CHAPTER 1 INTRODUCTION 1

CHAPTER 1
INTRODUCTION
1.1Introduction
This project is designed for probable visibility in foggy conditions. The main purpose of this project is to reduce accidents in fog and save human life. They are important because they help you to see through of the fog. It can be help pilots and drivers steer their vehicles at night and in fog it can be used in heavy rain to see the way clearly. Shown in (fig 1.1)
An infrared camera is a non-contact device that detects infrared energy(heat) and converts it into an electronic signal, which is then processed to produce a thermal image on a video monitor and perform temperature calculation.

Allow you to not only screen thermal performance, but also recognize and evaluate the relative brutality of heat-related problems. new innovations particularly detector technology, the incorporation of built-in visual imaging and automatic functionality.

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One of the innovations that were showcased at the 2005 Detroit auto show was the night vision systems in high end cars intended to improve driver safety for the duration of night time where there is insufficient illumination. This high technology safety option is probable to be available in the 2006 models of the Mercedes Benz S Class and BMW’s 7 series. The night vision systems use infrared sensors to let drivers see as much as three or four times farther ahead and help them quickly distinguish among objects. While night vision systems help reduce the chances of accidents, it is ultimately the driver’s responsibility to recognize obstacles in the road.1
In order to reduce traffic accidents involving animals, which is a major concern in worldwide traffic, Autoliv has developed a state-of-the-art vehicle mounted night vision animal detection system. The system is currently used by Audi, BMW and Daimler. The main contributions of this paper include: world’s first vehicular animal detection system to reach the customer market, an efficient classification approach based on a cascade boosting concept which is robust to occlusion, pose and scale variations, a large database of thousands of hours of far infrared (FIR) video data recorded worldwide including several hundred thousand example images of animals in traffic situations, a tracking approach to handle animal movement and estimate animal states, a validation approach to efficiently reduce the number of false detections and human-machine-interface (HMI) and warning concepts to highlight animals at risk of collision. The presented system detects animals up to 200 meters away from the car while generating very few false warnings. For animals that are considered a potential danger, advanced HMIs such as marking lights which actively illuminates the animals are applied, giving the driver the quick and accurate information he or she requires. The Autoliv night vision animal detection system is complementary to currently used methods for preventing accidents with animals. By using it, the driver is given all opportunities to react to dangerous situations and to avoid potential accidents.2
A night vision system must increase visibility in situations where only low beam head lights used today. As pedestrians and animals have highest risk increase in night time traffic due to darkness, the ability of detecting those objects should be the main performance criteria, and the system must remain effective facing the headlights of the oncoming vehicle. Thus BMW has applied the Night vision system in its vehicles to avoid accidents which can cause the deaths. In the paper, the performance of night vision camera (NVC) is evaluated. The night vision camera is produced by Autoliv for BMW. The paper results not only depended knowledge on performing NVC, but also the understanding the complex product that involves knowledge about engineering involved in it. An Automotive night vision system is system to increase the vehicle driver’s perception and seeing distance in darkness or poor weather beyond the reach of vehicles head light. They are currently offered as optional equipment on certain premium vehicles the camera is connected to the front grill of automotive. It senses the images in the form of electronic signal and then sends it via cable to the LCD screen which helps the driver for his convenience.13
Traffic accidents are the major causes of accidental death of pedestrians in the country. we intend to develop a visual system which detects pedestrians at night to reduce the risk of driving. Infrared imaging is more desirable in detecting human individual under dark conditions. 14

Fig 1.1: road view in camera
1.2Fog
A thick cloud of tiny water droplet suspended in the air at or near the earth surface which obscure or restrict visibility (to a greater extent than mist strictly, reducing visibility to below 300 meter.

1.2.1Fog classification
Fog is a visible collective of minute water droplets suspended in the air at or near the surface of the earth. When air is almost flooded with water vapor, this means that the relative humidity is close to 100%, and that fog can form in the existence of a sufficient number of reduction nucleus, which can be smoke or dust particle. There are different types of fog. Advection fog is formed through the mixing of two air sufficient with different temperatures and humidity. Another form is radiative fog. This is formed in a process of radiative cooling of the air at temperatures close to the dew peak. Some fogbanks are denser than others because the water droplets have grown bigger through increase. In fog conditions droplets can take up more water and grow greatly in size. The question whether scattering is less in the IR waveband compare to the visible range depends on the size distribution of the droplets. There are different ways to classify fog. An often-used classification is the one used by the International Civil Aviation Organization (ICAO). According to this system, fog can be classified in 4 categories.

visual range 1220 meters
visual range 610 meters
visual range 305 meters
visual range 92 meters.

