**CHAPTER 4 Modelling road safety in twenty-one countries**

**4.13 Israel**

For Israel, a model of the fatality rate was constructed using the all-occupant seat belt wearing rate, alcohol tests per vkt, and a time trend prior to 1973. The results are shown in Table 4.59.

Table 4.59 Regression results for predicting the Israeli fatality rate

*Regression Statistics*

Multiple R 0.9934037

R Square 0.9868510

Adjusted R Square 0.9859545 Standard Error 2.2132603

Observations 48

ANOVA

*df* *SS* *MS* *F* *Significance F*

Regression 3 16176.20289 5392.0676 1100.7541 2.20724E-41

Residual 44 215.53493 4.8985211

Total 47 16391.73782

*Coefficients Standard Error* *t Stat* *P-value* *Lower 95%* *Upper 95%*

Intercept 51.596920 1.004868 51.346942 0.000000 49.571741 53.622099

Belts -0.460845 0.019576 -23.540778 0.000000 -0.500299 -0.421391

Alcohol -0.814020 0.109229 -7.452432 0.000000 -1.034156 -0.593884

Timeles73 0.855604 0.203982 4.194515 0.000130 0.444506 1.266701

Figure 4.181 shows the pattern of the fatality rate is fairly accurately predicted by the model.

Figure 4.181 Actual/predicted Israeli fatality rate

Fatalities per billion safety-wgt vkt

2029 2027 2025 2023 2021 2019 2017 2015 2013 2011 2009 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965

Actual Predicted

0 10 20 30 40 50 60 70

Figure 4.182 shows the components of the Israeli fatality prediction/forecast. The major influence is the increase in seat belt wearing. From the early 90s, alcohol control starts to have an effect.

Figure 4.182 Components of the Israeli fatality rate prediction

Fatalities per billion safety-wgt vkt

Impact of seatbelts + alcohol + time pre-1973

Fatality rate Impact of seatbelts Impact of seatbelts + alcohol

2029

Figure 4.183 shows that the modeling also produces a fairly accurate prediction of the level of fatalities over time.

Figure 4.183 Actual/predicted Israeli road deaths

2029

Actual Predicted

0

Chapter 4 • Modelling road safety in twenty-one countries The safety weights applied in Israel were cars, light commercial vehicles and other vehicles 1.0, motorcycles 7.0, buses 1.5, trucks 2.0 and mopeds 3.5. The injury weighted vkt calculation used the same weights.

In Israel, the injury rate (road injuries per billion injury-weighted vkt) moved in sync with the fatality rate, aside from three shifts in level. This is shown in Figure 4.184.

Figure 4.184 Israeli injury and fatality rates

2009 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965 0 500 1000 1500 2000 2500 3000 3500 4000

Fatalities per billion safety-wgt vkt

Injury rate Fatality rate

Injuries per billion injury-wgt vkt

-4 6 16 26 36 46 56 66

A model of the injury rate was constructed using the fatality rate, alcohol tests per vkt, and three dummy variables. The regression results are shown in Table 4.60.

Table 4.60 Regression results for predicting the Israeli injury rate

*Regression Statistics*

Multiple R 0.9811801

R Square 0.9627143

Adjusted R Square 0.9580536 Standard Error 118.4877931

Observations 46

ANOVA

*df* *SS* *MS* *F* *Significance F*

Regression 5 14499820.63 2899964. 206.55961 1.88198E-27

Residual 40 561574.2841 14039.35

Total 45 15061394.92

*Coefficients Standard Error* *t Stat* *P-value* *Lower 95%* *Upper 95%*

Intercept 479.18712 86.34292 5.54981 0.00000 304.68156 653.69268

FatalRate 44.79061 2.17505 20.59290 0.00000 40.39467 49.18656

Alcohol -15.74899 10.76403 -1.46311 0.15125 -37.50391 6.00592

Dum6779 -508.60554 66.53427 -7.64426 0.00000 -643.07630 -374.13477

Dumles89 -448.43678 87.14308 -5.14598 0.00001 -624.55951 -272.31405

Dum07on -145.91217 113.61256 -1.28430 0.20643 -375.53172 83.70737

Figure 4.185 shows the pattern of the injury rate is fairly accurately predicted by the model.

Figure 4.186 shows that the modeling also produces a fairly accurate prediction of the level of injuries over time.

Figure 4.185 Actual and predicted Israeli injury rate

2029

Actual Predicted

0

Figure 4.186 Actual and predicted Israeli road injuries

2029

Actual Predicted

0

Chapter 4 • Modelling road safety in twenty-one countries

### 4.14 Japan

For Japan, a model of the fatality rate was constructed using the all-occupant seat belt wearing rate and two infringements variables (described in Appendix B), As well, there is a dummy variable for the lowering of the legal blood alcohol limit, and a time trend prior to 1974. The results are shown in Table 4.61.

