Measuring the contribution of randomness, exposure, weather, and daylight to the variation in road accident counts

The influence of economic incentives linked to road safety indicators on accidents: The case of toll concessions in Spain

“…is the log-likelihood at converge, and is the log-likelihood at zero. It is an indication of the additional variation in accident frequency explained by the model to the constant term alone (Fridstrøm et al, 1995). Table 3 shows that all the variables have the expected sign according to the literature review.…”

“…Other studies have been carried out in recent years to establish the relationships between accidents and the effect of different vehicle mix (Tay, 2003;Hiselius, 2004;Wong et al, 2007;Haleem, 2011, Pei et al, 2011), the frequency of intersections (Ivan and O'Mara, 1997), environmental factors (Chang, 2005;Caliendo et al, 2007;Fridstrøm et al, 1995;Shankar et al, 1995), geometric infrastructure characteristics (Chang, 2005;Hauer et al, 2004), number of lanes (Noland and Oh, 2004;Chang, 2005;Milton and Mannering, 1998), and speed limits (Fridstrøm et al, 1995;Ossiander and Cummings, 2002;Wong et al, 2005).…”

Studying the effect of weather conditions on daily crash counts using a discrete time-series model

“…Temperature has found to be important, especially in combination with snowfall or rain (e.g., Branas and Knudson, 2001;Brown and Baass, 1997;Fridstrøm et al, 1995;Fridstrøm and Ingebrigtsen, 1991). We use the daily mean temperature in 0.1 degrees Celsius, the minimum temperature in 0.1 degrees Celsius and the maximum temperature in 0.1 degrees Celsius.…”

“…The amount of sunshine was found to be an important variable in the prediction of crashes. For instance, in Fridstrøm et al (1995), it was found that an extra hour of daylight between 7 A.M and 11 P.M decreased the the number of crashes in Norway by 4%. We use sunshine duration in 0.1 hour and percentage of maximum possible sunshine duration.…”

“…More specifically, serial correlation between successive daily crash counts, i.e. autocorrelation, is reported as an important challenge for all accident models (Levine et al, 1995;Fridstrøm et al, 1995Fridstrøm et al, , 1991. For instance, Miaou and Lord (2003), Shankar data.…”