Data Introduction

Row

There are 3 CSVs in this dataset. Accidents is the primary one. The raw compiled 2005 to 2015 datasets downloaded from kaggle are as below:

Accidents Data

ï..Accident_Index Location_Easting_OSGR Location_Northing_OSGR Longitude Latitude Police_Force Accident_Severity Number_of_Vehicles Number_of_Casualties Date Day_of_Week Time Local_Authority_.District. Local_Authority_.Highway. X1st_Road_Class X1st_Road_Number Road_Type Speed_limit Junction_Detail Junction_Control X2nd_Road_Class X2nd_Road_Number Pedestrian_Crossing.Human_Control Pedestrian_Crossing.Physical_Facilities Light_Conditions Weather_Conditions Road_Surface_Conditions Special_Conditions_at_Site Carriageway_Hazards Urban_or_Rural_Area Did_Police_Officer_Attend_Scene_of_Accident LSOA_of_Accident_Location
200501BS00001 525680 178240 -0.191170 51.48910 1 2 1 1 04/01/2005 3 17:42 12 E09000020 3 3218 6 30 0 -1 -1 0 0 1 1 2 2 0 0 1 1 E01002849
200501BS00002 524170 181650 -0.211708 51.52007 1 3 1 1 05/01/2005 4 17:36 12 E09000020 4 450 3 30 6 2 5 0 0 5 4 1 1 0 0 1 1 E01002909
200501BS00003 524520 182240 -0.206458 51.52530 1 3 2 1 06/01/2005 5 00:15 12 E09000020 5 0 6 30 0 -1 -1 0 0 0 4 1 1 0 0 1 1 E01002857
200501BS00004 526900 177530 -0.173862 51.48244 1 3 1 1 07/01/2005 6 10:35 12 E09000020 3 3220 6 30 0 -1 -1 0 0 0 1 1 1 0 0 1 1 E01002840

Data Frame Summary

No Variable Stats / Values Freqs (% of Valid) Graph Missing

1

ï..Accident_Index
[factor]
1. 200501BS00001 2. 200501BS00002 3. 200501BS00003 4. 200501BS00004 5. 200501BS00005 6. 200501BS00006 7. 200501BS00007 8. 200501BS00009 9. 200501BS00010 10. 200501BS00011 [ 1780643 others ]
1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1780643 (100.0%)
0 (0%)

2

Location_Easting_OSGR
[integer]

Mean (sd) : 440179.9 (95476)
min < med < max:
64950 < 441320 < 655540
IQR (CV) : 147023.5 (0.2)

218883 distinct values

138
(0.01%)

3

Location_Northing_OSGR
[integer]

Mean (sd) : 298512.8 (161225.4)
min < med < max:
10290 < 264950 < 1208800
IQR (CV) : 218580 (0.5)

267801 distinct values

138
(0.01%)

4

Longitude
[numeric]

Mean (sd) : -1.4 (1.4)
min < med < max:
-7.5 < -1.4 < 1.8
IQR (CV) : 2.1 (-1)

1246102 distinct values

138
(0.01%)

5

Latitude
[numeric]

Mean (sd) : 52.6 (1.5)
min < med < max:
49.9 < 52.3 < 60.8
IQR (CV) : 2 (0)

1168981 distinct values

138
(0.01%)

6

Police_Force
[integer]

Mean (sd) : 30.8 (25.5)
min < med < max:
1 < 31 < 98
IQR (CV) : 39 (0.8)

51 distinct values

0
(0%)

7

Accident_Severity
[integer]

Mean (sd) : 2.8 (0.4)
min < med < max:
1 < 3 < 3
IQR (CV) : 0 (0.1)

1 : 22998 ( 1.3%)
2 : 242080 (13.6%)
3 : 1515575 (85.1%)

0
(0%)

8

Number_of_Vehicles
[integer]

Mean (sd) : 1.8 (0.7)
min < med < max:
1 < 2 < 67
IQR (CV) : 1 (0.4)

28 distinct values

0
(0%)

9

Number_of_Casualties
[integer]

Mean (sd) : 1.3 (0.8)
min < med < max:
1 < 1 < 93
IQR (CV) : 0 (0.6)

51 distinct values

0
(0%)

10

Date
[factor]

1. 01/01/2005
2. 01/01/2006
3. 01/01/2007
4. 01/01/2008
5. 01/01/2009
6. 01/01/2010
7. 01/01/2011
8. 01/01/2012
9. 01/01/2013
10. 01/01/2014
[ 4007 others ]

308 ( 0.0%)
282 ( 0.0%)
335 ( 0.0%)
257 ( 0.0%)
244 ( 0.0%)
282 ( 0.0%)
204 ( 0.0%)
249 ( 0.0%)
262 ( 0.0%)
267 ( 0.0%)
1777963 (99.9%)

0
(0%)

11

Day_of_Week
[integer]

Mean (sd) : 4.1 (1.9)
min < med < max:
1 < 4 < 7
IQR (CV) : 4 (0.5)

1 : 195326 (11.0%)
2 : 253270 (14.2%)
3 : 266706 (15.0%)
4 : 268390 (15.1%)
5 : 267494 (15.0%)
6 : 291359 (16.4%)
7 : 238108 (13.4%)

0
(0%)

12

Time
[factor]

1.
2. 00:01
3. 00:02
4. 00:03
5. 00:04
6. 00:05
7. 00:06
8. 00:07
9. 00:08
10. 00:09
[ 1430 others ]

151 ( 0.0%)
2405 ( 0.1%)
376 ( 0.0%)
286 ( 0.0%)
278 ( 0.0%)
1491 ( 0.1%)
211 ( 0.0%)
205 ( 0.0%)
312 ( 0.0%)
249 ( 0.0%)
1774689 (99.7%)

0
(0%)

13

Local_Authority_.District.
[integer]

Mean (sd) : 353.3 (259.3)
min < med < max:
1 < 328 < 941
IQR (CV) : 409 (0.7)

416 distinct values

0
(0%)

14

Local_Authority_.Highway.
[factor]

1. E06000001
2. E06000002
3. E06000003
4. E06000004
5. E06000005
6. E06000006
7. E06000007
8. E06000008
9. E06000009
10. E06000010
[ 197 others ]

