Safe School Zones

Florencia Victoria VassalloEstudiante de Doctorado

School zones: a review of literature

INDEX

Why school zones

Our study

Final remarks and possible new developments

Why school zones?

1. Why Children? 2. Why Schools?

✓ Children are among the most vunerable road users

✓ Children and adolescents are the workers for the future

✓ School are at the center of children daily activities

✓ Daily traffic increases during drop off and collecting times

Our study

✓ Main objective: to identify relevant literature describing and analysing the existing relationship between school zones and road safety. Attention: this is the first time that autores who do research on road safety had work with this particular road safety measure.

✓ As a secondary objective, discover how the literaure assess the efficacity of school zones schemes to improve road safety

❖ 1. Step: make a review of existing literatura. To do this, performed a web-based search using Keywords

❖ 2. Step: Keywords: school zones, speed reduction, speed decrease . We use Google Scholar as engine. We limited the search to academic articles, guidelines or grey literature. Blogs, articles from newspapers or books were banned.

❖ 3. Step: Complete the review of literature by manual search

❖ 4. Step: In order to identify literature that could be part of our corpus, it should analyse a certain school zone experiment. Under this assumption, papers that just mention “school zones” as an element of road safety have not been taken into account. We analysed the title and the abstract. Whenever these elements were not enought to find out if the article contradict or not our rule to be included, we read the whole content.

❖ 5. The results of the research had been resumed in an Excel sheet.

a. Journalb. Wether the Journal is a JCR or notc. Year of Publicationd. Authorse. Place were the scheme had been implementedf. Title of the Articleg. Variable used to measure the efficacity of the interventionh. Outcome

6. In order to follow with the work, we should be able to categorize the articles according to some issues

• 14 articles analysed the effects on speeds after installing speed control devices

• 8 articles analysed behavior of drivers in school zones (many of them using surveys to ask drivers)

❖ 7. A total of 41 articles had been identify. According to our revision

• 6 articles analysed the impact of school zones on: 3 on crashes (1 was in Korean) & 3 on speed reduction

• 3 articles analysed guidelines and general frameworks to build up school zones

• We had no access to 3 articles (not even to the abstract)

• 3 articles used simulation in order to assess the impact of school zones schemes

• 4 articles trated the impact of school zones on crashes on the journey to school

As our objective was to identify literature that assessed a direct effect of speed school zones on crashes, we have choosen to analyse the content of the group with articles about the effects of school zones on crashes involving children in the journey to school.

The papers were:

❖ Abdel-Aty et al. (2007)

❖ Kingham et al. (2011)

❖ Preston (1995)

❖ Warsh et al. (2009)

All the papers were published by JCR journals

1. Abdel-Aty et al. (2007)

➢ Data and Design of the experiment

➢ Main Findings

• 5 year crash data on state roads in Orange County, Florida of school-aged children (4-18) involved in crashes.• Crashes occurred during weekdays in the time periods 6.30-10 am and 1-5 pm are assumed to be school-trip-related crashes.• 2 Methods: geo-spatial analysis & log-linear analysis (using variables such as driver’s, pedestrian & cyclists’ characteristics, contributing cause of

drivers, traffic control measures, site location, driver’s alcohol use, number of lines…). The log-linear had 2 versions: driver-related models and pedestrian/cyclist-related model.

From geo-spatial

analysis:

✓ A majority of school-aged children crashes occurred near schools.

✓ In the zones within a half mile of the schools, there were more crashes involving school-aged children aroundmiddle & high schools than elementary schools.

From log-linear analysis:

✓ Middle-aged, aclohol-impaired and male drivers are more likely to be involved in school-aged children crashes

✓ Pedestrian’s/Cyclist’s ages are closely correlated with some road geometric and traffic characteristics (number oflanes, speed limits, speed ratio) in school-aged children crashes.

✓ The interaction effects of these variables on crash frequency (odds multipliers) indicate that higher crashinvolvement is associacted with high and middle school children in high-speed multilane roadways tan Elementary school children.

2. Kingham et al. (2011)

➢ Data and Design of the experiment

➢ Main Findings

• 25 years (1980-2004) of crashes data that resulted in 28,645 geocodede crash points. The data was aggregated every 15 minutes and grouped into 5 years periods.

• ArcGis was used to cluster geographical information. Identified hotspots were compared with the location of schools.

• Method: geo-spatial analysis used accidents occurred during school term time 8-9 am and 3-6 pm.

✓ There have been an overall increase in traffic volumen over 30 years, with a general decline in the number of road traffic accidents, but it wasnot uniform accros the day. There is evidence that accidents increased at 8-9 am and 3-3.15 pm but not form 5-6 pm.

✓ Spacially, we have not observed any evidence for accidents to occur in the immediate vicinity of schools. But the increase coincide with the time in wich children are dropped off and collected from school.

3. Preston (1995)

➢ Data and Design of the experiment

➢ Main Findings (on the journey to and from school section)

• Data about casualties is presented (casualties according to the age of the victim, child pedestrian death rates, casualties reduction –as a result of the adoption of traffic calming schemes). But this data is used to illustrate 8 ítems raleted to cost effective ways to increase safety of children and adolescents as pedestrians

• Many of the casualties incurred on the school journey occur near the schools.

• Traffic calming can be recommended for minor roads . On main roads, speed limits have to be enforced by the police.

• In Britain, school crossing patrols are provided to on some main roads near to primary schools but mosy local ahuthorities do not provide school crossing patrols for secondary school pupils.

4. Warsh et al. (2009)➢ Data and Design of the experiment

➢ Main Findings

• Data on all police-reported MVC involving pedestrians less than 18 years of age that occured in Toronto during (2000-2005). The ages were categorized as follows: 0-4, 5-9, 10-14, 15-17. School time are defined as 7-9 am, 12-1 pm, 3-5 pm.

• GIS were used to assess the distance of each collision relative to school location. School zone is defined as a 150 metre radius around a school. For the study, zones were created: 0-150 m, 151-300m, 301-450 m, >450 m.

• Methodology: frequency and % of collisions were calculated and chi-square test were used to compare the distribution of the characteristicswithin each zone.

✓ The risk ratio of a collision within the 150 m school zone was 5.7 compared to the largest zone (>450 m)

✓ The relative risk of a fatal collision within the 150 m school zone was 9.4 compared to the >451 m zone. ✓ The largest proportion of collisions was in the 10-14 year age group, followed by the 15-17 years-old, the 5-9 years-old and the 0-4 years-

old. In the 5-9 and 10-14 years-old groups, the proportion of collisions was highest in the areas closer to schools. Conversely, in the 15-17 year-old category, the proportion of collisions was highest at further distances from school.

✓ Almost 50% of collisions occurred over the hours defined as school-travel times.

✓ School zones, less tan 10 % of the surface area of the city, had a mich higher aboslute risk of child pedestrian collisions tan other áreas. The absolute density of injrueis and fatalities were 5.7 and 9.4 times higher in the school zones compared to the largest zone (>451 m zone)

Final remarks and possible new developments

Main Findings

Further developments

• Include new keywords and engines

• Study other groups of articles such as the behaviour one

• Try to perform a meta-analysis

Traffic increase significantly in school zones early in dropp off and collecting time

Traffic crashes increase significantly at the time where children enter and leave schools

Traffic calming measures and Education are two pillars to improve road safety forchildren.

High school students who walk or take a bus to go and leave school are taking more risk of having and accident than small children collected by their parents

Thank you!