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Advanced Driver Assistance System

Research Seminar Report

Chair of Computer Engineering

Dept. of Computer science

TU Chemnitz

Submitted by: Brahmaiah Takkellapati

Immatriculation Number: 366304 Address: Stadler straße3, 09126, Chemnitz Date of Birth: 09.04.1992 Supervising Tutor: Prof.Dr. W. Hardt

Table of Contents

Abstract………………………………………………………………………………........1 1 Introduction ……………………………………………….……………………...….…1

1.1 Why ADAS? ……………………………………………………………………….……….……......1

1.2 Why’s ADAS Interesting…………………………………………………………………...…..2

1.3 ADAS Demand-System level…………………………………………………………...…....2

1.4 Degree of Automation……………………………………………………………………….....3

2 Technology Overview……………………………………………………………......3

2.1 Lane Departure Warning System…………………………………………………………..4

2.2 Intelligent Headlamp Control…………………………………………………………….....5

2.3 Parking Assistance System…………………………………………………………………....6

2.4 Drowsiness Detection System ………………………………………………………….......7

3 Adaptive Cruise Control………………………………………………………….....8

3.1 Introduction………………………………………………………………………………..8

3.2 Working Principle and Operation ………………………………………….......9

3.3 Block diagram of ACC………………………………………………………………...10

3.4 Sensors & Actuators…………………………………………………………………..10

3.5 Algorithms…………………………………………………………………………………12

4 Blind Spot Detection System…………………………………………………....15

4.1 Introduction……………………………………………………………………………………….15

4.2 Sensors & Actuators…………………………………………………………………………...15

4.3 Algorithms……………………………………………………………………………………….…16

5 ADAS- Current Development ………………………………………………..….20

6 Conclusion…………………………………………………………………………….… 20

Abbreviations…………………………………………………………………………….….21

Bibliography………………………………………………………………………………....21

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Abstract

Advanced Driver Assistance System (ADAS) is the foremost runner of innovations to make driving experience easier and safer on our more cram-full roads. The main focus of this paper is to introduce the ADAS, Overviewing the few technologies in it and explaining in detail about two systems and Current Development.

CHAPTER 1

Introduction ADAS (Advanced Driver Assistance System) is one of the fastest growing segments in the automotive field. ADAS enables safe and relaxed driving. Based on the intelligent sensor technology the driver assistance system constantly monitors the vehicles surrounding as well as the driving situation at an early stage. In critical driving situation, these systems will give warn and actively support to the driver, if necessarily, intervene automatically in an effort to avoid a collision or mitigate the consequences of the accident.

Figure 1.1: http://www.autobild.de/bilder/technik-mercedes-e-klasse-807290.html#bild1

1.1 Why ADAS?

The number of people who die in the road accident each year in the Europe continent alone adds up to the population of small city i.e., 5, 04,000 deaths in 2002 approximately. European Government wants to see further improvement on road safety to reduce the accidents. European commission set a target of halving the number of road fatalities by 2010, which can be seen in Figure 1.1.1. This has been achieved by means of implementing the ADAS.

Figure 1.1.1: Number of fatalities Vs. Time

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1.2 Why ADAS Interesting?

Government wants to reduce the number of road fatalities, thereby increasing the safety and comfort.

Each and every consumer requires safety and comfort in order to have better life.

Automaker needs the new features. According to the above facts, we can say that ADAS is interesting in day by day life which can be illustrated by the Figure 1.2.1. The safety technologies have been improved in every year. By introducing these technologies, the numbers of fatalities are reduced.

Figure 1.2.1: ADAS Technologies vs. Number of Traffic Fatalities

1.3 ADAS Demand-System level?

The usage of technologies in each year can be illustrated by Figure 1.3.1. In 2010, the ADAS systems have been used below 5 by OEMS, but in 2015 the ADAS systems has been used above 15. This tells us that, in each year the usage of ADAS technologies is increasing gradually.