1754 ( 0.1%)
3419 ( 0.2%)
2537 ( 0.1%)
3709 ( 0.2%)
2918 ( 0.2%)
3387 ( 0.2%)
7333 ( 0.4%)
4893 ( 0.3%)
5126 ( 0.3%)
8568 ( 0.5%)
1737009 (97.5%)

0
(0%)

15

X1st_Road_Class
[integer]

Mean (sd) : 4.1 (1.4)
min < med < max:
1 < 4 < 6
IQR (CV) : 3 (0.3)

1 : 68634 ( 3.8%)
2 : 4743 ( 0.3%)
3 : 808813 (45.4%)
4 : 226488 (12.7%)
5 : 157600 ( 8.8%)
6 : 514375 (28.9%)

0
(0%)

16

X1st_Road_Number
[integer]

Mean (sd) : 1007.9 (1821.2)
min < med < max:
-1 < 128 < 9999
IQR (CV) : 725 (1.8)

7062 distinct values

0
(0%)

17

Road_Type
[integer]

Mean (sd) : 5.2 (1.6)
min < med < max:
1 < 6 < 9
IQR (CV) : 0 (0.3)

1 : 119472 ( 6.7%)
2 : 36755 ( 2.1%)
3 : 262950 (14.8%)
6 : 1332384 (74.8%)
7 : 18647 ( 1.0%)
9 : 10445 ( 0.6%)

0
(0%)

18

Speed_limit
[integer]

Mean (sd) : 39 (14.2)
min < med < max:
0 < 30 < 70
IQR (CV) : 20 (0.4)

0 : 1 ( 0.0%)
10 : 19 ( 0.0%)
15 : 16 ( 0.0%)
20 : 22017 ( 1.2%)
30 : 1141609 (64.1%)
40 : 146292 ( 8.2%)
50 : 58505 ( 3.3%)
60 : 282363 (15.9%)
70 : 129831 ( 7.3%)

0
(0%)

19

Junction_Detail
[integer]

Mean (sd) : 2.3 (2.6)
min < med < max:
-1 < 2 < 9
IQR (CV) : 3 (1.1)

-1 : 19 ( 0.0%)
0 : 716544 (40.2%)
1 : 154723 ( 8.7%)
2 : 19206 ( 1.1%)
3 : 553692 (31.1%)
5 : 26054 ( 1.5%)
6 : 170738 ( 9.6%)
7 : 23060 ( 1.3%)
8 : 65219 ( 3.7%)
9 : 51398 ( 2.9%)

0
(0%)

20

Junction_Control
[integer]

Mean (sd) : 1.8 (2.3)
min < med < max:
-1 < 2 < 4
IQR (CV) : 5 (1.3)

-1 : 641392 (36.0%)
0 : 76916 ( 4.3%)
1 : 2918 ( 0.2%)
2 : 182829 (10.3%)
3 : 10841 ( 0.6%)
4 : 865757 (48.6%)

0
(0%)

21

X2nd_Road_Class
[integer]

Mean (sd) : 2.7 (3.2)
min < med < max:
-1 < 3 < 6
IQR (CV) : 7 (1.2)

-1 : 732871 (41.2%)
1 : 11854 ( 0.7%)
2 : 1314 ( 0.1%)
3 : 175552 ( 9.9%)
4 : 69705 ( 3.9%)
5 : 82092 ( 4.6%)
6 : 707265 (39.7%)

0
(0%)

22

X2nd_Road_Number
[integer]

Mean (sd) : 378.3 (1297.4)
min < med < max:
-1 < 0 < 9999
IQR (CV) : 0 (3.4)

7438 distinct values

0
(0%)

23

Pedestrian_Crossing.Human_Control
[integer]

Mean (sd) : 0 (0.1)
min < med < max:
-1 < 0 < 2
IQR (CV) : 0 (13.8)

-1 : 161 ( 0.0%)
0 : 1770024 (99.4%)
1 : 4284 ( 0.2%)
2 : 6184 ( 0.4%)

0
(0%)

24

Pedestrian_Crossing.Physical_Facilities
[integer]

Mean (sd) : 0.7 (1.8)
min < med < max:
-1 < 0 < 8
IQR (CV) : 0 (2.5)

-1 : 164 ( 0.0%)
0 : 1482907 (83.3%)
1 : 47243 ( 2.6%)
4 : 93900 ( 5.3%)
5 : 118629 ( 6.7%)
7 : 5070 ( 0.3%)
8 : 32740 ( 1.8%)

0
(0%)

25

Light_Conditions
[integer]

Mean (sd) : 2 (1.6)
min < med < max:
1 < 1 < 7
IQR (CV) : 3 (0.8)

1 : 1304474 (73.3%)
4 : 349728 (19.6%)
5 : 8185 ( 0.5%)
6 : 98947 ( 5.6%)
7 : 19319 ( 1.1%)

0
(0%)

26

Weather_Conditions
[integer]

Mean (sd) : 1.6 (1.6)
min < med < max:
-1 < 1 < 9
IQR (CV) : 0 (1)

-1 : 161 ( 0.0%)
1 : 1423144 (79.9%)
2 : 210489 (11.8%)
3 : 12400 ( 0.7%)
4 : 23313 ( 1.3%)
5 : 25855 ( 1.4%)
6 : 2309 ( 0.1%)
7 : 9699 ( 0.5%)
8 : 39165 ( 2.2%)
9 : 34118 ( 1.9%)

0
(0%)

27

Road_Surface_Conditions
[integer]

Mean (sd) : 1.4 (0.6)
min < med < max:
-1 < 1 < 5
IQR (CV) : 1 (0.5)

-1 : 2439 ( 0.1%)
1 : 1226381 (68.9%)
2 : 501779 (28.2%)
3 : 11476 ( 0.6%)
4 : 35994 ( 2.0%)
5 : 2584 ( 0.1%)

0
(0%)

28

Special_Conditions_at_Site
[integer]

Mean (sd) : 0.1 (0.7)
min < med < max:
-1 < 0 < 7
IQR (CV) : 0 (6.7)

-1 : 124 ( 0.0%)
0 : 1736828 (97.5%)
1 : 3263 ( 0.2%)
2 : 901 ( 0.0%)
3 : 2616 ( 0.1%)
4 : 20741 ( 1.2%)
5 : 4293 ( 0.2%)
6 : 6222 ( 0.4%)
7 : 5665 ( 0.3%)

0
(0%)

29

Carriageway_Hazards
[integer]

