טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
Ph.D Thesis
Ph.D StudentElias Wafa
SubjectThe Effect of Activity Patterns on Road Accidents:
Case Studies of Bypassed Towns
DepartmentDepartment of Architecture and Town Planning
Supervisors Professor Tomer Toledo
Professor Yoram Shiftan
Full Thesis text - in Hebrew Full thesis text - Hebrew Version


Abstract

This study analyzes the impact of infrastructural development in general, and bypass roads in particular, on road safety. Specific attention is given to the influence of the daily activity patterns of individuals and their demographic and social-economic characteristics on the risk of being involved in car accidents.

The methodology used in this research deals with the subject with an overall approach by employing a number of methods: firstly, the development of a theoretical framework which explains the effects of bypass roads on several variables and their impact on car accident involvement risk. Secondly, the use of an aggregate method so as to test, at a given time, the change in the spatial spread and pattern of business establishments, the change in the spatial spread of residences and the change in the safety level. Within the framework of the research, it was decided to focus on the Arab sector of the population.


A main element of this framework is the development of a disaggregate method.  This includes a risk model based on activities, which enable the prediction of expected changes in the risk level, and which takes the individual's daily activity patterns, the demographic and social-economic characteristics and similarly, the expected changes in activity accessibility into account. The day activity model was developed in order to enable the application of the risk model for the purpose of evaluating the potential effect of various policies so as to improve safety. 


Data collection was based upon two methods: firstly, aggregate data mapping over a period of time from a number of sources. Secondly, disaggregate mapping by means of a household survey including trip diaries. Moreover, personal interviews were held with drivers involved in car accidents, as well as with the families of children involved in pedestrian accidents. The disaggregate mapping of car accidents was also accomplished through access to police files.


The research findings demonstrate that daily activity pattern significantly affect the risk of car accident involvement. The results additionally show a significant connection between the demographic and socio-economic characteristics of the individual and accident-involvement risk. In particular, education level and possession of a driver license, especially concerning women, affect the daily activity patterns-particularly employment-as well as accident involvement risks.