Figure 1.3.1: http://on-demand.gputechconf.com/gtc/2013/presentations/S3413-Advanced-Driver-Assistance-Systems-ADAS.pdf

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1.4 Degree of Automation

There are 5 levels of Automation that can be illustrated by the Figure 1.4.1. 1. No automation Level: Human driver executes the manual driving task. 2. Partial Automation: The System takes over longitudinal and lateral control, the driver will permanently monitor the system and prepared to take over control at any time. 3. High Automation: The system takes the longitudinal and lateral control: the driver must no longer permanently monitor the system. In case of takeover to control the request, the driver must take over. 4. Full Automation: The system takes over longitudinal, control fully and forever. In case of take over the request that is not followed, the system will return to the minimal risk condition by itself. 5. Autonomous Driving/Driverless: System can tackle all driving situations. No driver necessary from start to destination.

Figure 1.4.1: http://www.infineon.com/dgdl/2015-09-28+ATV+Analyst+Presentation.pdf?fileId=5546d4614fb7fdd10150046b31b2022b

CHAPTER 2

Technology Overview

Today, the usage of advanced driver assistance systems is fast increasing importance as these systems are expected to improve road safety, increase road capacity and to reduce the environmental impacts of traffic. The development of new technologies in ADAS such as Sensors (Radar, LIDAR, ultrasonic and cameras), transmitter, communications, computers which allows the vehicle to monitor the surrounding in all directions and of evolving and improving sensor fusion algorithms ensures that vehicle, driver's, passenger’s, and wayfarer safety based on factors such as traffic, weather, dangerous conditions, etc. [15] Modern ADAS system act in real time via Warning system to the driver or by actuation of the control systems directly and are precursors to the autonomous vehicle of the future. In ADAS there are several challenges to design, implement, deploy and operate the ADAS systems. The system is expected to gather accurate input, process the data as fast as possible, exactly predict context, and it will react in real time and it is required to be robust, reliable, and have low error rates. [15]

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Figure 2.1: Technology overview of ADAS

2.1 Lane Departure Warning System

System that provides the driver with visual or audio warnings, and protect him from unintended lanes changes. The turn Indicator is active i.e., when the driver changes the lane intentionally then there will not be any warning to the driver.

Figure2.1.1:http://www.continentalautomotive.com/www/automotive_de_en/themes/commercial_vehicles/chassis_safety/adas/ldw_lks_en.html

Sensors:

Lane Departure Warning system uses cameras, mounted high up the Windshield that continuously tracks the visible lanes. In the system, camera and image processing are used to detect the painted lane marking up to 50m ahead of the vehicle. Vehicles heading and the lateral position in the lane is determined by the system in order to provide the proximity.

Figure 2.1.2: http://www.nissan-global.com/EN/TECHNOLOGY/OVERVIEW/ldw.html

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Actuators:

After the system detects the unintended lane changes the driver gets alerted by the audible/visible alarms and with the small Vibrations of the Steering wheel or seat.

2.2 Intelligent Headlamp Control

Optimal night Vision is extremely important particularly at night time when the risk of accident is twice greater than the day. Intelligent Headlamp Control is the system which allows a better vision at night. The system takes oncoming traffic and preceding vehicles into consideration, in order to ensure that the headlamps are set to provide excellent lighting in any situation and making certain high beams which do not blind other road users. The System uses the camera and a microprocessor to continuously adjust the Illuminations range of the vehicle headlamps to the traffic situation. [25]

Figure2.2.1:http://www.continentalautomotive.com/www/automotive_de_en/themes/commercial_vehicles/chassis_safety/adas/ihc_en.html

Sensors:

Light beam can be control by the camera which is fitted with the inside mirror. The imaging sensor picks up the oncoming vehicle’s headlamps, front vehicle’s tails lamps and the street lightening. IHC not only senses if they are light rays which mainly comes from headlamp and tail lamps, but it also calculates the height above the ground and also the velocity, angle at which they are approaching or moving away from one’s own vehicle. The camera also senses the intensity of the light. IHC calculates whether the vehicle matches the parameters and changes the headlamp beam illumination range.

Figure 2.2.2: http://www.conti-online.com/www/industrial_sensors_de_de/themes/mfc_2_de.html

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Actuators:

Low and High beam of Vehicles Headlamp can be switched automatically in order to avoid dazzling other road users.

2.3 Parking Assistance System

Now a days parking can be frustrating and stressful. Parking has never been an easier task, that let you park in any suitable space in just a moment. So to avoid that PAS is the system that detects the available parking spaces of suitable size (lengthwise, cross-wise, and diagonal). PAS automatically parks the vehicle in the parking space, following driver approval, using independent braking and steering.

