Obstacle Detection in Self-Controlled Cars

Abstract

An autonomous car is a vehicle that can guide itself without human command and control. It is also known as a driverless car, self-driving car, unmanned vehicle, or robot car. Autonomous vehicles can perceive their surroundings (obstacles and track) and commute to their destination with the help of a combination of sensors, cameras, and radars. There is a basic need for a system that can detect obstacles and move in a pre-computed path, a system that can detect the obstacles that appear suddenly which may cause accidents. Therefore, the automatic obstacle avoidance vehicle is designed for obstacle detection and collision avoidance. The ultrasonic sensor is tuned to enable the real-time obstacle avoidance system for wheeled robots, allowing the robot to continuously sense its environment, avoid obstacles and move to its target area. The design requires an ultrasonic sensor (hcsr04) to detect the obstacle and determine its distance. This sensor module is placed on the front of the vehicle and mounted on a servo motor rotating in the direction of the sensor. The system includes a motor driving module and four dc wheel motors which are used to move the vehicle forward, reverse, left, right, and stop. The Arduino Uno microcontroller is mainly used to control the vehicle and achieve the desired detection and prevention

Introduction

I. INTRODUCTION

With the development of automation technology, automation begins to develop from simple system control to complex system control and advanced intelligent control, and that too in various fields.

An intelligent car is based on the automobile as the background, including automatic control, sensor technology, computer, machinery, and other disciplines of design.

An intelligent car integrates a complex integrated system, which can realize environment perception, self-planning, and self-decision functions. It can make full use of computers, sensors, information, communication, artificial intelligence, automatic control technology, and high-tech complex technology.

As demand for autonomous projects increases, the use of the sensor increases. The sensor is a complex device that converts physical parameters (e.g. temperature, pressure, humidity, speed, etc.) to a signal that can be electrically measured. They are very important to robots. It offers robot remote access and decisions about the desired environment.

The project is designed to build an obstacle avoidance robotic vehicle using ultrasonic sensors that will move according to the code assigned and will a free space, navigating from any obstacle on its way.

The so-called obstacle avoidance system is made to use the advanced range finding device in front of the autonomous car. When the car faces an obstacle, it can locate and respond to the location sensor and enter the Arduino through the data transmission starting the core processing.

Ultrasonic sensors are known for their reliability and great versatility in the industry. Ultrasonic sensors can be used to solve the most difficult tasks involving object detection or level measurement with millimeter accuracy because the measuring method works reliably in almost all conditions.

In this project, a robotic vehicle that moves in different directions like forward, backward, left, and right are designed and built to avoid the obstacle when it receives the sensor input that the object is detected.

II.  LITERATURE REVIEW

Matthies et al. highlighted the importance of an autonomous navigation scheme for Unmanned Ground Vehicles operating under a complex operational scenario that required obstacle detection. During the detection phase, the relationship between encountered obstacles and the robot’s path was inferred [1].

Darms et al. focused their work on path planning together with one of the main issues that were represented by tracking activity. The role of such topics is fundamental in evaluating a collision-free path for self-driving vehicles. The authors formulated the tracking controller as a multiconstrained model predictive control (PC) problem to follow the planned path for maneuvering to avoid obstacles by evaluating the proper steering angle to avoid collisions [2].

Discant et al. instead, underlined the safety issues regarding obstacle avoidance, being an important feature for any kind of vehicle. A lidar sensor was used to detect the obstacles along the route and to optimize the path automatically by using the information about the vehicle’s position, the location of the obstacle, the operational capabilities of the vehicle, and environmental restrictions [3].

Matthies et al. presented a method for identifying objects in a dynamic environment by using a 3d light detection and ranging sensor, for high-speed object detection [4].

Borenstein & Koren used a fuzzy-based inference system (FIS) for navigation by using sensor information fusion. Such a system is made of two controllers: the first one uses sensors positioned in the front of the vehicle to detect obstacles, while the second controller evaluates the difference between the heading and the target angle [5,6].

Furthermore, Gibbs et al. used an adaptive neuro-fuzzy inference system for navigation purposes by fusing sensor information. Such a system was made of four controllers: two are used for angular velocity regulation for reaching the target position and the other two are used for obstacle avoidance [7,8,9,10].

Rajashekaraiah et al. proposed the MATLAB/Simulink simulation environment as a powerful tool for implementing the item algorithm (probabilistic threat exposure map) to improve the obstacle avoidance capability for moving and stationary obstacles [11].

Simone et al. investigated safety issues for manned vehicles. The authors developed a system capable of evaluating the commands of an operator and, in the case of the detection of obstacles, automatically correcting unsafe operations [12].

