ride in these facilities (
Must ride in parallel bike environment).
New bike based-crash-
The number of scene codes, minor or severe crashes is different (table 2).
View this table: view the frequency of minor and serious injuries based on the new bikecrash-
Scene code for the bike *, since it is difficult to identify more than four potential impact points from the crash report, four potential impact points are identified (figure 1).
For motor vehicles, 18 possible impact points have been identified (
Include a of the mirror and B and c of the open door).
Before the bike (side 1)
And motor vehicle front (side 2)
The highest frequency of collisions and injuries (table 2).
A test was conducted to assess the usefulness of having these new bikescrash-
Enter the scene data into an existing spreadsheet. In Model 2B (
Not including possible strikes. and-
As a control group, people running and cycling suffered minor injuries)
People riding bicycles on roads with bicycle lanes are less likely to be seriously injured by people riding bicycles outside the lanes (OR, 0. 40, 95% CI 0. 16 to 0. 99)
Compared to cycling on roads without bicycle facilities (table 3).
View this table: View the inline View popuptable 3 OR and 95% CIs based on the bike facility and side collision of the motor vehicle under the combined similar turn/collision chart to determine if there is a serious injury, it is most likely that 300 collision maps have been compiled.
For example, all the heads
There was a motor vehicle/bicycle accident. (figure 3).
The highest frequency of motor vehicle/bicycle collision is the left-turn and side-slip motor vehicle (
Motor vehicles in the same direction as bicycles)(table 2).
VINs and motor vehicle configuration VINs and motor vehicle images allow the classification of eight different types of motor vehicles and sedans, including taxis, which are most prone to crash and serioustable 2).
The contents of the data in the different motor vehicle/bicycle collision report format for New York Motor Vehicle/bicycle collision can be requested in spreadsheet form, but for bicycles-crash-
Scene data, only body type (bicyclist)Type of vehicle (bicycle)
The spreadsheet input is coded with a helmet.
You can also get a crash report for typing, but this is a text version of the spreadsheet information.
Original edit crash report with text and graphics (
If the collision was drawn
Can be requested.
With this full crash report and Google Street View, the scene is time though
Consumption can be redrawn to reveal motor vehicles-
Side Collision of bicycle
If a bicycle is most likely to ride in a bicycle facility, or a unique motor vehicle/bicycle steering direction, a side collision will occur. These bicycle-crash-
Scenario data must then be entered into an existing spreadsheet for a more centralized analysis of bicyclist.
The content analysis of the existing collision report template of the National Police template shows that the pedal-cyclist (
Mark in non-down
Motor Vehicle 2)and helmet (
Except for three states with motorcycle helmets)
Standard but other bikescrash-
Include scene categories in inconsistency (table 1).
The drawing of the car has 8 to 16 potential impact points, but does not include open doors or side mirrors.
States with motorcycle/foot bike drawings include Nevada (
8 Potential impact points), Arizona (
6 Potential impact points)
, North Carolina and South Carolina (
4 Potential impact points).
Only a few states include pedals.
The action, position, reflective clothing, light, direction, or action of riding a bicycle.
Some states publish electronic citations using online templates, but some do not include the bike category.
Standardized MMUCC includes a motor vehicle diagram (
12 potential impact points)
Motorcycle drawings (
12 potential impact points)
Reflective clothes and lighting.
In the template that lists bicycle facilities, only bicycle lanes or shared use paths are included.
View this table: View the inline View popupTable1 status template with New York City bicycle information motor vehicle/bicycle accident selected for analysis of three hundred vehicle/bicycle accident Studies and Analysis in New York City, to test if there is a bikecrash-
Entering the scene variables of the collision spreadsheet may help to analyze vehicle/bicycle collisions.
Motor vehicle/bicycle collisions are redrawn due to environmental, impact points, and traffic accidents. Although the bicycle environment may exist, unless there is a side-path method, cyclists do not have to ride in these facilities (
Must ride in parallel bike environment).
New bike based-crash-
The number of scene codes, minor or severe crashes is different (table 2).
View this table: view the frequency of minor and serious injuries based on the new bikecrash-
Scene code for the bike *, since it is difficult to identify more than four potential impact points from the crash report, four potential impact points are identified (figure 1).
For motor vehicles, 18 possible impact points have been identified (
Include a of the mirror and B and c of the open door).