Figure 2.3.1: http://www.at.ford.com/news/publications/Publications/APA.pdf

When a driver wants to park, he or she can switch the PAS ON in order to start the parking process. The ultrasonic sensors are used to detect the proper parking space and the system calculates the best possible way to move in to parking spot and also necessary steering action can be determined in milliseconds. Driver can take control of the steering wheel at any time.

Sensors:

PAS uses the ultrasonic sensors, mounted on the sides of the bumper to monitor the both side of the streets when the vehicle is traveling with speed less than 35km/h. Ultrasonic sensor works according to the sonic altimeter principle. The sensor transmits the short ultrasonic pulses which are reflected by the objects/barriers. These reflected echo pulses are registered by the sensor and are evaluated by the central control unit.

Figure2.3.2:http://www.bosch-mobilitysolutions.cz/media/db_application/downloads/pdf/comfort_1/en_5/

einparkenleichtgemachtparkassistenzsystemevonbosch.pdf

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Actuators:

Driver is alerted by audible/visible Alarms when the vehicle gets too closer to other objects in the parking space.

2.4 Drowsiness Detection System

Driver drowsiness has been one of the major causes for vehicle accidents. In Recent years, annually 1,200 deaths and 76,000 injuries can be attributed to drowsiness related crashes. The development of technologies for detecting or preventing drowsiness is a major challenge in the field of accident avoidance systems. System that assists and warns the driver, in order to prevent them falls asleep momentarily. Driver drowsiness can be determined by the following measure:

Vehicle based measure

Behavioral measure

Physiological measure Vehicle based measure Factors which come under vehicle based measure are lane position of the car; steering wheel movement, acceleration pedal pressure etc. are constantly monitored. The driver will be notified, based on changes in the above factors keeping reference point as threshold. [13] Behavioral measure Factors which are considered in behavioral measure are yawing, eye closure, Eye blinking, head position etc. are constantly monitored. If any of these drowsiness symptoms are detected, the driver gets alerted. [13] Physiological measure The correlation between physiological measures are ECG (Electrocardiogram), EEG (Electro encephalogram), EOG (Electro Oculography) etc. are constantly observed. Driver gets alerted if there are any changes in above factors that go beyond the set point or reference point. [13]

Figure 2.4.1: https://www.rti.com/whitepapers/Right_Middleware_for_IIoT.pdf

Sensors:

1. Steering angle Sensor The steering angle sensor which is mounted on the steering column is used to detect the steering wheel movement and also measures the driver’s steering behavior. Speed of the vehicle, desired braking pressure, and acceleration pedal position and driver’s intention can be calculated by steering wheel movements. It is widely used for detecting the level of drowsiness.

2. Position Sensor By mounting array of Position sensors in headliner and seat of the vehicle, sensor is used to detect the head movements and position of the driver. When the head position goes beyond certain angle, the driver is alerted by an alarm.

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3. External Camera Standard deviation of lane position is another measure through which the level of drowsiness can be evaluated. The position of the lane can be tracked using external cameras.

4. Camera to detect eye movement Cameras which are mounted on steering wheel are used to detect the eye movements by using IR LED.

Actuators:

If the system detects the drowsiness of the driver, then it will provide an adequate warning to the driver, with different levels of warnings according to the estimated driver’s fatigue state and also to the estimated level of traffic risk. The DDS uses the different modalities-acoustic, visual and haptic output signal to warn the driver against the drowsiness.

Figure 2.4.2: http://nissannews.com/en-US/nissan/usa/releases/video-report-nissan-driver-attention-alert-helps-combat-drowsy- driving-with-innovative-system

CHAPTER 3 Adaptive Cruise Control

3.1 Introduction

Adaptive Cruise Control (ACC) is one of the ADAS systems, introduced by General Motors in 1990 that is similar to conventional cruise control. ACC assists the driver to keep a safe distance from preceding vehicle by controlling the engine, throttle and brake.