Furthermore, Giesbrecht et al. (2017) focused on driving assistance algorithms to reduce low-level tasks for a driver in the presence of cluttered and difficult areas. Such a system shares the burden between the autonomous algorithms and the driver, manages proximity warnings, trajectory control in the case of narrow passages, wall following, etc. [13].

In Mohammadi and khaloozadeh (2016), a nonlinear sub-optimal regulator is proposed for trajectory planning and avoidance of obstacles. The state-dependent Riccati equation (sure) is used to design a sub-optimal nonlinear controller. Such an approach allows one to create an efficient and well-organized method for the control design of a non-linear system [14].

Tee kit et al. used Microsoft robotics developer studio 4 (MRDS) to create autonomous system navigation. The authors implemented an indoor robot navigation system by using multi-sensor fusion, obtaining information by a depth camera, proximity sensors, and an IR marker tracking system. The navigation system implemented this by transforming the data of the three sensors into tendency arrays to fuse them to decide on object-avoiding maneuvers. The algorithm established the appropriate maneuvers according to the short, medium, or long distance from the obstacle to be avoided [15].

IV.  WORKING

1. The car moved along a specific distance; it counts the distance while it is moving on the track.
2. If the sensor can detect any obstacle, then Arduino will give instructions to stop instantly.
3. The Left side and Right-side distance values will be determined by the sensor with the help of a rotating SG90 servo motor.
4. If the left side distance value is more than the right side distance value, then the car turns 900 to the left. Otherwise, it turns 900 to the right.
5. After the obstacle disappears the car starts to move again.
6. After this the car will start to move forward until the obstacle comes in front of it.

V. OBSTACLE DETECTION

On detection of the obstacle, the braking force to be applied depends upon the distance. If the obstacle appears on the Path, the host vehicle will detect it and determines the distance of the obstacle from the host. The speed is then, decreased automatically. If the distance exceeds the critical distance (not a safe distance for driving); the braking mechanism is activated and the horn is pressed. If the obstacle is a living creature, it might move out of the path by the horn. But in case the obstacle is not moving, the speed is kept on decreasing in such a way that the host is brought to a stop at a fixed pre-set value before the obstacle.

VI. SPEED MEASUREMENT

For measuring speed with an ultrasonic sensor, a microcontroller or any controller such as Arduino is necessary to connect with this sensor. The ultrasonic sensor consists of two transducers one is act as a speaker which converts the electrical pulses into sound pulses and then emits them with a high frequency of almost 40khz.similarly, the other one acts as a microphone for receiving the sound pulses which are reflected after the collision of a specific object. Because a microcontroller or any controller is attached to an ultrasonic sensor, therefore, the timer of the controller starts to count the pulses when it is transmitted and is stop when sound waves are received by the microphone. Based on sending and receiving the sound pulses the microcontroller or any controller determined to speed of that specific object.

VII.  ADVANTAGES

1. The ultrasonic sensor has high frequency, high sensitivity, and high penetrating power therefore it can easily detect external or deep objects.
2. It can be used as a movable Surveillance System.
3.  It can be controlled remotely.
4. It does not require Man Power.
5. It can be used for critical applications like a flood, bomb disposal, Fire, Terrorist attack, earthquakes, and Spying.
6. These sensors easily interface with a microcontroller or any type of controller
7. These sensors have greater accuracy than other methods for measuring the thickness and depth of parallel surfaces.
8. These sensors could easily sense the nature, shape, and orientation of that specific objects which is within the area of these sensors.
9. These sensors are easy to use, not dangerous during operation for nearby objects, persons, equipment, or material

VIII.  DISADVANTAGES

1. It is used for short distances only
2. It is not in human control.
3. During the use of an ultrasonic tester for testing it is very important to know the operational manual, in other words, it required careful attention from an experienced technician.
4. When these sensors are used for inspection purposes they should be water-resistive otherwise they could be damaged.
5. When these sensors are interfaced with a microcontroller or any controller then an experienced person or programmer is required.

IX.  APPLICATIONS

1. By doing extra things, it can be used in army applications.
2. Intruder alarm system.
3. This can be used in the robotic industry for robot sensing.
4. This can be used in a car parking system where car entry is controlled through a barrier system, the barrier must not be lowered when there is beneath a vehicle. This whole process is controlled through the ultrasonic sensor.
5. This sensor is used for detecting the speed of the motor or generator.
6. This sensor is also used in the presence detection system.

