based on the maximum representable contrast of the object from 0% in steps of 10%, until the object can be safely detected for the first time. Based on this value, the initial values can be set flexibly. According to preliminary tests SO was set to 99%
and SU to 5% of this contrast.
A detailed description of the adaptive methods is omitted here. A more detailed description of the Automatic Staircase method used in this work can be found in [6].
2.5. STATISTICS 47 be understood as a decomposition of the total variance. An advantage of using analysis of variance is that it is very robust against infringements of assumptions.
For the following investigations, the requirements were proven and deviations were considered to be sufficiently small.
2.5.2 Significance tests
Table 2.3 provides an overview of possible test procedures that can be applied to interval scaled and normal distributed variables. There are a number of methods that can describe the relationship between two variables.
Number of samples Dependence Test
2 Independent t-test
2 Dependent t-test for dependent samples
>2 Independent One-factor variance analysis
>2 Dependent One-factor variance analysis with repeated measurements
>2 Independent Two-factor variance analysis
>2 Dependent Two-factor variance analysis with repeated measurements
Table 2.3: Test procedures for interval scaled and normally distributed variables according to [35].
A variance analysis with repeated measurements considers that more than two dependent variables are related to one another [35]. If two or more samples exist, the samples can be compared in pairs, but with a small sample number, this becomes problematic. Therefore, a global test is used to prove all samples. In this work, a two-factor variance analysis is used as global test. If this test provides a significant result, the samples are compared in pairs to determine possible significances. Using those methods clear distinctions must be made between individual definitions:
• Detection: Is the luminance difference or contrast of an object just noticeable?
• Simple identification: Is an object perceivable based on a specific attribute?
• Complex identification: Is an object perceivable based on all attributes?
A detailed description of the different statistical methods can be found in [35] or [68].
Chapter 3
State of the art
The following chapter provides an overview of the current state of the art and regulations that must be taken into account when implementing new headlamp systems. In addition, accident statistics are consulted to underline the importance of the topic.
3.1 Accident statistics
For better understanding the safety aspect of the road network in Germany, a brief overview of the current accident statistics is provided. Two-thirds of the accidents in road traffic occur at night-time outside urban areas and mostly under unfavor-able weather conditions without any street lighting. 80% of the fatal accidents with pedestrians happen in the dark. Since there are not many pedestrians out at night-time the accident risk can classified as significantly high. Additionally it should be noted, that approximately 85% of the pedestrians wear dark clothes with a small reflection coefficient [69]. From CIE No.191 [69] it can be inferred:
“A pedestrian wearing grey clothing seen against the road surface (black/grey) has achromatic contrast whereas a pedestrian with coloured clothing has chromatic contrast. Also, coloured traffic signs have chromatic contrast against the surround-ing scene due to the selective reflectance of the coloured marksurround-ings at different wavelengths.”
A total of 2.5 million traffic accidents occurred in Germany in 2015, with 2.2 mil-lion accidents involving no personal injury. In the remaining 0.3 milmil-lion casualties, 1% (3,459) of the accidents were fatal, in 22% (68,706) the road users were badly hurt and 76% (233,494) of the cases were only slightly injured [70]. Of the total of 3,459 fatal accidents, 1,024 people aged 65 or more were concerned. Furthermore 1,181 of the fatal accidents took place at night or at dusk. A significant improve-ment could be achieved, as in 1991 about 11,300 people were killed [71]. Of the 0.3 million accidents involving personal injuries, about 3097 people were involved in an accident with animals on the road, 2228 of the animals involved in the accident were wild animals [8] (compare Figure 3.1). Overall, a total of 651 accidents with objects on the road were recorded.
Since in this work the influence of the age is also considered, age-related accident statistics are also of interest. The percentage of people aged 65 and over as a whole is growing steadily, from 15.5% to 21.0% in the last 20 years [9].
At the end of 2014, a total of 17.1 million people aged 65 years and older lived 48
3.1. ACCIDENT STATISTICS 49
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 0
2200 2400 2600 2800 3000 3200
Year
Numberofinjuredpersons
Figure 3.1: Number of injured persons in accidents caused by wild animals on the road (in Germany) according to [8].
in Germany. In 2015, 73,338 elderly people were involved in accidents involving personal injuries, which was 12.9% of all accidents. As a result, seniors have a distinctly minor part of accidents compared to their part of the population, which can be explained by their reduced attendance in traffic as vehicle drivers. Seniors are more active these days than former generations and are more likely to use a vehicle, but overall, their average driven distances per year is still significantly lower compared to younger age groups [9]. The group of seniors is a very inhomogeneous age group, as far as their perception, visual performance and health are concerned.
In particular, the deterioration of the visual faculty and reduction of the reactiv-ity with increasing age are important influence factors. The availabilreactiv-ity of older people, especially older women, is also significantly lower than the amount of male seniors [9]. The type, duration and frequency of the participation in road traffic of older male drivers differs significantly from younger age groups and thus have an impact on the accident behaviour.
In 2015 a total of 48,690 people aged 65 or more had accidents in road traffic, 35,267 seniors were slightly injured (increase of 2.4%) and 12,399 were badly injured (increase of 1.7%) [9]. This resulted in an accident increase of 2.3% compared to the previous year.
Complex situations in road traffic are more difficult to cope for older participants than for younger age groups. For example, “off-road driving” was the most common cause of accidents of 467,81 vehicle drivers involved in personal injuries (17.7%). It was followed by “turning, reversing and starting” corresponding to 16.5%. Thus, the accident causes point to age-related limitations of visual perception.
As illustrated in Figure 3.2 a total of 46,781 accidents involving personal injury occurred to drivers who were at least 65 years old, 36,916 were accused of misconduct
in road traffic. For old pedestrians the most frequent accident was “wrong behaviour when crossing the road”(80.8% ). In over half of the cases (66.4%) it was “crossing of the road, without paying attention to vehicle traffic”. Further casualties had a significantly lower importance [9].
Right ofway Vehicle
control
DistanceMisconduct Unadapted
speed Wrong
roaduse Overtak
e
Alcohol 0
2000 4000 6000 8000
Numberofinjuredpersons
Figure 3.2: Misconduct of seniors at the age of 65 years and older as vehicle driver accord-ing to [9].
For the reasons outlined above, it is definitely necessary to performe both age-based examinations and investigations, which examine the perception of an object, in more detail.