Figure 3.1.1: Prabs, (2010), Adaptive Cruise Control system

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As shown in the above Figure 3.1.1. ACC uses a forward-looking radar sensor, which is installed behind the front grill of the vehicle. The Adaptive cruise control equipped vehicle has the ability to detect the speed and distance of the predecessor vehicle or any other obstacle ahead. Adaptive cruise control automatically adjusts the car speed initially set by the driver to maintain a safe following distance with the preceding vehicle. Thus by using the Adaptive cruise control, the driver has safety with the preceding vehicle.

3.2 Working Principle and Operation

Working Principle of ACC:

The radar is main component in adaptive cruise control. It is used to detect the speed and distance form vehicle ahead of it. The distance can be measured by time taken to transmit and receive of the radar signal is key principle. The speed can be measured by using the Doppler Effect principle.

The Doppler Effect principle can be explained by the Figure 3.2.1. When the source of the waves moves either towards or away from the observer/listener, then there will be change in frequency and wavelength. When the source of the waves moves towards to the listener, then there will be a high frequency and small wavelength. At the same time, when the source of the waves moves away from the listener, then there will be a small frequency and high wavelength.

Figure 3.2.1: http://science.howstuffworks.com/science-vs-myth/everyday-myths/doppler-effect2.htm

Working Operation of ACC:

ACC is very easy to operate. Firstly, the driver has to select the desired speed and the distance that has to be maintained from the vehicle ahead. This distance can be set at several levels adapting to the driving situation and individual driving styles. After setting, ACC will get activated. A long-range radar sensor in ACC, will monitors the driving situations ahead of the vehicle. The sensor transmits the radar waves that are reflected by the object in front of the vehicles. Based on the data, ACC can detect the preceding vehicle and can calculate the distance and relative speed of the vehicle ahead. When the system detects that it is approaching a vehicle, it interacts with engine control or electronic stability program and ensure that the safe distance is maintained. Once the road ahead is clear, ACC automatically accelerates the vehicle to the preset or desired speed.

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Figure 3.2.2: https://www.embedded.rwth-aachen.de/lib/exe/fetch.php?media=lehre:sose05:2_20050426_reqsbasics.pdf

3.3 Block Diagram

Data from both the radar and stereo camera are combined in to the fusion processor. Radar is used to detect the forward looking manner objects but it cannot detect the edged vehicles and the stereo camera uses to detect the edged objects. So in fusion processor, these two input signals are combined and it is transferred to the headway control unit. Based on the data, headway control unit will calculate the relative speed and distance from the preceding vehicle. The algorithm in headway control unit will ensure that, which actions should take over. If the system detects that it is approaching any obstacle/vehicle, it will respond through throttle, brake system, or dash board display.

Figure 3.3.1: Greg Marsden et al. (2000), Towards an understanding of adaptive cruise control

3.4 Sensors and Actuators

Sensors:

Adaptive cruise control uses the various kinds of sensors that are mounted behind the grill of the vehicle to assists the driver in providing a safe following distance from preceding vehicle. Sensors are used to detect velocity, angular position and distance of a preceding vehicle.

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Figure 3.4.1: Different types of Sensor used in ACC

1. Radar Radar is acronym for radio detection and ranging. The radar is used to detect and determine the relative speed and distance from object/ vehicle. In the current ADAS, the most frequently used radar is the Pulse Doppler.

Figure 3.4.2: http://www.porscheownersmanuals.com/2011-cayenne-owners-manual/4/160/ACC

The pulse Doppler is a radar system that functions by sending short pulses of radio energy and simultaneously listens to the echo from objects using the same antenna. The time difference between transmission and reception of the radar signal is key principle for measuring the distance. Frequency of the reflected beam can be measured by using Doppler Effect principle that means speed can be measured by using the frequency of the reflected beams. Most commonly used radar in ACC systems are 77GHz based Radar sensors. The major advantage of the Pulse Doppler is to separate the moving objects from clutter. The clutter refers to actual radio frequency (RF) echoes returned from targets. It also works in poor weather conditions. 2. LIDAR LIDAR is light detection and ranging or laser imaging detection and ranging. LIDAR is a technology that calculates the distance to an object using laser pulses. The range to an object is determining by measuring the time delay between the transmission of pulses and detection of reflected signal. Drawbacks: Even through its cheap compare to radar, it does not work in poor weather condition. Dirt builds up in the laser beams blocks up on the sensor lenses. 3. Fusion Sensor Radar and stereo camera are combined in to the fusion sensor. Radar is used to detect the forward looking manner objects but it cannot detect the edged vehicles. So to detect the objects in edged manner fusion sensor combines the radar with stereo camera.