Mean (sd) : 0.1 (0.6)
min < med < max:
-1 < 0 < 7
IQR (CV) : 0 (8.6)

-1 : 127 ( 0.0%)
0 : 1748381 (98.2%)
1 : 1935 ( 0.1%)
2 : 13931 ( 0.8%)
3 : 2725 ( 0.1%)
6 : 4171 ( 0.2%)
7 : 9383 ( 0.5%)

0
(0%)

30

Urban_or_Rural_Area
[integer]

Mean (sd) : 1.4 (0.5)
min < med < max:
1 < 1 < 3
IQR (CV) : 1 (0.4)

1 : 1146421 (64.4%)
2 : 634089 (35.6%)
3 : 143 ( 0.0%)

0
(0%)

31

Did_Police_Officer_Attend_Scene_of_Accident
[integer]

Mean (sd) : 1.2 (0.4)
min < med < max:
-1 < 1 < 3
IQR (CV) : 0 (0.3)

-1 : 278 ( 0.0%)
1 : 1438886 (80.8%)
2 : 337945 (19.0%)
3 : 3544 ( 0.2%)

0
(0%)

32

LSOA_of_Accident_Location
[factor]

1.
2. E01000001
3. E01000002
4. E01000003
5. E01000004
6. E01000005
7. E01000006
8. E01000007
9. E01000008
10. E01000009
[ 35505 others ]

129471 ( 7.3%)
131 ( 0.0%)
62 ( 0.0%)
5 ( 0.0%)
2367 ( 0.1%)
216 ( 0.0%)
13 ( 0.0%)
140 ( 0.0%)
108 ( 0.0%)
88 ( 0.0%)
1648052 (92.5%)

0
(0%)

Vehicle Data

ï..Accident_Index Vehicle_Reference Vehicle_Type Towing_and_Articulation Vehicle_Manoeuvre Vehicle_Location.Restricted_Lane Junction_Location Skidding_and_Overturning Hit_Object_in_Carriageway Vehicle_Leaving_Carriageway Hit_Object_off_Carriageway X1st_Point_of_Impact Was_Vehicle_Left_Hand_Drive. Journey_Purpose_of_Driver Sex_of_Driver Age_of_Driver Age_Band_of_Driver Engine_Capacity_.CC. Propulsion_Code Age_of_Vehicle Driver_IMD_Decile Driver_Home_Area_Type
200501BS00001 1 9 0 18 0 0 0 0 0 0 1 1 15 2 74 10 -1 -1 -1 7 1
200501BS00002 1 11 0 4 0 3 0 0 0 0 4 1 1 1 42 7 8268 2 3 -1 -1
200501BS00003 1 11 0 17 0 0 0 4 0 0 4 1 1 1 35 6 8300 2 5 2 1
200501BS00003 2 9 0 2 0 0 0 0 0 0 3 1 15 1 62 9 1762 1 6 1 1

Data Frame Summary (Vehicles0515.csv)

No Variable Stats / Values Freqs (% of Valid) Graph Missing

1

ï..Accident_Index
[factor]
1. -1 2. 200501BS00001 3. 200501BS00002 4. 200501BS00003 5. 200501BS00004 6. 200501BS00005 7. 200501BS00006 8. 200501BS00007 9. 200501BS00009 10. 200501BS00010 [ 1780644 others ]
257845 ( 7.3%) 1 ( 0.0%) 1 ( 0.0%) 2 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 2 ( 0.0%) 2 ( 0.0%) 1 ( 0.0%) 2 ( 0.0%) 3262257 (92.7%)
0 (0%)

2

Vehicle_Reference
[integer]

Mean (sd) : 1.6 (0.8)
min < med < max:
1 < 1 < 91
IQR (CV) : 1 (0.5)

68 distinct values

257845
(7.32%)

3

Vehicle_Type
[integer]

Mean (sd) : 9.6 (8.4)
min < med < max:
-1 < 9 < 98
IQR (CV) : 0 (0.9)

21 distinct values

257845
(7.32%)

4

Towing_and_Articulation
[integer]

Mean (sd) : 0 (0.3)
min < med < max:
-1 < 0 < 5
IQR (CV) : 0 (9.9)

-1 : 433 ( 0.0%)
0 : 3210323 (98.4%)
1 : 34571 ( 1.1%)
2 : 802 ( 0.0%)
3 : 1858 ( 0.1%)
4 : 11599 ( 0.4%)
5 : 2684 ( 0.1%)

257845
(7.32%)

5

Vehicle_Manoeuvre
[integer]

Mean (sd) : 12.7 (6.2)
min < med < max:
-1 < 17 < 18
IQR (CV) : 11 (0.5)

19 distinct values

257845
(7.32%)

6

Vehicle_Location.Restricted_Lane
[integer]

Mean (sd) : 0.1 (1)
min < med < max:
-1 < 0 < 9
IQR (CV) : 0 (7.5)

11 distinct values

257845
(7.32%)

7

Junction_Location
[integer]

Mean (sd) : 2.5 (3.2)
min < med < max:
-1 < 1 < 8
IQR (CV) : 6 (1.2)

-1 : 9943 ( 0.3%)
0 : 1258869 (38.6%)
1 : 770322 (23.6%)
2 : 187181 ( 5.7%)
3 : 47629 ( 1.5%)
4 : 83554 ( 2.6%)
5 : 78122 ( 2.4%)
6 : 144724 ( 4.4%)
7 : 12479 ( 0.4%)
8 : 669447 (20.5%)

257845
(7.32%)

8

Skidding_and_Overturning
[integer]

Mean (sd) : 0.2 (0.7)
min < med < max:
-1 < 0 < 5
IQR (CV) : 0 (3.4)

-1 : 269 ( 0.0%)
0 : 2835890 (86.9%)
1 : 310249 ( 9.5%)
2 : 64898 ( 2.0%)
3 : 1388 ( 0.0%)
4 : 761 ( 0.0%)
5 : 48815 ( 1.5%)

257845
(7.32%)

9

Hit_Object_in_Carriageway
[integer]

Mean (sd) : 0.3 (1.6)
min < med < max:
-1 < 0 < 12
IQR (CV) : 0 (5.3)

13 distinct values

257845
(7.32%)

10

Vehicle_Leaving_Carriageway
[integer]

Mean (sd) : 0.4 (1.4)
min < med < max:
-1 < 0 < 8
IQR (CV) : 0 (3.7)

