There is a well-established relation between speed and occurrence of traffic accidents. If the average speed in a street decreases by 1 km/h the frequency of accidents reduces by 3-5%. In order to decrease the number of traffic accidents and feeling of insecurity in urban areas, increased knowledge concerning relations between car drivers' choice of speed and street design are of great importance.
The aim of this study is to clarify which of the variables that describe the street's geometrical design have an effect on speed.
Another purpose is to illustrate which of the most frequent geometrical events in the street have the highest influence on car driver's choices of speed.
The objective is to reach an understanding of the relation between vehicles' average speed and geometrical design in a specific street segment. It is hoped that this knowledge will bring a better understanding of how we can influence car driver's choice of speed by using different types of changes in designing the street.
In this project the speed behaviour of passing motorists has continuously been studied in two directions in 14 different street segments. Traffic volume on the studied streets varied from 1600 to 9500 vehicles per day and street width varied from 6.6 to 12.9 metres. The first step was to identify street incidents that had an effect on the speed behaviour. Thereafter, car drivers for whom speed affecting street incidents occurred were removed from the material. With the remaining material a mean speed for each segment and direction were calculated. Those mean speed values were related to variables documented for each street's segment.
Regression analyses resulted in the following model (R2=0,92): Mean speed = 16,24 -0,030 * crossing pedestrians and cyclists per hour and 100 m +0,061 * number of passing vehicles per hour in current direction +3,942 * -0,041 * number of passing pedestrians and cyclists per hour +0,368 * average width form pavement to nearest building or tree.
A simplified model was also created and used.
The study found an obvious relation between measured speed, the actual street design and traffic intensity. The conclusion of this project is that it will be difficult to secure that no one drives faster than for example 40 km/h, only using the variables presented in the model. However, it should be possible to direct the mean and 90th percentile speed to desired level, using above mentioned variables.
Comparisons show that the results from this study are in line with results from other similar studies.
The study has partly brought light to new knowledge about the relation between speed, street design and other events in the street. There is an obvious relation between speed and lane width that ought to be used in future street design in order to achieve fewer traffic accidents.
It ought to be possible to lower the average speed by using the studied variables, lane width, parking density, traffic intensity, number of pedestrians crossing, etc. If this work is done in more than only in a few streets it will probably also have a positive effect on the small group of drivers that drive very fast and cause most of the major traffic accidents in urban areas.