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Figure 3.4.3: http://studymafia.org/wp-content/uploads/2015/03/mechADAPTIVE-CRUISE-CONTROL-report.pdf

Actuators:

If the system detects that it is approaching any obstacle/vehicle, it will respond through throttle, brake system, or dash board display.

Figure 3.4.4: Hwisoo Eom and Sang Hun Lee, (12 June 2015), Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles

3.5 Algorithms:

Speed Algorithm

Adaptive speed control algorithm is used to calculate the desired speed. Here Constant rotation value (CR) of the wheel is fixed for the constant speed of the car. Current speed of the car (ROT) is to measured and compared with constant rotation value (CR). Based on the comparison result if the current speed is greater that the desired speed (i.e.) ROT>CR then the vehicle is slowed down by reducing the PWM to the constant duty value (i.e.) 65 to make the vehicle to move in the desired speed. If the speed of the vehicle decreases from the desired speed (i.e.) ROT<CR then we increment ‘Ks’ for every iteration which increases the speed by increasing the PWM duty gradually according to equation 1 until the vehicle reaches the desired speed. Equation 1 shows how the PWM value for the DC drive is assigned dynamically and they are tabulated in Table 3.5.1. [5] PWM_duty = Const_duty+ (Ks*(CR - ROT)) …………………………………………….. (1) [5]

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Figure 3.5.1: D.Sivaraj, K.R.Radhakrishnan,(2011 ), Design of Automatic Steering Control and Adaptive Cruise Control of Smart Car.

According to the Table 3.5.1 the first row values are the speed factor (Ks) value which is increased for every iteration. The first column value is the difference of constant rotation value (CR) with the Current Speed (ROT). When this difference is zero, vehicle moves in a desired speed hence the row values are 65 which is the PWM duty value for DC motor. When the difference is more, the PWM duty value is increased for each iteration to attain the desired speed. Different possible PWM duty values with respect to the speed factor and speed difference is shown in Table 3.5.1. Thus the speed of the car is

dynamically varied to maintain the desired speed independent of the road conditions. [5]

Table 3.5.1: D.Sivaraj, K.R.Radhakrishnan,(2011 ), Design of Automatic Steering Control and Adaptive Cruise Control of Smart Car.

PID based Adaptive cruise control Algorithm:

The Proposed method is used to determine the distance and speed by using the PID Controller. Following steps explains how to determine the distance and speed of the preceding vehicle:

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Start of the ACC system Step1: Starting the Engine. Step2: User will run the vehicle manually by using the acceleration and brake pedal. Step3: User will check if the ACC is turned on or not. Step4: If ACC is turned off then it directly goes to step2. Step5: On the other hand, If the ACC is turned ON then it checks whether any object detection is get fails or not. Step6: Then if object detection gets fail then we have to bypass the method to PID Controller as seen in Figure 3.5.2. Step7: After that it again checks if any object detection fails or not. Step8: If there was no object detected then the host vehicle speed is equal to the set speed. Step9: After, if the object gets detected, we calculate the distance by measuring the time difference techniques. Step10: Getting the vehicle speed.

Step11: we need to fix up the vehicle speed is equal to the lead vehicle speed. Step12: The ACC system adjusts the acceleration and brake pedals in order to maintain the safe speed is required. Step13: The ACC gets deactivated, if user manually presses the acceleration or brake pedals.

Step14: User will be shown on display that ACC is deactivated. Step15: Process will repeat the continuously. [4]

Figure 3.5.2: M. Ben Swarup, M. Srinivasa Rao, (June 2015), Software Safety Simulation and Failure Analysis of Adaptive Cruise Control

System

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CHAPTER 4 Blind Spot Detection System

4.1 Introduction

Driving a vehicle in traffic conditions is very risky. The major risk could occur if the driver watches the oncoming road hazards and at the same time looking backwards. It is important for the driver to look on both sideways and backwards, before he/she safely changes the lanes. A problem that often occurs by the driver is the blind spot areas. Blind spot are the areas around a vehicle where the driver cannot detect an object by their mirrors and must turn their heads from the road to look objects. These areas are usually over the right and left shoulders of the driver and are out of range of the side view and rear view mirrors. [3] Blind spot detection system is a device that monitors the blind spot detection areas when the driving vehicle is entered in to the modern traffic condition. Then it alerts the driver of an object through illuminating LEDs on or near each side-view mirror. [3]