-1 : 251 ( 0.0%)
0 : 2890137 (88.6%)
1 : 193356 ( 5.9%)
2 : 25844 ( 0.8%)
3 : 11462 ( 0.4%)
4 : 15246 ( 0.5%)
5 : 11149 ( 0.3%)
6 : 3073 ( 0.1%)
7 : 97913 ( 3.0%)
8 : 13839 ( 0.4%)

257845
(7.32%)

11

Hit_Object_off_Carriageway
[integer]

Mean (sd) : 0.6 (2.1)
min < med < max:
-1 < 0 < 11
IQR (CV) : 0 (3.7)

13 distinct values

257845
(7.32%)

12

X1st_Point_of_Impact
[integer]

Mean (sd) : 1.8 (1.2)
min < med < max:
-1 < 1 < 4
IQR (CV) : 2 (0.7)

-1 : 727 ( 0.0%)
0 : 212001 ( 6.5%)
1 : 1599856 (49.0%)
2 : 585668 (17.9%)
3 : 457162 (14.0%)
4 : 406856 (12.5%)

257845
(7.32%)

13

Was_Vehicle_Left_Hand_Drive.
[integer]

Mean (sd) : 1 (0.2)
min < med < max:
-1 < 1 < 2
IQR (CV) : 0 (0.2)

-1 : 24068 ( 0.7%)
1 : 3223341 (98.8%)
2 : 14861 ( 0.5%)

257845
(7.32%)

14

Journey_Purpose_of_Driver
[integer]

Mean (sd) : 8.4 (5.9)
min < med < max:
-1 < 6 < 15
IQR (CV) : 13 (0.7)

-1 : 44945 ( 1.4%)
1 : 545046 (16.7%)
2 : 311840 ( 9.6%)
3 : 31786 ( 1.0%)
4 : 11118 ( 0.3%)
5 : 22462 ( 0.7%)
6 : 932374 (28.6%)
15 : 1362699 (41.8%)

257845
(7.32%)

15

Sex_of_Driver
[integer]

Mean (sd) : 1.4 (0.6)
min < med < max:
-1 < 1 < 3
IQR (CV) : 1 (0.4)

-1 : 52 ( 0.0%)
1 : 2147401 (65.8%)
2 : 924565 (28.3%)
3 : 190252 ( 5.8%)

257845
(7.32%)

16

Age_of_Driver
[integer]

Mean (sd) : 34.4 (19.5)
min < med < max:
-1 < 34 < 100
IQR (CV) : 25 (0.6)

101 distinct values

257845
(7.32%)

17

Age_Band_of_Driver
[integer]

Mean (sd) : 5.9 (2.9)
min < med < max:
-1 < 6 < 11
IQR (CV) : 3 (0.5)

12 distinct values

257845
(7.32%)

18

Engine_Capacity_.CC.
[integer]

Mean (sd) : 1408 (1689.6)
min < med < max:
-1 < 1388 < 99999
IQR (CV) : 1897 (1.2)

2881 distinct values

257845
(7.32%)

19

Propulsion_Code
[integer]

Mean (sd) : 0.8 (1.2)
min < med < max:
-1 < 1 < 12
IQR (CV) : 3 (1.5)

13 distinct values

257845
(7.32%)

20

Age_of_Vehicle
[integer]

Mean (sd) : 4.9 (5.4)
min < med < max:
-1 < 4 < 111
IQR (CV) : 10 (1.1)

99 distinct values

257845
(7.32%)

21

Driver_IMD_Decile
[integer]

Mean (sd) : 3.2 (3.8)
min < med < max:
-1 < 3 < 10
IQR (CV) : 7 (1.2)

11 distinct values

257845
(7.32%)

22

Driver_Home_Area_Type
[integer]

Mean (sd) : 0.9 (1.1)
min < med < max:
-1 < 1 < 3
IQR (CV) : 0 (1.3)

-1 : 635640 (19.5%)
1 : 2058187 (63.1%)
2 : 245732 ( 7.5%)
3 : 322711 ( 9.9%)

257845
(7.32%)

Casualties Data

ï..Accident_Index Vehicle_Reference Casualty_Reference Casualty_Class Sex_of_Casualty Age_of_Casualty Age_Band_of_Casualty Casualty_Severity Pedestrian_Location Pedestrian_Movement Car_Passenger Bus_or_Coach_Passenger Pedestrian_Road_Maintenance_Worker Casualty_Type Casualty_Home_Area_Type
200501BS00001 1 1 3 1 37 7 2 1 1 0 0 -1 0 1
200501BS00002 1 1 2 1 37 7 3 0 0 0 4 -1 11 1
200501BS00003 2 1 1 1 62 9 3 0 0 0 0 -1 9 1
200501BS00004 1 1 3 1 30 6 3 5 2 0 0 -1 0 1

Data Frame Summary (Casualties0515.csv)

No Variable Stats / Values Freqs (% of Valid) Graph Missing

1

ï..Accident_Index
[factor]
1. -1 2. 1 3. 10 4. 2 5. 200501BS00001 6. 200501BS00002 7. 200501BS00003 8. 200501BS00004 9. 200501BS00005 10. 200501BS00006 [ 1780654 others ]
36756 ( 1.4%) 18297 ( 0.7%) 10851 ( 0.4%) 17999 ( 0.7%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 1 ( 0.0%) 2505189 (96.8%)
0 (0%)

2

Vehicle_Reference
[integer]

Mean (sd) : 1.5 (0.7)
min < med < max:
1 < 1 < 91
IQR (CV) : 1 (0.4)

67 distinct values

186189
(7.19%)

3

Casualty_Reference
[integer]

Mean (sd) : 1.4 (1.4)
min < med < max:
1 < 1 < 852
IQR (CV) : 1 (1)

97 distinct values

186189
(7.19%)

4

Casualty_Class
[integer]

Mean (sd) : 1.5 (0.7)
min < med < max:
1 < 1 < 3
IQR (CV) : 1 (0.5)

1 : 1518808 (63.2%)
2 : 584175 (24.3%)
3 : 299926 (12.5%)

186189
(7.19%)

5

Sex_of_Casualty
[integer]

Mean (sd) : 1.4 (0.5)
min < med < max:
-1 < 1 < 2
IQR (CV) : 1 (0.3)

-1 : 691 ( 0.0%)
1 : 1402561 (58.4%)
2 : 999657 (41.6%)

