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Table 1 Explanatory variables description in Single-vehicle Run-off-road Crashes (n = 724)

From: A hybrid of regularization method and generalized path analysis: modeling single-vehicle run-off-road crashes in a cross-sectional study

Variable

Variable level

Total crashes

Fatal crashes

n (%)

n (%)

Passenger presence

no

321 (43.26%)

29 (28.71%)

yes

421 (56.74%)

72 (71.29%)

Crash day

weekday

501 (67.52%)

65 (64.36%)

weekend

241 (32.48%)

36 (35.64%)

Lighting

day

498 (67.12%)

72 (71.29%)

night

218 (29.38%)

27 (26.73%)

twilight/dawn

26 (3.5%)

2 (1.98%)

Clear/cloudy weather

no

41 (5.53%)

2 (1.98%)

yes

701 (94.74%)

99 (98.02%)

Dry road surface

no

45 (6.06%)

2 (1.98%)

yes

697 (93.94%)

99 (98.02%)

Curved geometric design

no

628 (84.64%)

82 (81.19%)

yes

114 (15.36%)

19 (18.81%)

Vehicle factor

no

731 (98.52%)

99 (98.02%)

yes

11 (1.48%)

2 (1.98%)

Human factor

no

196 (26.42%)

24 (23.76%)

yes

546 (73.58%)

77 (76.24%)

Collision type

head-on collision

176 (23.72%)

38 (37.63%)

rear-end collision

311 (41.91%)

41 (40.59%)

T-bone collision

220 (29.65%)

11 (10.89%)

side-swipe collision

35 (4.72%)

11 (10.89%)

Road shoulder

unpaved

35 (4.72%)

1 (0.99%)

paved with soil

349 (47.04%)

47 (46.53%)

paved with asphalt

358 (48.25%)

53 (52.48%)

Road design

one-way road

709 (95.55%)

100 (99.01%)

two-way road

33 (4.45%)

1 (0.99%)

Road defect

no

702 (94.61%)

91 (90.1%)

yes

40 (5.39%)

10 (9.9%)

Permitted speed

60–80

77 (10.38%)

1 (0.99%)

80–95

38 (5.12%)

5 (4.95%)

95–110

545 (73.45%)

83 (82.18%)

110–120

82 (11.05%)

12 (11.88%)

Vehicle type

low

578 (77.9%)

83 (82.18%)

high

153 (20.62%)

14 (13.86%)

tricycle/ bicycle/motorcycle

11 (1.48%)

4 (3.96%)

High-risk vehicle colora

no

560 (75.47%)

72 (71.29%)

yes

182 (24.53%)

29 (28.71%)

Vehicle safety equipment

low risk

456 (61.46%)

60 (59.41%)

high risk

286 (38.54%)

41 (40.59%)

Vehicle age

less than 5yrs

261 (35.18%)

44 (43.56%)

5 to 9 yrs

279 (37.6%)

34 (33.66%)

10 to 14 yrs

154 (20.75%)

14 (13.86%)

15 and more than 15yrs

48 (6.47%)

9 (8.91%)

Vehicle plaque description

personal regional

647 (87.2%)

90 (89.11%)

other

95 (12.8%)

11 (10.89%)

Vehicle maneuver

forward

723 (97.44%)

100 (99.01%)

turn

14 (1.89%)

0 (0%)

other

4 (54%)

1 (0.99%)

backward

1 (0.13%)

0 (0%)

Driver fault status

at fault

733 (98.79%)

98 (97.03%)

not at fault

9 (1.21%)

3 (2.97%)

Driver gender

male

667 (89.89%)

94 (93.07%)

female

75 (10.11%)

7 (6.93%)

Driver educationb

illiterate

13 (1.75%)

3 (2.97%)

primary

69 (9.3%)

7 (6.93%)

nonacademic

595 (80.19%)

76 (75.25%)

academic

65 (8.76%)

15 (14.85%)

Driver job

jobs with high economic status

642 (86.52%)

85 (84.16%)

jobs with middle economic status

60 (8.09%)

14 (13.86%)

jobs with low economic status

40 (5.39%)

2 (1.98%)

Driver age (years)c

Child (< 18)

1 (0.13%)

0 (0%)

Adult (18 -65)

694 (93.53%)

92 (91.09%)

Elderly (> = 65)

47 (6.33%)

9 (8.91%)

Type of driving license

class A

83 (11.19%)

7 (6.93%)

class B

250 (33.69%)

33 (32.67%)

class C

393 (52.96%)

58 (57.43%)

motorcycle

6 (0.81%)

0 (0%)

no license

10 (1.35%)

3 (2.97%)

Driver seatbelt usage status

used

525 (70.75%)

58 (57.43%)

not used

217 (29.25%)

43 (42.57%)

Driver Judiciary cause

carelessness

725 (97.71%)

94 (93.07%)

other

17 (2.29%)

7 (6.93%)

Driver misconduct

spiral movement

356 (47.98%)

6 (5.94%)

over speeding

326 (43.94%)

66 (65.35%)

other

60 (8.09%)

29 (28.71%)

  1. aLow-risk colors: white, yellow, cream, pink, orange, brown; High-risk colors: silver, graphite gray, black, blue, green, dark blue, gray, purple, red [14]
  2. bPrimary: literacy and elementary education; non-academic: cycle, middle school, and diploma; academic: Bachelor's (B.Sc.), Associate's (A.Sc.), Master's (M.Sc.), and Doctorate (Ph.D.) degrees
  3. cAge categories based on the driving regulations in the country