Before the bike (side 1)
And motor vehicle front (side 2)
The highest frequency of collisions and injuries (table 2).
A test was conducted to assess the usefulness of having these new bikescrash-
Enter the scene data into an existing spreadsheet. In Model 2B (
Not including possible strikes. and-
As a control group, people running and cycling suffered minor injuries)
People riding bicycles on roads with bicycle lanes are less likely to be seriously injured by people riding bicycles outside the lanes (OR, 0. 40, 95% CI 0. 16 to 0. 99)
Compared to cycling on roads without bicycle facilities (table 3).
View this table: View the inline View popuptable 3 OR and 95% CIs based on the bike facility and side collision of the motor vehicle under the combined similar turn/collision chart to determine if there is a serious injury, it is most likely that 300 collision maps have been compiled.
For example, all the heads
There was a motor vehicle/bicycle accident. (figure 3).
The highest frequency of motor vehicle/bicycle collision is the left-turn and side-slip motor vehicle (
Motor vehicles in the same direction as bicycles)(table 2).
VINs and motor vehicle configuration VINs and motor vehicle images allow the classification of eight different types of motor vehicles and sedans, including taxis, which are most prone to crash and serioustable 2).
The contents of the data in the different motor vehicle/bicycle collision report format for New York Motor Vehicle/bicycle collision can be requested in spreadsheet form, but for bicycles-crash-
Scene data, only body type (bicyclist)Type of vehicle (bicycle)
The spreadsheet input is coded with a helmet.
You can also get a crash report for typing, but this is a text version of the spreadsheet information.
Original edit crash report with text and graphics (
If the collision was drawn
Can be requested.
With this full crash report and Google Street View, the scene is time though
Consumption can be redrawn to reveal motor vehicles-
Side Collision of bicycle
If a bicycle is most likely to ride in a bicycle facility, or a unique motor vehicle/bicycle steering direction, a side collision will occur. These bicycle-crash-
Scenario data must then be entered into an existing spreadsheet for a more centralized analysis of bicyclist.
Motor vehicle/bicycle collisions are redrawn due to environmental, impact points, and traffic accidents. Although the bicycle environment may exist, unless there is a side-path method, cyclists do not have to ride in these facilities (
Must ride in parallel bike environment).
New bike based-crash-
The number of scene codes, minor or severe crashes is different (table 2).
View this table: view the frequency of minor and serious injuries based on the new bikecrash-
Scene code for the bike *, since it is difficult to identify more than four potential impact points from the crash report, four potential impact points are identified (figure 1).
For motor vehicles, 18 possible impact points have been identified (
Include a of the mirror and B and c of the open door).
Before the bike (side 1)
And motor vehicle front (side 2)
The highest frequency of collisions and injuries (table 2).
A test was conducted to assess the usefulness of having these new bikescrash-
Enter the scene data into an existing spreadsheet. In Model 2B (
Not including possible strikes. and-
As a control group, people running and cycling suffered minor injuries)
People riding bicycles on roads with bicycle lanes are less likely to be seriously injured by people riding bicycles outside the lanes (OR, 0. 40, 95% CI 0. 16 to 0. 99)
Compared to cycling on roads without bicycle facilities (table 3).
View this table: View the inline View popuptable 3 OR and 95% CIs based on the bike facility and side collision of the motor vehicle under the combined similar turn/collision chart to determine if there is a serious injury, it is most likely that 300 collision maps have been compiled.
For example, all the heads
There was a motor vehicle/bicycle accident. (figure 3).
The highest frequency of motor vehicle/bicycle collision is the left-turn and side-slip motor vehicle (
Motor vehicles in the same direction as bicycles)(table 2).
VINs and motor vehicle configuration VINs and motor vehicle images allow the classification of eight different types of motor vehicles and sedans, including taxis, which are most prone to crash and serioustable 2).
The contents of the data in the different motor vehicle/bicycle collision report format for New York Motor Vehicle/bicycle collision can be requested in spreadsheet form, but for bicycles-crash-
Scene data, only body type (bicyclist)Type of vehicle (bicycle)
The spreadsheet input is coded with a helmet.
You can also get a crash report for typing, but this is a text version of the spreadsheet information.
Original edit crash report with text and graphics (
If the collision was drawn
Can be requested.