Figure 4.1.1: Mohd Ridhuan Bin Selamat, (16 June 2014), A BLIND SPOT DETECTION SYSTEM BASED ON ULTRASONIC SENSING

4.2 Sensors and Actuators

Sensors:

Blind spot detection system uses the different types of sensors, to detect the vehicle in blind spot regions. 1. Radar BSDS uses the Radar as the sensor, which is usually mounted in left rear position and right rear position of the vehicle. The sensor transmits and receives radio waves to and from the vehicle’s left and right blind spot regions. The system processes these radar signals and provides visual and audible information to the driver. 2. Vision camera Computer vision based BSDS uses digital camera imaging technology to sense the presence of vehicle in blind spot regions. Cameras are mounted on or near the outside rear-view mirror housing on both sides of the vehicle, which provides the views of the blind spot regions to the system. The Systems processes these images and provide visual and audible information to the driver. 3. Ultrasonic Sensor

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Ultrasonic sensor based BSDS uses the Ultrasonic sensor. Ultrasonic signals are like audible sound waves, expect the frequencies are much higher. The ultrasonic pulses transmitted in the shape of the cone and are reflected from a target back to the transducer can be illustrated from Figure 4.2.1. An output signal is produced to perform some kinds of indicating or control function. Echoes can be interpreted by providing a minimum distance from the sensor that is required to provide a time delay. [3]

Figure 4.2.1: Mohd Ridhuan Bin Selamat, (16 June 2014), A BLIND SPOT DETECTION SYSTEM BASED ON ULTRASONIC SENSING

Actuators:

Blind spot detection system alerts the driver if there are any upcoming potential hazards in blind spot zone. Depends upon the severity of the hazards, system alerts the driver through the flashing light display which is mounted on the side view mirror housing, steering wheel vibrations and audible/visible alarm.

Figure 4.2.2: Mohd Ridhuan Bin Selamat, (16 June 2014), A BLIND SPOT DETECTION SYSTEM BASED ON ULTRASONIC SENSING

4.3 Algorithms

A Blind Spot Detection System based on Ultrasonic Sensor:

Blind spot detection system consisting of five components. In which, four of them are the sensors and fifth one is the microcontroller that can be seen in the Figure 4.3.1. The nodes are connected in the sequel that can be attached to the car body. The microcontroller is important to combine the operation of the all nodes and to processes the data, which comes from nodes. Then it will give alerts to the driver. The sensors cover the both side of vehicle front corners. When the driver neglects the blind spot areas, the two front corners are found to produce the highest accident rates. As the Figure 4.3.1 represents the correlation among the system components. All five modules are arranged around

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the same processing unit of a microcontroller and radio transceiver. The four sensors are consist of ultrasonic sensors at the same time the microcontroller connected to three types of indicators such as LED panel, buzzer, and vibrators mounted on the steering wheel. [3]

Figure 4.3.1: Mohd Ridhuan Bin Selamat, (16 June 2014), A BLIND SPOT DETECTION SYSTEM BASED ON ULTRASONIC SENSING

Indicators in various conditions:

According to the Table 4.3.1, if the vehicle is located in the blind spot zone then driver will get alerted by the indicators. If there was no object in the zone1 and zone 2, then all indicators were deactivated at that time and vehicle is considered that it is in safer zone. During the driving, if the objects enters in to the zone 1 then it is considered as middle threatened, then the driver is alerted by LED indicators which are turned on. When the object enters in to the zone 2, then the vehicle is in threatened position which can indicate by LED indicators, buzzer and vibrators. [3]

TABLE 4.3.1: Mohd Ridhuan Bin Selamat, (16 June 2014), A BLIND SPOT DETECTION SYSTEM BASED ON ULTRASONIC SENSING

Flow chart:

Proposed method is used to detect the obstacles in blind spot region of the vehicle by ultrasonic sensor. There are two main parts in hardware development of BSD system, one is Circuitry of wireless

