Binary logit :

As discussed in reference to the severity of injury, the relevant section in the Binary Logit (BL) model assumes that the dependent variable falls into two categories. I this analysis, the dependent variable is represented by two categories of ROW and non ROW. A total of 942 pedestrian casualties resulting from the pedestrian-vehicle accidents that took place at pedestrian crossing were extracted of those pedestrian casualties that were involved in vehicle-pedestrian accidents at pedestrian crossing: 25.1% were classified as ROW1 and 74.9% were classified as non ROW. Table 6.5 below shows the coefficients’ estimated results of the Binary Logit model, the p-values (measure of significance), the _ρ2 _{and the Log-likelihood values. Table 6.1 provides a}

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Table 6. 4: Summary of statistics and estimation results of the Binary Logit aggregate model by pedestrians’-car accidents

Variable Categories of each variable Frequency (%) Coefficients (p-value) Odds

Child (0-15) 105 (11.1%) -0.61 (0.093) 0.544 Adult (16-59) 731 (77.6) -0.17 (0.570) 0.846 Age group Old (60+) 89 (9.4) 0 -- Female 327(40.5) -0.32 (0.068) 0.728 Gender Male 481 (59.5) 0 -- 16-21 79 (8.4) 0.63 (0.127) 1.873 22-59 704 (74.7) 0.60 (0.056) 1.823

Driver age group

60+ 54 (5.7) 0 -- Night time 271 (28.8) 0.24 (0.262) 1.267 Time of accident Day time 671 (71.2) 0 -- Crossing 765 (81.2 -0.13 (0.631) 0.878 Pedestrian movement Not crossing 177 (18.8) 0 -- Going ahead 754 (80.0) 0.27 (0.217) 1.304 Vehicle manoeuvre Other 172 (18.3) 0 --

Bus and goods vehicles 287 (30.5) 0.32 (0.137) 1.374

Heavy goods vehicles

Other 655 (69.5) 0 --

Pelican 232 (24.6) -0.72 (0.000) 0.486

Type of signalised pedestrian

crossing junction 710 (75.4) 0 --

One way street 14 (1.5) -22.02 (1.000) --

Dual carriageway 131 (13.9) -20.70 (1.000) -- Single carriageway 794 (84.3) -20.78 (1.000) -- Type of road Other 3 (0.3) 0 -- 1-2 lanes 582 (61.8) -0.11 (0.610) 0.900 3-4 lanes 212 (22.5) 0 --

Width of single carriageway

Other 148 (15.7) 0 --

Crossing from driver offside 298 (31.6) 00.17 (0.353) 1.190

First impact of pedestrian

accidents Other 644 (68.4) 0 --

Weekend 265 (28.1) 0.20 (0.322) 1.224

The day of accidents

weekdays 677 (71.9) 0 -- Wet 281 (29.8) -0.24 (0.306) 0.785 Road condition Dry 658 (69.9) 0 -- Fine 783 (83.1) 0.40 (0.504) 1.491 Rain 135 (14.3) 0.28 (0.636) 1.329 Weather Other 24 (2.5) 0 -- Factors Intercept _{-- --} 21.23 (1.000) 1.652 Summary Statistics -2 Log-likelihood at zero = 906.53 -2 Log-likelihood at convergence = 861.351 Log-likelihood ratio index (ρ2) = 0.081

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The negative sign for the coefficient for age groups (child and adult groups) indicates that the child and adult groups are more likely to be involved in accidents in pedestrian ROW than the older group. The odds ratios for the child group indicate that when assuming all predictors are constant, the child group is 0.54 times more likely to be involved in accidents in ROW than the non-pedestrian ROW. The adult group is 0.85 times more likely to be involved in accidents involving pedestrian ROW situations than non-pedestrian ROW.

Regarding the gender of casualties, the negative signs indicate that the female group is more likely to be involved in accidents than the male group in pedestrian ROW. The female group is 0.73 times more likely to experience pedestrian accidents in the pedestrian ROW than the male group. The positive sign for the coefficient of the driver age group (young driver 16-21 and adult driver 22-59) indicates that these age groups are more likely to be involved in pedestrian accidents in non-pedestrian ROW areas. Driver age groups (young and adult) are 1.87 and 1.82 times, respectively, more likely to be involved in pedestrian accidents in non-pedestrian ROW areas than the elderly group.

The positive sign for the coefficient for accidents at night indicate that there were more accidents at this time in non-pedestrian ROW areas than in pedestrian ROW areas. Inverting the odds ratio for night accidents reveals that pedestrians are 1.27 times more likely to be involved in accidents in non-pedestrian ROW areas. In terms of pedestrian movement (crossing the road or not crossing), the negative signs indicate that pedestrians who crossed the road from the driver’s nearside and driver’s offside were more likely to be involved in accidents involving pedestrian ROW than pedestrians who were standing or walking along the carriageway. The odds ratio for pedestrian movement indicates that pedestrians who crossed the road in pedestrian ROW incidents were 0.88 times more likely to be involved in accidents than those who were standing on, or walking along the carriageway.

In consideration of vehicle manoeuvres, the positive signs indicate that when the vehicle is travelling ahead it is more likely to be involved in accidents involving non-pedestrian ROW than when performing other manoeuvres (turning, reversing and starting). The odds ratio for manoeuvres involving vehicles show that the going ahead manoeuvre caused more accidents than other manoeuvres (1.30). Regarding the type of vehicle, the

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positive sign indicates that heavy goods vehicles and buses are more likely to be involved in pedestrian accidents in non-pedestrian ROW than cars, taxis and motorcycles. The odds ratio for this category is 1.37.

The negative sign for pedestrian crossing facilities indicates that more pedestrian accidents occurred within pelican, puffin and toucan areas than at junction crossings in pedestrian ROW cases. The odds ratio for pedestrian crossing facilities indicate that at pelican, puffin and toucan crossings there are 0.49 times more accidents than at junctions in pedestrian ROW accidents. The positive sign for the coefficient for one and two lanes in a single carriageway indicate that on single carriageways there were more pedestrian accidents over one and two lanes in the non-pedestrian ROW than occurred over three or more lanes. Inverting the odds ratios for one and two lanes indicated that 0.90 more slight accidents occurred on one and two lane single carriageways than on other types.

The positive sign for the coefficient when crossing the road from the driver’s offside area indicates that more pedestrian accidents occurred in non-pedestrian ROW areas when pedestrians crossed the road from the driver’s offside area. The odds ratio for this category is 1.19. Regarding the day on which accidents occurred, the positive sign for the weekend indicates that pedestrians who were involved in accidents at the weekend were more likely to be involved in accidents in non-pedestrian ROW areas, than those that happened on the weekdays. The odds ratio for this category is 1.22.

In consideration of the road condition, the negative sign for wet road condition indicates that there were more pedestrian accidents occurring in pedestrian ROW areas than non- pedestrian ROW. The odds ratio for road conditions showed that wet roads caused more accidents in cases of pedestrian ROW than road conditions (0.79). The positive sign for the coefficient of fine and rainy weather indicates that more pedestrian accidents occurred in fine and rainy weather in non-pedestrian ROW areas. The odds ratio for these categories are 1.49 and 1.33 respectively.