186189
(7.19%)

6

Age_of_Casualty
[integer]

Mean (sd) : 34.5 (18.9)
min < med < max:
-1 < 31 < 104
IQR (CV) : 27 (0.5)

106 distinct values

186189
(7.19%)

7

Age_Band_of_Casualty
[integer]

Mean (sd) : 6 (2.4)
min < med < max:
-1 < 6 < 11
IQR (CV) : 4 (0.4)

12 distinct values

186189
(7.19%)

8

Casualty_Severity
[integer]

Mean (sd) : 2.9 (0.4)
min < med < max:
1 < 3 < 3
IQR (CV) : 0 (0.1)

1 : 24802 ( 1.0%)
2 : 271554 (11.3%)
3 : 2106553 (87.7%)

186189
(7.19%)

9

Pedestrian_Location
[integer]

Mean (sd) : 0.7 (2)
min < med < max:
-1 < 0 < 10
IQR (CV) : 0 (2.9)

12 distinct values

186189
(7.19%)

10

Pedestrian_Movement
[integer]

Mean (sd) : 0.5 (1.7)
min < med < max:
-1 < 0 < 9
IQR (CV) : 0 (3.5)

11 distinct values

186189
(7.19%)

11

Car_Passenger
[integer]

Mean (sd) : 0.3 (0.6)
min < med < max:
-1 < 0 < 2
IQR (CV) : 0 (2.1)

-1 : 780 ( 0.0%)
0 : 1904469 (79.3%)
1 : 319866 (13.3%)
2 : 177794 ( 7.4%)

186189
(7.19%)

12

Bus_or_Coach_Passenger
[integer]

Mean (sd) : 0.1 (0.6)
min < med < max:
-1 < 0 < 4
IQR (CV) : 0 (6.3)

-1 : 63 ( 0.0%)
0 : 2339779 (97.4%)
1 : 3913 ( 0.2%)
2 : 3832 ( 0.2%)
3 : 16871 ( 0.7%)
4 : 38451 ( 1.6%)

186189
(7.19%)

13

Pedestrian_Road_Maintenance_Worker
[integer]

Mean (sd) : -0.6 (0.6)
min < med < max:
-1 < -1 < 2
IQR (CV) : 1 (-1)

-1 : 1439175 (59.9%)
0 : 931615 (38.8%)
1 : 191 ( 0.0%)
2 : 31928 ( 1.3%)

186189
(7.19%)

14

Casualty_Type
[integer]

Mean (sd) : 7.5 (7.2)
min < med < max:
0 < 9 < 98
IQR (CV) : 6 (1)

21 distinct values

186189
(7.19%)

15

Casualty_Home_Area_Type
[integer]

Mean (sd) : 1 (1)
min < med < max:
-1 < 1 < 3
IQR (CV) : 0 (1)

-1 : 343872 (14.3%)
1 : 1624427 (67.6%)
2 : 194050 ( 8.1%)
3 : 240560 (10.0%)

186189
(7.19%)

Data Cleaning

Row

Cleaned and Compiled Accidents Data

Accident_Index Longitude Latitude Accident_Severity Number_of_Vehicles Number_of_Casualties Date Day_of_Week Time Road_Type Speed_limit Junction_Detail Junction_Control Light_Conditions Weather_Conditions Road_Surface_Conditions Special_Conditions_at_Site Carriageway_Hazards Urban_or_Rural_Area Vehicle_Reference Vehicle_Type Vehicle_Manoeuvre Junction_Location Skidding_and_Overturning Hit_Object_in_Carriageway Vehicle_Leaving_Carriageway Hit_Object_off_Carriageway X1st_Point_of_Impact Sex_of_Driver Age_of_Driver Age_Band_of_Driver Engine_Capacity_.CC. Age_of_Vehicle Driver_Home_Area_Type Casualty_Severity Driver_Casualties_1 Driver_Casualties_2 Driver_Casualties_3 Passenger_Casualties_1 Passenger_Casualties_2 Passenger_Casualties_3 Pedestrian_Casualties_1 Pedestrian_Casualties_2 Pedestrian_Casualties_3
200501BS00001 -0.191170 51.48910 2 1 1 2005-01-04 3 17:42 6 30 0 -1 1 2 2 0 0 1 1 9 18 0 0 0 0 0 1 2 74 10 -1 -1 1 2 0 0 0 0 0 0 0 1 0
200501BS00002 -0.211708 51.52007 3 1 1 2005-01-05 4 17:36 3 30 6 2 4 1 1 0 0 1 1 11 4 3 0 0 0 0 4 1 42 7 8268 3 -1 3 0 0 0 0 0 1 0 0 0
200501BS00003 -0.206458 51.52530 3 2 1 2005-01-06 5 00:15 6 30 0 -1 4 1 1 0 0 1 1 11 17 0 0 4 0 0 4 1 35 6 8300 5 1 NA 0 0 0 0 0 0 0 0 0
200501BS00003 -0.206458 51.52530 3 2 1 2005-01-06 5 00:15 6 30 0 -1 4 1 1 0 0 1 2 9 2 0 0 0 0 0 3 1 62 9 1762 6 1 3 0 0 1 0 0 0 0 0 0

Data Frame Summary (Cleaned Data)

No Variable Stats / Values Freqs (% of Valid) Graph Missing

1

Accident_Index
[factor]

1. 200501BS00001
2. 200501BS00002
3. 200501BS00003
4. 200501BS00004
5. 200501BS00005
6. 200501BS00006
7. 200501BS00007
8. 200501BS00009
9. 200501BS00010
10. 200501BS00011
[ 1780643 others ]

1 ( 0.0%)
1 ( 0.0%)
2 ( 0.0%)
1 ( 0.0%)
1 ( 0.0%)
2 ( 0.0%)
2 ( 0.0%)
1 ( 0.0%)
2 ( 0.0%)
2 ( 0.0%)
3301010 (100.0%)

0
(0%)

2

Longitude
[numeric]

Mean (sd) : -1.4 (1.4)
min < med < max:
-7.5 < -1.4 < 1.8
IQR (CV) : 2.1 (-1)

1246102 distinct values

253
(0.01%)

3

Latitude
[numeric]

Mean (sd) : 52.6 (1.4)
min < med < max:
49.9 < 52.3 < 60.8
IQR (CV) : 2 (0)

1168981 distinct values

253
(0.01%)