With this full crash report and Google Street View, the scene is time though
Consumption can be redrawn to reveal motor vehicles-
Side Collision of bicycle
If a bicycle is most likely to ride in a bicycle facility, or a unique motor vehicle/bicycle steering direction, a side collision will occur. These bicycle-crash-
Scenario data must then be entered into an existing spreadsheet for a more centralized analysis of bicyclist. Discussion 50-
Analyze and pedal a status crash report template and MMUCC Template
Bicycles and helmets are the only bikes-
Relevant information is entered consistently as encoded data into the status spreadsheet for each crash.
For more analysis, a full crash report with text and graphics was obtained and redrawn using Google street view.
This process is artificial.
Intensively, the extracted variables are only available to this team, and with the construction of some circular tracks, Google Street View has changed during the analysis.
Because the crash report is being improved, bicyclist-crash-
Scene variables can be encoded with drop-on a police electronic tablet
Down template for motor vehicle/bicycle collisions and automatically upload to the status spreadsheet database.
Our research shows that new bicyclescrash-
Scenario variables may be useful for analysis, including: 4 bike environments (
Roads, sharks, bike trails and bike paths);
18 potential impact points for motor vehicles, including opening doors and mirrors;
4 Potential impact points of bicycles;
Whether in a bicycle environment or in a bicycle environment; 10 bicycle-crash-Scene mode (turn/impact);
Types of motor vehicles related to cycling.
With these new variables, there is a higher frequency of collisions in front of motor vehicles, in front of bicycles, without bicycle facilities, in cars and side skids.
Compared with the rider hitting the rear of the motor vehicle, the open motor vehicle doors and rear view mirrors lead to a higher risk of serious injury, compared with riding on roads without bicycle facilities, riding on roads with bicycle lanes, but not riding in the driveway, reducing the risk of serious injuries.
These analyses are possible as new bike variables are entered into existing spreadsheets that already contain categories of minor and serious/fatal injuries.
While it is valuable to use bike counts to study the situation around a collision, collecting bike counts from 33-36 can be difficult, especially if all the relevant streets need to be counted.
If these new bikescrash-
The scene variables are entered into the existing spreadsheet, and cycling can be analyzed against minor injuries and with serious injuries as a case.
While there is no such ideal comparison between injury and injury, using the data in the spreadsheet can at least be compared between minor and serious injuries.
New bike-crash-
The scene variables may be worth it because in the US the focus is on the bike lanes37, 38, while recent studies have shown the safety of the bike track.
Bicycles 33, 34, 39-41-crash-
Scenario spreadsheet code, associations can be found between the environment plus potential motor vehicle/bicycle impact points, motor vehicles and injuries, especially when combined with big data including emergency medical services, insurance, etc.
These bicycles 28, 42crash-
The scene data is informative because, unlike motor vehicles, bicyclist may be negatively affected by the open door 43 or the direction of the motor vehicle driving or turning.
In addition, 11% of car drivers saw bicycles before the car accident, while 68% of bike drivers saw cars.
47 if the environment and collision mode are coded for motor vehicle/bicycle collisions, the intersection can be better understood and designed to reduce the appearancebut-failed-to-see-errors.
48-50 better data lead to better analysis, which will also inform bicyclist and driver education work.
44, 51 with bicyclescrash-
The scene spreadsheet code, access to and use of data will be improved.
Now a research team can request the first 11 digits of VIN, but this information is only available to the team.
The current code includes chassis size, but many vehicle descriptors are not related to bike safety.
To protect users, motor vehicles have been improved, and perhaps, with the wider use of the 11-digit VIN and the different categories of motor vehicles, motor vehicles can also be designed to be better protected
It is recommended to add the bike category, but the specific content is less.
Researchers in Minnesota only recommend adding on-street and off-
Street bike facilities
52 analysis of bicycle collision types in North Carolina (2006–2010)
It is recommended to add the environment in the study of the Department of Transport of North Carolina, but only to add bicycle lanes or multi-purpose paths.
53. because there is no law of side roads that means bicycles can be driven on roads, bike lanes, or lanes, the code can recognize that the bike is in and out of the facility.
Since the invention of bicycles in 1890, traffic research has been focusing on motor vehicle risks, but bicycles are more vulnerable.