Table 4.61 Regression results for predicting the Japanese fatality rate

*Regression Statistics*

Multiple R 0.9919572

R Square 0.9839792

Adjusted R Square 0.9821163 Standard Error 2.1498208

Observations 49

ANOVA

*df* *SS* *MS* *F* *Significance F*

Regression 5 12206.00891 2441.2017 528.20091 2.00656E-37

Residual 43 198.7343717 4.6217295

Total 48 12404.74328

*Coefficients Standard Error* *t Stat* *P-value* *Lower 95%* *Upper 95%*

Intercept 41.103800 2.579189 15.936714 0.000000 35.902369 46.305230

SeatBelts -0.084238 0.019500 -4.319816 0.000090 -0.123564 -0.044912

Infringements -0.124081 0.016105 -7.704480 0.000000 -0.156560 -0.091602 Infr Increase -0.180227 0.067438 -2.672480 0.010595 -0.316230 -0.044225

Timeles74 3.076448 0.172872 17.796147 0.000000 2.727819 3.425077

BAC .3 -1.715091 1.165705 -1.471290 0.148494 -4.065960 0.635778

Figure 4.187 shows the pattern of the fatality rate is fairly accurately predicted by the model.

Figure 4.187 Actual/predicted Japanese fatality rate

Fatalities per billion safety-wgt vkt

2029 2027 2025 2023 2021 2019 2017 2015 2013 2011 2009 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965 0 10 20 30 40 50 60 70

Figure 4.188 shows the components of the Japanese fatality prediction/forecast. The major influences are pre-1974 ‘learning’ and enforcement. From the early 80s, seat belt wearing starts to have an effect, as does the lowering of the legal blood alcohol limit in 2003.

Figure 4.188 Components of the Japanese fatality rate prediction

Fatalities per billion safety-wgt vkt

Fatality rate 0

Impact of infringements Impact of infringements + seatbelts Impact of infringements + seatbelts + BAC limit

Impact of infringements + seatbelts + BAC limit + time pre-1974

2029

Figure 4.189 shows that the modeling also produces a fairly accurate prediction of the level of fatalities over time.

Figure 4.189 Actual/predicted Japanese road deaths

Actual Predicted

2029

Chapter 4 • Modelling road safety in twenty-one countries The safety weights applied in Japan were cars, light commercial vehicles and other vehicles 1.0, motorcycles 4.3, buses 1.5, trucks 2.0 and mopeds 7.1. The injury weighted vkt calculation has motorcycles at 3.5 and mopeds at 10.5.

In Japan, the injury rate (road injuries per billion injury-weighted vkt) moved in sync with the fatality rate except at the beginning and end of the period. This is shown in Figure 4.190.

Figure 4.190 Japanese injury and fatality rates

2011 2009 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 1979 1977 1975 1973 1971 1969 1967 1965 1963 -200

300 800 1300 1800

Fatalities per billion safety-wgt vkt

Injury rate Fatality rate

Injuries per billion injury-wgt vkt

-15 -5 5 15 25 35 45 55 65 75

A model of the injury rate was constructed using the fatality rate and two time trends – from 1994 to 2002 and prior to 1967. The regression results are shown in Table 4.62.

Table 4.62 Regression results for predicting the Japanese injury rate

*Regression Statistics*

Multiple R 0.9876659

R Square 0.9754840

Adjusted R Square 0.9738496 Standard Error 47.3902406

Observations 49

ANOVA

*df* *SS* *MS* *F* *Significance F*

Regression 3 4021252.385 1340417.4 596.84594 3.11263E-36

Residual 45 101062.5708 2245.8349

Total 48 4122314.956

*Coefficients Standard Error* *t Stat* *P-value* *Lower 95%* *Upper 95%*

Intercept 230.54060 20.40881 11.29613 0.00000 189.43514 271.64606

FatalRate 35.25461 0.89990 39.17630 0.00000 33.44212 37.06709

Timeles67 -232.83920 10.87965 -21.40136 0.00000 -254.75194 -210.9264

Time9402 51.00258 2.37255 21.49699 0.00000 46.22403 55.78113

Figure 4.191 shows the pattern of the injury rate is fairly accurately predicted by the model.

Figure 4.192 shows that the modeling also produces a fairly accurate prediction of the level of injuries over time.

Figure 4.191 Actual and predicted Japanese injury rate

Actual Predicted

Injuries per billion injury-wgt vkt

2029

Figure 4.192 Actual and predicted Japanese road injuries

Actual Predicted

2029 200 000 400 000 600 000 800 000 1 000 000 1 200 000 1 400 000

Chapter 4 • Modelling road safety in twenty-one countries