4

Accident_Severity
[integer]

Mean (sd) : 2.8 (0.4)
min < med < max:
1 < 3 < 3
IQR (CV) : 0 (0.1)

1 : 47769 ( 1.4%)
2 : 439454 (13.3%)
3 : 2813802 (85.2%)

0
(0%)

5

Number_of_Vehicles
[integer]

Mean (sd) : 2.1 (0.9)
min < med < max:
1 < 2 < 67
IQR (CV) : 0 (0.4)

28 distinct values

0
(0%)

6

Number_of_Casualties
[integer]

Mean (sd) : 1.4 (1)
min < med < max:
1 < 1 < 93
IQR (CV) : 1 (0.7)

51 distinct values

0
(0%)

7

Date
[Date]

min : 2005-01-01
med : 2009-11-25
max : 2015-12-31
range : 10y 11m 30d

4017 distinct values

0
(0%)

8

Day_of_Week
[integer]

Mean (sd) : 4.1 (1.9)
min < med < max:
1 < 4 < 7
IQR (CV) : 4 (0.5)

1 : 354601 (10.7%)
2 : 471080 (14.3%)
3 : 498043 (15.1%)
4 : 501414 (15.2%)
5 : 499545 (15.1%)
6 : 544458 (16.5%)
7 : 431884 (13.1%)

0
(0%)

9

Time
[factor]

1.
2. 00:01
3. 00:02
4. 00:03
5. 00:04
6. 00:05
7. 00:06
8. 00:07
9. 00:08
10. 00:09
[ 1430 others ]

256 ( 0.0%)
3921 ( 0.1%)
621 ( 0.0%)
467 ( 0.0%)
445 ( 0.0%)
2405 ( 0.1%)
345 ( 0.0%)
338 ( 0.0%)
529 ( 0.0%)
406 ( 0.0%)
3291292 (99.7%)

0
(0%)

10

Road_Type
[integer]

Mean (sd) : 5.1 (1.7)
min < med < max:
1 < 6 < 9
IQR (CV) : 3 (0.3)

1 : 228449 ( 6.9%)
2 : 59032 ( 1.8%)
3 : 538028 (16.3%)
6 : 2421798 (73.4%)
7 : 36217 ( 1.1%)
9 : 17501 ( 0.5%)

0
(0%)

11

Speed_limit
[integer]

Mean (sd) : 39.6 (14.5)
min < med < max:
0 < 30 < 70
IQR (CV) : 20 (0.4)

0 : 2 ( 0.0%)
10 : 24 ( 0.0%)
15 : 23 ( 0.0%)
20 : 36076 ( 1.1%)
30 : 2059108 (62.4%)
40 : 289163 ( 8.8%)
50 : 119633 ( 3.6%)
60 : 518401 (15.7%)
70 : 278595 ( 8.4%)

0
(0%)

12

Junction_Detail
[integer]

Mean (sd) : 2.4 (2.6)
min < med < max:
-1 < 3 < 9
IQR (CV) : 3 (1.1)

-1 : 36 ( 0.0%)
0 : 1285885 (39.0%)
1 : 294432 ( 8.9%)
2 : 36202 ( 1.1%)
3 : 1032749 (31.3%)
5 : 53492 ( 1.6%)
6 : 328375 (10.0%)
7 : 43216 ( 1.3%)
8 : 131128 ( 4.0%)
9 : 95510 ( 2.9%)

0
(0%)

13

Junction_Control
[integer]

Mean (sd) : 1.9 (2.3)
min < med < max:
-1 < 3 < 4
IQR (CV) : 5 (1.2)

-1 : 1147040 (34.8%)
0 : 142330 ( 4.3%)
1 : 5181 ( 0.2%)
2 : 343672 (10.4%)
3 : 21358 ( 0.6%)
4 : 1641444 (49.7%)

0
(0%)

14

Light_Conditions
[integer]

Mean (sd) : 1.9 (1.6)
min < med < max:
1 < 1 < 7
IQR (CV) : 3 (0.8)

1 : 2455476 (74.4%)
4 : 631123 (19.1%)
5 : 14720 ( 0.4%)
6 : 165329 ( 5.0%)
7 : 34377 ( 1.0%)

0
(0%)

15

Weather_Conditions
[integer]

Mean (sd) : 1.6 (1.6)
min < med < max:
-1 < 1 < 9
IQR (CV) : 0 (1)

-1 : 299 ( 0.0%)
1 : 2648206 (80.2%)
2 : 388555 (11.8%)
3 : 21872 ( 0.7%)
4 : 42210 ( 1.3%)
5 : 45977 ( 1.4%)
6 : 4061 ( 0.1%)
7 : 17974 ( 0.5%)
8 : 70545 ( 2.1%)
9 : 61326 ( 1.9%)

0
(0%)

16

Road_Surface_Conditions
[integer]

Mean (sd) : 1.3 (0.6)
min < med < max:
-1 < 1 < 5
IQR (CV) : 1 (0.5)

-1 : 4323 ( 0.1%)
1 : 2286141 (69.3%)
2 : 927436 (28.1%)
3 : 20003 ( 0.6%)
4 : 58978 ( 1.8%)
5 : 4144 ( 0.1%)

0
(0%)

17

Special_Conditions_at_Site
[integer]

Mean (sd) : 0.1 (0.7)
min < med < max:
-1 < 0 < 7
IQR (CV) : 0 (6.7)

-1 : 232 ( 0.0%)
0 : 3219625 (97.5%)
1 : 6296 ( 0.2%)
2 : 1749 ( 0.0%)
3 : 5069 ( 0.1%)
4 : 42788 ( 1.3%)
5 : 6327 ( 0.2%)
6 : 10280 ( 0.3%)
7 : 8659 ( 0.3%)

0
(0%)

18

Carriageway_Hazards
[integer]

Mean (sd) : 0.1 (0.6)
min < med < max:
-1 < 0 < 7
IQR (CV) : 0 (9)

-1 : 234 ( 0.0%)
0 : 3245610 (98.3%)
1 : 4178 ( 0.1%)
2 : 24312 ( 0.7%)
3 : 7510 ( 0.2%)
6 : 6124 ( 0.2%)
7 : 13057 ( 0.4%)

0
(0%)

19

Urban_or_Rural_Area
[integer]

Mean (sd) : 1.4 (0.5)
min < med < max:
1 < 1 < 3
IQR (CV) : 1 (0.4)