55-57 multiple data sets can be used to study mvc, 58, 59, and multiple data sets can also be used to study bicycle collisions.
Safety should not be the sole responsibility of cyclists, nor should it be the sole responsibility of them to choose a riding position or clothing when riding.
60 in addition to the coding of the helmet, bicycle lights should be coded with other bicycles 61, 62-crash-
Scene code that helps design the safest environment.
63 has the advantages of coding bicycles-crash-
The on-site data has been identified and it is still necessary to review.
Bicycle and Pedestrian collision data in North Carolina were analyzed and 78 collision types were developed.
53. in the event of a crash, the police may not be willing or able to enter multiple codes, but the bike --crash-scene drop-
The down menu on the spreadsheet can be a useful tool.
Recent crash templates are not available in all states, but some old ones contain useful information such as motorcycle/pedal loops with four potential crash points.
Analyze the accident details from New York's unique urban environment.
Due to the complexity of redrawing, the analysis involved only 300 crashes and only crashes with drawings were analyzed.
Due to the need to understand four different bike environments, the analysis is not a random sample of all motor vehicle/bike collisions, but in different environments, the maximum number of crashes in order to balance the sample size.
Bike counting is ideal for four environments, but this is a daunting task in New York.
Police have identified minor injuries and serious injuries, but these data allow minor injuries to be taken into control.
However, the sample size limits the power of each variable and the data allows inference of the value of the bikecrash-
The scene variable being encoded to be included in the spreadsheet.
Conclusion motor vehicles are similar to rectangles, bicycles are similar to straight lines, and motor vehicles are different from bicycles.
Data can be found in the full police crash report, but obtaining and extracting information is a Labor
Data-intensive, sometimes available only to researchers, changes in Google Street View.
Therefore, federal and state officials responsible for creating a template for state crash reports can consider including bicyclescrash-
The variable encoded by the scene spreadsheet can be used drop-
Down template for bike crash only.
The variables worth considering include: 4 bicycle environments;
18 potential impact points of cars (
4 Open Door positions and side mirrors included);
4 Potential impact points of bicycles;
Suitable for steering direction of motor vehicle/bicycle interaction;
Entrance and exit of bicycle environment;
Categories of motor vehicles related to cycling.
In future studies, more coding variables can be considered, especially the combination with big data.
Many states are making changes to the accident reporting template, but the focus remains on motor vehicles.
There is detailed information in the text and drawing of individual reports, but the analysis takes quite a long time.
However, Google Street View may change over the next few years, eliminating the recognition of the bike environment.
This study adds vehicle/bicycle collision variables that can be entered into spreadsheets, including 4 bicycle environments, 18 potential collision points for motor vehicles (
Open the door and mirror)
, 4 Potential impact points for bicycles, 10 bicycles-crash-
Scene mode, bicycle environment and access of bicycle-related motor vehicle types.
With these new data, the analysis can determine that there is a greater risk of serious injuries caused by vehicle doors and mirrors compared to the rider hitting the rear of the vehicle.
With these new data, the analysis can determine that, compared to riding on roads without bicycle facilities, there is a lower probability of serious injuries on roads with bicycle lanes but not on lanes.
The authors thank the New York state department of transport for their analysis.
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005 openurlcrossrefubmedfootnotesacl and horse are the first collaborators.
Contributors ACL, MA, and MSF have full access to the data in the study and are responsible for the integrity of the data and the accuracy of the data analysis.
Concept and design: ACL and MA.
Acquisition of data: ACL and MA.
Interpretation of data analysis: ACL, MA, MSF.
Manuscript drafting: ACL.
Key revisions to knowledge content: ACL, MA, and MF.
Statistical expertise: ACL, MA, MSF.
Management or technical or material support: ACL.
Learning supervisor: ACL.
Nissan Motor Corporation supports the financing of ACL and MA. , Ltd.
There is no competitive interest.
The Harvard School of Public Health IRB found that the agreement met IRB's exemption criteria and did not require an additional review by IRB.
Uncommissioned source and peer review;
External peer review.
Data sharing statement the original crash data was owned by the New York State Department of Transportation.
Information about the police crash report template can be made available to the public online or through contact with the state police department.
In addition to the separate drawings of 300 crashes and the resulting data entered as Excel code, there is no unpublished data in the study.
In order to provide this data to others, we will first seek approval from NYSDOT.
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