Authors: Sangeeta Kurundkar , Atharv Balaji Mali, Gitesh Prakash Mane, Shubham Shivaji Mali, Pratik Masani
Certificate: View Certificate
Driving in low-lighting conditions can raise several challenges that may affect your safety at night. Due to darkness, low visibility is the most frequent issue that drivers have at night. It will be difficult to see obstacles, pedestrians and vehicles on the road and another important problem is glare of Oncoming headlights from high intensity beams of xenon or LED headlights of the front facing vehicles. This will lead to temporary blindness for the drivers. In this situation driving the vehicle is a challenging task. It will be difficult to drive with the traditional headlights in such conditions. It poses a serious threat, and many accidents are caused by temporary blindness. According to the Indian statistics, more than 60% of accidents occur during night time and the main reasons behind those accidents is headlights problems. The abrupt brightness experienced by the travellers is known as the Troxler Effect. However, there is an option in every vehicle weather to keep the headlight either high or low when the vehicle is coming from the front side and this is called as upper and dipper system. Some of the drivers do follow this system as the car approaches them at night but a lot of them do not. Due to which it led to the problem of lack of visibility on the road due to constant glare of the headlights. Heavy vehicle’s (like trucks and buses) have extremely powerful headlights which produce very high intensity lights that in turn result in fatal accidents. Truck and bus drivers will ignore to reduce the headlight intensity when small vehicles are approaching them. As we analyse the current highway situation, most of the goods and passenger transportation occur during night. In lots of time These vehicles jeopardise the safety of other people. There is no such system available which can automatically high and low beam those headlights of heavy vehicles and even high beams of small vehicles. To resolve this problem, The System should be developed so that when a car or bike approaches another vehicle then there should be automatic change in the upper and dipper mode of the lights and reduce the light intensity. So that accidents due to headlights can be reduced.
Car headlight design has changed over the years, moving from an electronic component of the car to the core of its design and overall functionality. The basic functionality of traditional headlights is to Illuminate the road with constant light as high brightness of the light. Even though flashy headlights typically only operate in the low-beam and high-beam modes. Rather than changing Headlight settings automatically. Intelligent headlights have been developed that emit different intensity’s light according to changes in the road ahead and nearby . Auto adaptive headlights (ADB) are another name for smart headlights. The ADB System makes use of a sensor camera and unique headlight designs that modify the light's strength and direction. ADB System makes use of a sensor camera and unique headlight designs that alter the light's brightness and direction. ADB System uses a sensor camera and special Headlight designs that change the brightness and direction of the light. This project smart headlight is developed for providing a better solution for traditional headlights . According to the report of central Transport and road ministry of India, In the year 2021 total 1,66,073 accidents occurred at the night time . To reduce number of accidents at night. This project smart headlight is developed for providing a better solution for traditional headlights. The outline of this paper is to improve headlights of the vehicles.
By dynamically altering the brightness or intensity of the vehicle's headlights based on numerous criteria and driving situations, an automatic headlight dimmer system on a car aims to increase road safety, improve driver comfort, and maximise energy efficiency.
The primary goals include:
II. LITERATURE REVIEW
Temporary blindness caused by increased illumination intensity is one of the most major problems for night time transport. While increased headlight intensity improves eye acuity, it has the opposite effect on oncoming vehicles. This issue is exacerbated when both drivers use a greater beam intensity level. Additionally, accidents are more severe at night because of faster speeds brought on by less traffic . The demonstration suggested smart headlights, which will automatically alter their intensity when two cars are close to one another in order to prevent accidents caused by momentary blindness. Compared to 2011, there was a 3.3% rise in traffic accidents in 2012.
The National Highway Traffic Safety Administration provided this image. It must be automated since many people disregard the rules governing dimmer headlight beams. Even though the number of vehicles is much smaller than during the day, nighttime accidents nevertheless account for about 33% of all accidents and a larger percentage of fatalities. According to a survey conducted by academics, the potential danger of traffic accidents is doubled when compared to daytime . The Troxler effect occurs in the medical field when intense light falls on the eyes of a motorist, causing blindness of temporary type. It can be also called as ‘fading effect’. Study says when light from a source of near about 10,000 lumens falls on human eyes the glare occurs. This glare is caused by overexposure and cones within our eyes. As well as image remains in eyes of human even if source of glare is removed this is called as Troxler effect .