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ultrasonic sensor and other one is circuitry of warning light indicators. Circuitry of Wireless ultrasonic sensor contains four major components, which are Arduino Promini, Ultrasonic sensor, NRF24L01 Transceiver module, and power supply. Circuitry of warning light indicators contains four major components, which are Arduino, NRF module for Receiver, LED, and Buzzer. [3] The circuitry of wireless ultrasonic sensor will detect the obstacles. After that, warning light indicator will respond the signal from the circuitry of wireless ultrasonic sensor and activated the LED or buzzer inside the warning light indicator. [3]

Figure 4.3.2: Flow chart of ultrasonic sensor based BSD system

The ultrasonic sensor is used to detect the obstacles which are present in blind spot regions of the vehicle by determining the distance between the obstacles. The input signal from the sensor is given to the microcontroller that’s Arduino Promini which acts as brain of the circuitry. If the distance is less than 2 meters, then NRF transmitter transfers the sensor signal from the circuitry of wireless ultrasonic sensor to the NRF Receiver in the circuitry of warning light indicators. Based on the severity level the processor will activates the LED or buzzer inside the warning light indicator. [3]

A Blind Spot Detection System using cameras:

The Proposed method is used to detect the obstacles in blind spot areas of vehicle by using cameras.

Here the System consisting of 3 units:

Input unit

Processing unit and

Output unit

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The input unit contains the image capture unit and vehicle signals. The processing unit includes of image processing unit and microprocessor, digital signal processor which is used for image processing unit. The output unit consists of the display unit and alert unit. [6]

The Input unit will monitor the receiving image data from CCD or CMOS cameras as well as steering wheel and speed sensor data from vehicles CAN network. Input signals are processed by the processing unit. [6]

Resulting flow of information through the processing unit includes the following steps can be illustrated by Figure 4.3.3

Images will be continuously captured from the CMOS/CCD camera and also cameras are used to define the detected regions.

And then based on the Image entropy estimation it converts the 2-D image in to 1-D distance axis signal information.

The differential value at single time point and at least two adjacent time point of the 1-D signal axis information can be calculated.

Based on the differential value, the system determines the Position of objects and also the approaching status of object.

Finally the driver will get alerted.

Figure 4.3.3: Flow chart of Camera based BSD system

The output unit includes a display showing a view of camera as well as alerting the driver by means of audible/visible alarms.

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CHAPTER 5 ADAS-Current Development

Autonomous Car There are few issues that require to turn a regular car into Autonomous car. The main one is GPS. GPS is actually a virtual part of an autonomous car. But GPS alone is not enough to make a intelligent car. The other one is dynamic condition on road; maps never changes and the reality of the roads includes dynamic like traffic and other objects. So autonomous driving requires a second level of intelligence with the competence to fill the additional particulars in the map. Autonomous car uses an array of technology such radar, camera, laser. [17] Camera’s, are used to make the car’s computer to see what’s around it. Radar allows the vehicle to look up to 100 meters away in dark, snow, rain. Laser, which looks like spinning siren light, constantly scans the world around your car and provide the vehicle with continues three dimensional view of its surrounding. [17] The sophisticated algorithm presents in the car’s computer process all that sensors information. And lastly, autonomous vehicle needs to be equipped to take the GPS and all sensor information and turn in to actions. In future, all cars would be able to talk to each other in a connected vehicle environment. So that the other vehicles would know precisely where the car is going, and where they will turn. So the computer can navigate smoothly and reduce the accidents.

Figure 5.1: http://www.rdtaxsavers.com/articles/Advanced-Driver-Assistance

Conclusion

Fully autonomous car is probably viable in the foreseen future. Nearby vehicle would be in constant communication with each other and act co-operatively. It will probably take decades, but car accidents may eventually become rare.

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Abbreviations

ADAS – Advanced Driver Assistance System

LDWS – Lane Departure Warning System

IHC – Intelligent Headlamp Control

PAS – Parking Assistance System

DDS – Drowsiness Detection System

ACC – Adaptive Cruise Control

BSDS – Blind Spot Detection System

GPS – Global Positioning System

LED – Light Emitting Diode

PWM – Pulse width modulation

PID – Proportional, Integral, Derivative

DC – Direct current

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16 June 2014.

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