1 : 2091420 (63.4%)
2 : 1209344 (36.6%)
3 : 261 ( 0.0%)

0
(0%)

20

Vehicle_Reference
[integer]

Mean (sd) : 1.6 (0.8)
min < med < max:
1 < 1 < 91
IQR (CV) : 1 (0.5)

68 distinct values

0
(0%)

21

Vehicle_Type
[integer]

Mean (sd) : 9.6 (8.3)
min < med < max:
-1 < 9 < 98
IQR (CV) : 0 (0.9)

21 distinct values

0
(0%)

22

Vehicle_Manoeuvre
[integer]

Mean (sd) : 12.7 (6.2)
min < med < max:
-1 < 17 < 18
IQR (CV) : 11 (0.5)

19 distinct values

0
(0%)

23

Junction_Location
[integer]

Mean (sd) : 2.5 (3.2)
min < med < max:
-1 < 1 < 8
IQR (CV) : 6 (1.2)

-1 : 10079 ( 0.3%)
0 : 1280894 (38.8%)
1 : 776254 (23.5%)
2 : 189221 ( 5.7%)
3 : 47977 ( 1.4%)
4 : 83975 ( 2.5%)
5 : 78766 ( 2.4%)
6 : 145877 ( 4.4%)
7 : 12590 ( 0.4%)
8 : 675392 (20.5%)

0
(0%)

24

Skidding_and_Overturning
[integer]

Mean (sd) : 0.2 (0.7)
min < med < max:
-1 < 0 < 5
IQR (CV) : 0 (3.3)

-1 : 269 ( 0.0%)
0 : 2860171 (86.6%)
1 : 318514 ( 9.6%)
2 : 68750 ( 2.1%)
3 : 1410 ( 0.0%)
4 : 794 ( 0.0%)
5 : 51117 ( 1.6%)

0
(0%)

25

Hit_Object_in_Carriageway
[integer]

Mean (sd) : 0.3 (1.6)
min < med < max:
-1 < 0 < 12
IQR (CV) : 0 (5.2)

13 distinct values

0
(0%)

26

Vehicle_Leaving_Carriageway
[integer]

Mean (sd) : 0.4 (1.4)
min < med < max:
-1 < 0 < 8
IQR (CV) : 0 (3.7)

-1 : 251 ( 0.0%)
0 : 2911733 (88.2%)
1 : 201940 ( 6.1%)
2 : 27249 ( 0.8%)
3 : 11996 ( 0.4%)
4 : 15691 ( 0.5%)
5 : 11504 ( 0.4%)
6 : 3269 ( 0.1%)
7 : 102700 ( 3.1%)
8 : 14692 ( 0.4%)

0
(0%)

27

Hit_Object_off_Carriageway
[integer]

Mean (sd) : 0.6 (2.1)
min < med < max:
-1 < 0 < 11
IQR (CV) : 0 (3.6)

13 distinct values

0
(0%)

28

X1st_Point_of_Impact
[integer]

Mean (sd) : 1.8 (1.2)
min < med < max:
-1 < 1 < 4
IQR (CV) : 2 (0.7)

-1 : 737 ( 0.0%)
0 : 213085 ( 6.5%)
1 : 1624897 (49.2%)
2 : 588182 (17.8%)
3 : 462125 (14.0%)
4 : 411999 (12.5%)

0
(0%)

29

Sex_of_Driver
[integer]

Mean (sd) : 1.4 (0.6)
min < med < max:
-1 < 1 < 3
IQR (CV) : 1 (0.4)

-1 : 52 ( 0.0%)
1 : 2176483 (65.9%)
2 : 933894 (28.3%)
3 : 190596 ( 5.8%)

0
(0%)

30

Age_of_Driver
[integer]

Mean (sd) : 34.4 (19.5)
min < med < max:
-1 < 34 < 100
IQR (CV) : 25 (0.6)

101 distinct values

0
(0%)

31

Age_Band_of_Driver
[integer]

Mean (sd) : 5.9 (2.9)
min < med < max:
-1 < 6 < 11
IQR (CV) : 3 (0.5)

12 distinct values

0
(0%)

32

Engine_Capacity_.CC.
[integer]

Mean (sd) : 1408.3 (1685.8)
min < med < max:
-1 < 1388 < 99999
IQR (CV) : 1897 (1.2)

2881 distinct values

0
(0%)

33

Age_of_Vehicle
[integer]

Mean (sd) : 4.9 (5.4)
min < med < max:
-1 < 4 < 111
IQR (CV) : 10 (1.1)

99 distinct values

0
(0%)

34

Driver_Home_Area_Type
[integer]

Mean (sd) : 0.9 (1.1)
min < med < max:
-1 < 1 < 3
IQR (CV) : 0 (1.3)

-1 : 640565 (19.4%)
1 : 2082486 (63.1%)
2 : 249905 ( 7.6%)
3 : 328069 ( 9.9%)

0
(0%)

35

Casualty_Severity
[integer]

Mean (sd) : 2.9 (0.4)
min < med < max:
1 < 3 < 3
IQR (CV) : 0 (0.1)

1 : 23331 ( 1.1%)
2 : 254763 (12.4%)
3 : 1778981 (86.5%)

1243950
(37.68%)

36

Driver_Casualties_1
[integer]

Min : 0
Mean : 0
Max : 1

0 : 3286101 (99.6%)
1 : 14924 ( 0.4%)

0
(0%)

37

Driver_Casualties_2
[integer]

Min : 0
Mean : 0.1
Max : 1

0 : 3135738 (95.0%)
1 : 165287 ( 5.0%)

0
(0%)

38

Driver_Casualties_3
[integer]

Min : 0
Mean : 0.4
Max : 1

0 : 1962428 (59.5%)
1 : 1338597 (40.6%)

0
(0%)

39

Passenger_Casualties_1
[integer]

Mean (sd) : 0 (0)
min < med < max:
0 < 0 < 5
IQR (CV) : 0 (31.1)

0 : 3297185 (99.9%)
1 : 3479 ( 0.1%)
2 : 296 ( 0.0%)
3 : 50 ( 0.0%)
4 : 12 ( 0.0%)
5 : 3 ( 0.0%)

0
(0%)

40

Passenger_Casualties_2
[integer]

Mean (sd) : 0 (0.1)
min < med < max:
0 < 0 < 44
IQR (CV) : 0 (10.1)

