Fuzzy logic in car safty
Car safety issues are wide-reaching problem. This problem is mainly due to human driving which involves reaction times, delays, and Judgment errors that may affect traffic flow and cause accidents. In some cases, the cause of the accident is distraction on the part of the driver and failure to react in time. Even in some cases, it could be cause by environmental factors (Song, 2005). Advanced system of auxiliary functions has been developed to help avoid such accident and minimize the effects of collision should one occur.
Fuzzy logic provides tools for dealing with imprecision, which is fundamental to many engineering problems. The level of safety in our society could be archived by applying fuzzy logic control system. Fuzzy logic control technique has become an active area of research in the application of industrial processes, which are not friendly to straight control techniques. It attempts to emulate human mind for checking the processes parameters and to take decisions regarding the control action (Eugene, 1985).
Fuzzy control become a huge industry in Japan and other countries where it was adapted into home appliances such as scum cleaners, microwaves ovens, video cameras, washing machines, etc. A fuzzy controller acts or regulates by means of rules in a more or less natural language, based on the distinguishing feature: fuzzy logic. On the other hand, to reduce car accidents we are going to examine a system, which makes the drivers, pay more attention and alert them before an accident takes place.
Because of this, we shall acknowledge the digital systems because they are easier to handle with, so the first thing in the development is to convert all variations in the car environment into digital signals without any changes. The ultrasonic transmitter circuit sends its vibrations in front of car, when these vibrations reflected the ultrasonic receiver circuit would take these vibrations and amplify it. Moreover, send it to the microelectronic, which can compute the distance between the car and anything in front it (as shown in the figure 1 below).
At the same time, the Infrared ‘R) circuit senses the round of the wheel and sends it signal to the microelectronic, which can compute the car speed. After that, the microelectronic sends the output signal to the speaker and The LCD. In addition, of these output devices the microelectronic sends output data to a personal computer using the serial port. Figure 1: Overview of the used hardware; copied figure (from Journal of Computer science 4 (1 2): 1061-1063, 2008]) We shall consider developing level of safety under three steps, which are: Defining level of safety Calculating each degrees of risk between two vehicles, and Combining these degrees to level of safety with average speeds in some divisions (Method et al, 2001). In the other hand, to ascertain the danger degrees of each car, and the base elements, fuzzy sets and their membership functions, are define by using survey data and degrees of risk (Chunk, 2003). In addition, if-then rules of inference engine are made by rough set theory.
Conclusively, to get the level of safety in some divisions, fuzzy membership function values of each safety result is averaged, and a method to et ‘Level of Safety based on these degrees relates with an average of safety speeds is suggested. Definition of Level of Safety Safety being a wide-reaching problem, has gained various definitions from several authors. The level of safety in a road division means the grades, which people feel about the possibility to experience, rear-end collision including relentlessness in the division (Song, 2003).
This definition is composed of three elements related with roads in themselves, driving behaviors in this road, and relation between drivers and roads. These three factors are mix in microscopic driving behaviors on roads, and five gyroscopic traffic condition variables are selected such as velocity and acceleration of lead and following cars, and the gap distance between these cars divided the minimum safety distance (Method et al, 2001). The minimum safety distance (MS) is the distance that following car needs to avoid a rear-end collision.
The traffic condition in itself can be included into velocity, drivers’ behaviors are able to be included into oscillations of accelerations in every two seconds, and degree of risk in the system can explain the gap distance divided the minimum safety distance (MS). Where, : following Car speed Response time : Possible deceleration rate However, these results are not level of safety but risk degrees of two Cars (Fuller, 2005). Definition of Fuzzy Sets and Membership Function The member functions are divided into speed fuzzy sets and acceleration fuzzy sets (Method et al, 2001).
Speed fuzzy sets are composed of three sets, ‘high speed’, ‘medium speed’, and ‘low speed’. Their membership functions are based on macroscopic traffic condition data and number of accident. Acceleration fuzzy sets also consist of three sets, ‘positive acceleration’, ‘no acceleration’, and ‘negative acceleration’, and membership functions, which are based on microscopic field, survey data and maximum and common acceleration rates of vehicles. The gap distance/MS sets are divided into three fuzzy sets, ‘more than 1’, ‘around 1’, and ‘less than 1’ using microscopic data.
The combined danger degrees are about from 0. 4 to 0. 55 that corresponds to common situation defined in fuzzy set, and this result means that people drives more or less safely bearing some anger because there are possibility to happen accidents in traffic condition in itself but drivers believe that they can response properly to a danger situation. Moreover, this result shows that there are some danger situations n each two vehicle, but in road divisions, the danger degrees become normalized.
Figure 3: Relation between Speed and Danger Degrees For this reason, ‘Level of Safety should not include the combined danger degree directly, and should be deducted from relationship between speeds as well as danger degrees. In order to find their relation, pairs of average speed and danger degree are, shown in figure 3. We find that danger degrees are low in low speed level and high in fast speed level, and the level of change is not high in low and rapid speed situations. However, in medium speed case, danger degrees are increase vapidly, and there are two points of inflection.
If danger degrees do not change rapidly, drivers would react properly because their expectations to the road conditions are fixed, but if they change fast, the situation on a road division would be dangerous because the expectation of drivers cannot be fix. Consequently, the simple possibility of accidents depends on the grades of change in danger degrees, and the severity depends on the quantity of danger degrees. Conclusively, this seminar suggests ‘Level of Safety such as in Figure 4. First, range of Level of Safety in which relentlessness and possibility of accident is high is defined as Very dangerous situation’, E.
Similarly, that of range which relentlessness or possibility is high is suggested as ‘dangerous situation’, D, and which relentlessness and possibility is usual as ‘common situation’, C, and which possibility is low and relentlessness is high as ‘safe situation’, B, and which possibility and relentlessness is low as Very safe situation’, A, these are shown in Table 3 below. Finally, relation of danger degrees and average speeds develops the intercepts of each level of safety, UT it needs to be more precisely define by further study based on more investigation.
Table 3: Level of Safety Definition The possibility The severity The range(km/hrs) Very safe -18 c 25-40 (or) High 18-25, 40-53 53-63 Figure 4: copied figure (from [Proceedings of the Eastern Asia Society for Transportation Studies]) 8. 0 CONCLUSION This seminar work shows how the system provides a solution to decrease the car accidents by giving the drivers more time to avoid the accidents. Adjusting the sensitivity and the accuracy for the measuring circuits is important to ensure that the assured parameters represent its actual values.
The use of microelectronic makes it possible to implement the system with less hardware components. The microelectronic, FISTICUFF was chosen among all the other microelectronics because of its low-cost and small size. In addition, we evaluated safety degrees on a road division, and suggest ‘Level of safety. The method to develop ‘Level of Safety from degrees of danger and combined using fuzzy theory, and we combined danger degrees to define level of service with average speeds. This is the first trial to define