Manual switching is the current way for dimming headlights. In the current method, we must manually regulate the switch from high to low beam. It will be always challenging. This concept is designed to eliminate manual complexion while driving and to avoid accidents. The primary components in this case are an LDR sensor, a relay, and an Atmega328. These components are the system's focal point . One of the research articles by G. R. Poornima, V. Harish focuses on the development of a smart energy management system for vehicle headlights. The primary objective of the research was to design and implement a system that automates vehicle headlights while efficiently managing energy consumption . Another study done by S. Ucar, B. Turan, S. C. Ergen addresses possible uses for VLC with dimming support in traffic and intelligent transportation systems . One of the key reasons for the smart headlight dimmer was in order to prevent road accidents and to avoid Troxler’s effect at night going further S. Saha, M. A. Mondal and Z. Rehena did research on this and the main goal of their research was to develop and put into use a smart headlight intensity management system for automobiles to counteract Troxler's impacts when driving at night. Their research mainly focused on Troxler’s effects mitigation, Intensity control and Driver comfort . There are also a lot of IoT-based automatic headlight dimmer systems and for summarised evaluation these devices research was done by K. Gandhi, K.S. Aulakh where their paper focuses on aspects related to IoT-based automatic headlight dimmer systems such as IoT integration. Sensors and data collection and different evaluation criteria such as energy efficiency, safety, compliance with regulations etc .
The primary objective of smart headlights is to automatically adjust Headlight’s intensity when one vehicle approaches another. This functionality is achieved through a combination of image processing techniques and microcontroller interfacing, specifically using a webcam, servo motors, Raspberry Pi, and Arduino, along with small LEDs serving as the headlight’s functionality. The pivotal aspect of this project involves identifying vehicles approaching from the front using the webcam and performing real-time image processing to track these vehicles.
For the implementation of image processing, Python is selected as the programming language. Python is fevered due to its extensive libraries and user-friendly syntax, making it an ideal choice for the task. When it comes to the algorithms for object detection in Python, several options are available, including Haar Cascade, YOLO (You Only Look Once), and object detection using TensorFlow.
In this project, the Haar Cascade algorithm is adopted as the primary method for vehicle detection, because it is a machine learning method for object detection in Python. Its strength lies in its ability to find good products by recognizing certain patterns, and face recognition etc. It has seen applications in many fields such as vehicles and traffic sings detection also.
VI. FUTURE SCOPE
As in the above paper method followed for image processing is nothing but Haar cascade based as Haar cascade determines only one type of object at a time more advanced algorithms like yolo and TensorFlow can be used for the image processing. As well as more accurate distance measurement can also be done in future. As if multiple cars are at the same distance from the camera, the system may not be able to detect all of them, as it is designed to detect only one object at a time so more advanced algorithms can be used. As in typical upper dipper system 2 lights are used for achieving high and low beam of light and discussed algorithm only uses one and ability of PWM signal of Arduino for lowering the light ,2 lights can be use in future with the help of relays. More accurate dipping of the servo motors can also be done in future. As raspberry pi B3 model is used as a primary microcontroller in the work it is little bit slow than today's laptops and computers so this microcontroller can be replaced by the more powerful microcontrollers. As well as Arduino can also be replaced by the advance microcontrollers which has more speed and processing power than Arduino. As to operate this system microcontrollers which has more speed and processing power than Arduino. As to operate this system raspberry pi must be connected to the WIFI of home router or the mobile sometimes it needs more speed of the internet for the processing so this system can also be replaced by wired system or some other systems.
The above demonstration shows the use of OpenCV to detect the approaching vehicle in the night time thus resulting in the activation of the servo motors and also the reducing the intensity of lights this demonstration doesn’t depend on sensors such as LDR that are commonly used to for detecting light intensity but a camera module to detect the approaching car thus making it more reliable solution for fighting the temporary state of blindness called the Troxler effect, LDR sensors are unreliable because the variation in resistance value has a delay, which differs depending on whether it travels from dark to illuminated or illuminated to dark. This restricts their applicability in applications where the light signal varies frequently.
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Copyright © 2023 Sangeeta Kurundkar , Atharv Balaji Mali, Gitesh Prakash Mane, Shubham Shivaji Mali, Pratik Masani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.