15 distinct values

0
(0%)

41

Passenger_Casualties_3
[integer]

Mean (sd) : 0.2 (0.5)
min < med < max:
0 < 0 < 82
IQR (CV) : 0 (3.1)

45 distinct values

0
(0%)

42

Pedestrian_Casualties_1
[integer]

Mean (sd) : 0 (0)
min < med < max:
0 < 0 < 6
IQR (CV) : 0 (24.6)

0 : 3295500 (99.8%)
1 : 5463 ( 0.2%)
2 : 58 ( 0.0%)
3 : 3 ( 0.0%)
6 : 1 ( 0.0%)

0
(0%)

43

Pedestrian_Casualties_2
[integer]

Mean (sd) : 0 (0.1)
min < med < max:
0 < 0 < 11
IQR (CV) : 0 (7.4)

0 : 3240018 (98.2%)
1 : 60202 ( 1.8%)
2 : 726 ( 0.0%)
3 : 55 ( 0.0%)
4 : 15 ( 0.0%)
5 : 5 ( 0.0%)
6 : 1 ( 0.0%)
10 : 2 ( 0.0%)
11 : 1 ( 0.0%)

0
(0%)

44

Pedestrian_Casualties_3
[integer]

Mean (sd) : 0.1 (0.3)
min < med < max:
0 < 0 < 16
IQR (CV) : 0 (3.8)

13 distinct values

0
(0%)

Data Cleaning Procedure

Step 1: Remove unwanted attributes in myAccidents dataframe 
rmAccidents=c("Location_Easting_OSGR","Location_Northing_OSGR","Police_Force","Local_Authority_.District.",
              "Local_Authority_.Highway","X1st_Road_Class","X1st_Road_Number","X2nd_Road_Class",
              "X2nd_Road_Number","Pedestrian_Crossing.Human_Control","Pedestrian_Crossing.Physical_Facilities",
              "Did_Police_Officer_Attend_Scene_of_Accident","LSOA_of_Accident_Location")

myAccidents.clean=myAccidents[,!(names(myAccidents)%in%rmAccidents)]
Step 2: Remove unwanted attributes in myVehicle dataframe 
rmVehicles=c("Towing_and_Articulation","Vehicle_Location.Restricted_Lane","Was_Vehicle_Left_Hand_Drive.",
             "Journey_Purpose_of_Driver","Propulsion_Code","Driver_IMD_Decile")

myVehicles.clean=myVehicles[,!(names(myVehicles)%in%rmVehicles)]

Step 3 : Mutate casualties data into columns of casualty severity by casualty class

#1. Driver or Rider Casualties Severity 
Driver_Casualties_1= myCasualties\$Casualty_Class==1 & myCasualties\$Casualty_Severity==1

Driver_Casualties_2= myCasualties\$Casualty_Class==1 & myCasualties\$Casualty_Severity==2

Driver_Casualties_3= myCasualties\$Casualty_Class==1 & myCasualties\$Casualty_Severity==3
#2. Passenger Casualties Severity 
Passenger_Casualties_1 = myCasualties\$Casualty_Class==2 & myCasualties\$Casualty_Severity==1

Passenger_Casualties_2 = myCasualties\$Casualty_Class==2 & myCasualties\$Casualty_Severity==2

Passenger_Casualties_3 = myCasualties\$Casualty_Class==2 & myCasualties\$Casualty_Severity==3
#3. Pedestrian Casualties Severity 
Pedestrian_Casualties_1 = myCasualties\$Casualty_Class==3 & myCasualties\$Casualty_Severity==1

Pedestrian_Casualties_2 = myCasualties\$Casualty_Class==3 & myCasualties\$Casualty_Severity==2

Pedestrian_Casualties_3 = myCasualties\$Casualty_Class==3 & myCasualties\$Casualty_Severity==3
#All Conditions 
Mutate_Condition_1=c(Driver_Casualties_1,Driver_Casualties_2,Driver_Casualties_3,
                     Passenger_Casualties_1,Passenger_Casualties_2,Passenger_Casualties_3,
                     Pedestrian_Casualties_1,Pedestrian_Casualties_2,Pedestrian_Casualties_3)

myCasualties.clean=myCasualties%>%
  mutate(Driver_Casualties_1,Driver_Casualties_2,Driver_Casualties_3,
         Passenger_Casualties_1,Passenger_Casualties_2,Passenger_Casualties_3,
         Pedestrian_Casualties_1,Pedestrian_Casualties_2,Pedestrian_Casualties_3)%>%
  group_by(Accident_Index, Vehicle_Reference,Casualty_Severity)%>%
  summarize_each(funs(sum(.,na.rm=TRUE)),Driver_Casualties_1,Driver_Casualties_2,Driver_Casualties_3,
                 Passenger_Casualties_1,Passenger_Casualties_2,Passenger_Casualties_3,
                 Pedestrian_Casualties_1,Pedestrian_Casualties_2, Pedestrian_Casualties_3)
Step 4: Merging of three different datasets with the application of full joint function 
myCombined= full_join(myAccidents.clean,myVehicles.clean)

myCombined= full_join(myCombined, myCasualties.clean)
#Replace all NA values in casualties dataset to 0 as a result from the join 
myCombined = myCombined %>%mutate_each(funs(replace(.,is.na(.),0)),c(Driver_Casualties_1:Pedestrian_Casualties_3))

Data Exploration

Row

Accident Severity Based on Year

Accident Frequency Based on Age

Vehicles Involved Based on Day of Week

Machine Learning

Column

Result

Model Accuracy Sensitivity Specificity
CART 69.62 75.26 69.55
Random Forest 73.94 76.22 73.91
Logistic Regression 74.34 73.08 74.36
LogitBoost 77.83 59.66 78.07

Feature Importance

Feature Plot (Density graph)

Variable_1 Legend_1 Variable_2 Legend_2
Feature_1 Speed limit - 30mph Feature_7 Darkness - no ligthing
Feature_2 Not at junction Feature_8 Daylight
Feature_3 Speed limit - 60mph Feature_9 T or staggered junction
Feature_4 Did not leave carriageway Feature_10 Car
Feature_5 Not Skidding or Overturning Feature_11 Leave carriageway (Nearside)
Feature_6 Not Hitting Object Off Carriageway Feature_12 Rear Impact

Trend Prediction

Semantic Analysis