Conclusion

This project is very simple but very effective and useful. The automatic detection and avoidance technology is also popular and is required in the unmanned vehicle. For detecting obstacles one single sensor was used along with a servo motor. The percentage of accuracy and minimum probability of failure was obtained. The system shows that it can avoid obstacles, able to avoid a collision, and change its position. It can be said that with the design, more functions can be added to perform various work to lessen human stress The obstacle avoidance system of intelligent cars has the advantages of simple design, stable performance, low cost, and measurement accuracy to meet the requirements of the obstacle avoidance system. The measuring precision of the ultrasonic distance module can reach 0.3 cm, the minimum measuring distance is 2 cm, and the maximum measuring distance is 400 cm. The ultrasonic obstacle avoidance system can set the specific distance of obstacle avoidance, and the range of obstacle avoidance is wide, so it is widely used. For detecting obstacles one single sensor was used along with a servo motor. The percentage of accuracy and minimum probability of failure was obtained. The system shows that it can avoid obstacles, able to avoid a collision, and change its position. It can be said that with the design, more functions can be added to perform various work to lessen human stress. This project can be extended to line following and object avoidance robot vehicles. It also can be modified by adding various types of sensors such as flame sensor modules, and camera modules for various applications. Finally, the project will be helpful for the environment, defence, and security sectors of the country.

References

[1] Matthies, L., Kelly, A., Litwin, T., & Tharp, G. Obstacle Detection for Unmanned Ground Vehicles: A Progress Report. Robotics Research, 475–486. 1996. [2] Darms, M., Rybski, P., Baker, C., & Urmson, C. Obstacle Detection and Tracking for the Urban Challenge. IEEE Transactions on Intelligent Transportation Systems, 10(3), 475–485. 2009. [3] Discant, A., Rogozan, A., Rusu, C., & Bensrhair, A. Sensors for Obstacle Detection - A Survey 2007 30th International Spring Seminar on Electronics Technology (ISSE). 2007 [4] Borenstein, J., & Koren, Y. Obstacle avoidance with ultrasonic sensors. IEEE Journal on Robotics and Automation, 4(2), 213–218. 1988. [5] Gibbs, G., Jia, H., & Madani, I. Obstacle Detection with Ultrasonic Sensors and Signal Analysis Metrics. Transportation Research Procedia, 28, 173–182. 2017. [6] De Simone, M., Rivera, Z., & Guida, D. Obstacle Avoidance System for Unmanned Ground Vehicles by Using Ultrasonic Sensors. Machines, 6(2), 18. 2018. [7] Gibbs, G., Jia, H., & Madani, I. Obstacle Detection with Ultrasonic Sensors and Signal Analysis Metrics. Transportation Research Procedia, 28, 173–182. 2017. [8] Hu, J. W., Zheng, B. Y., Wang, C., Zhao, C. H., Hou, X. L., Pan, Q., & Xu, Z. A survey on multi-sensor fusion-based obstacle detection for intelligent ground vehicles in off-road environments. Frontiers of Information Technology & Electronic Engineering, 21(5), 675–692. 2020 [9] Tian, F. X. A Novel Method of Pipeline Obstacle Detection Using Ultrasonic. Applied Mechanics and Materials, 373–375, 819–823. 2013. [10] Fazlur Rahman, M., & Adhy Sasongko, R. Obstacle Avoidance for Quadcopter using Ultrasonic Sensor. Journal of Physics: Conference Series, 1005, 012037. 2018. [11] Azeta, J., Bolu, C., Hinvi, D., & Abioye, A. A. Obstacle detection using the ultrasonic sensor for a mobile robot. IOP Conference Series: Materials Science and Engineering, 707(1), 012012. 2019. [12] Mothe, R., Tharun Reddy, S., Sunil, G., & Sidhardha, C. An IoT Based Obstacle Avoidance Robot Using Ultrasonic Sensor and Arduino. IOP Conference Series: Materials Science and Engineering, 981(4), 042002. 2020. [13] Designing of FPGA board for obstacle avoidance robotic vehicle. International Journal of Recent Trends in Engineering and Research, 4(2), 190–197. 2018. [14] Pithode, A., Wagadre, H., Verma, N., Rathore, R., Bhange, V., & Joshi, A. OBSTACLE AVOIDING ROBOTIC VEHICLES USING ARDUINO. International Journal of Engineering Applied Sciences and Technology, 5(1), 281–284. 2020. [15] Sato, K. Obstruction detector using ultrasonic sensors for upgrading the safety of a level crossing. International Conference on Developments in Mass Transit Systems. 1998.

Copyright

Copyright © 2022 Shivangi Patidar, Shivam Patel, Shubham Dwivedi, Vikas Ojha, Suveer Chandra Dubey. 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.