1.3Low visibility weather condition
Due to fog and heavy rain, visibility space is reduced which results in increased speed clash that enhance the risks of crash. In US every year, more than 38,700 vehicle crashes occur due to fog and around 600 people are killed and more than 16,300 people are injured in such crashes every year 3.

According to the report of Federal Highway Administration, from 2002 to 2012, around 1.3 million vehicle crashes every year due to weather conditions within the U.S. Focusing on fog related accidents only, the annual average is 31,385 crashes, 511 deaths and 11, 812 people were injured in over 500 road accidents in U.S. 4.

As analyzed by Booz Allen Hamilton and based on NHTSA data, from 2005 to 2014, around 28,533 crashes occurred due to fog, in which, 10,448 persons were injured and 495 persons were
Killed 5.

1.4Problem of Statement
People are facing problems in everywhere to heavy fog and low visibility level.

Another problem is due to fog lots of accidents occur in winter.
1.5ObjectiveEnable to see the road in fog or smog.

To reduce the accidents.
1.6Scope of Project
In todays time, fog on roads are definitely dangerous as they block visibility for driver and the drivers coming your way, Fog is formed at the surface of the earth, which is made of irrelevant water droplets suspended in air. The bigger problem with fog is that it will reduce visibility for up to ¼ km depending on the weather conditions, especially in the winter season. On average you are more possible accident when you’re driving in fog compare to any other weather condition with much worse injuries caused to the driver and passengers.
To decrease accidents in a foggy weather, we have created a device that can positively decrease the chances of having an accident on road. The device can fully recognize vehicles coming its way and inform the driver by screen. More importantly the device can be bought online open market for an economical price.
The device will clearly recognize any cars. Even in the worst weather the device is able to record the view up ahead, stored in SD card.

1.7Project expectations
Superior fog and smoke resistance performance
More visibility
Reduce accident ratio

1.8Methodology
The proposed approach for the escorting project is presented as follows.

In this project we use raspberry pi to connect all devices.

Camera connects with raspberry pi via ribbon.

LCD is also connecting with raspberry pi Its use as an output device. LCD gives us the display and gives us the camera out video.

Camera fixed on the front grill or front glass.

IR lights are connecting with fog lights connection. We can fixed it on car headlights. When we on the fog lights the IR lights is also on. IR LEDs allow for cheap, efficient production of infrared light, which is electromagnetic radiation in the 700 nm to 1mm range.

IR camera catch the electromagnetic radiation and show the way clearly.

With the help of LCD we see the way view in screen.

Similarly, we can avoid some accidents.

1.9LITERATURE REVIEWLiterature review describes some overview of fog, visibility in fog, anti fog, thermal image, night vision. Many researchers have done several studies regarding these issues. In fact, this issue will be discussed in detail in the following sub topics.

1.9.1Literature survey
This paper describes the development and validation of an automatic defogging system control. This system consists of an auto defog sensor, an independent actuated defrost door flap toward windshield glass and a control head. The sensor signal is calibrated within 2%RH tolerance according to the windshield glass temperature. A fog probability (FP) value is suggested to indicate the likelihood of fogging for more sophisticated actions. Anti-fog control strategies are established on some practical requirements to be applied in actual vehicles.6
Modern vehicles are equipped with many cameras and their use in many practical applications is extensive. Detecting the presence of fog from images of a camera mounted in vehicles is a very challenging task with the potential to be used in many practical applications. Approaches introduced until now analyze properties of local objects in the image like lane markings, traffic signs, back lights of vehicles in front or head lights of approaching vehicles. By contrast to all these related works we propose to use image descriptors and a classification procedure in order to distinguish images with fog present from those free of fog. These image descriptors are global and describe the entire image using Gabor filters at different frequencies, scales and orientations. Our experiments demonstrated height potential of the proposed method for fog detection on daytime images.7
In this paper, a rescue methodology is proposed using a Hexarotor UAV. The aerial vehicle is used for scanning the roads in foggy weathers by using thermal sensing camera fixed on it. The drone will escort the police cars and/or car-ambulances by scanning the road ahead of them, and navigating them to reach their destinations safely and quickly despite the poor visibility caused by the fog. The main purpose of this work is to reduce the number of accident fatalities caused in foggy weather days by helping the rescue services to arrive quickly to the accident location. The project is implemented and flight tests are conducted and presented in this paper.8