gps-tracking-system-for-autonomous-vehicles-88332 [wiki.modywzm.pl]

GPS tracking system for autonomous vehicles Abstract This paper presents a proposed design of a mechatronics system for autonomous vehicles. The proposed design has the capacity to to memorize a route based on Global Positioning System (GPS) rather than using pre-saved maps that are infrequently updated and do not include all roads of all different countries. Moreover, it can autonomously avoid obstacles and detect bumps. Experimental tests are conducted using a small-scale car equipped an issue proposed mechatronics device. The results show that the proposed system operates with minor errors and slips. The proposed autonomous vehicle can serve normal, disabled, and older people. It can be used on roads and even inside facilities like campuses, airports, and factories to transport passengers or loads thus reducing workmanship and costs. Previous article in issueNext article in issue Keywords Autonomous vehiclesGPSCollision avoidanceTracking system 1. Introduction For the past fifty years, engineers went on trying to find keys to further minimize the human input in driving vehicles. Jansson [1] stated that 93% of car accidents are caused by human errors and also a study conducted by the Lebanese Red Cross [2] revealed that car accidents in 2014 yielded 14,516 casualties. These shocking statistics are due to the constantly increasing traffic density upon the slow developing existing infrastructure as stated by Zlocki et al. [3]. This resulted in more and difficult driving situations, which upsurge the possibility belonging to the human error in so doing increasing accident tariffs. The need to develop driverless vehicles arouse in order to remove this error the majority importantly to spare human lives. Another statistical study conducted by the Lebanese Ministry of Social Affairs [4] said that 10% of the Lebanese population have problems a disability. So people who face difficulties with driving, such as disabled people and seniors would be willing to experience the freedom of car travel using autonomous are probably the biggest. On the luxury side, cars could become mini-leisure rooms where passengers will have zero need to be facing forwards at all times and can sleep, enjoy entertainment features, and even work on the go without the concern of driving. This technology is accompanied with disadvantages, as driverless cars would be very expensive when first introduced. Also truck drivers and taxi drivers would lose their job opportunities. On the other hand, crash repair shops and automobile insurance agencies might suffer to be the technology makes certain aspects of these occupations obsolete. After surveying rewards of and disadvantages of that particular technology, researchers observed that the benefits from it would likely outweigh its disadvantages, beeing the economic concerns that might arise are like several economic problem fresh technology brings. This matter has long been present and people found other fields of experience to cope with new technologies. So why haven't we seen autonomous vehicles on the roads yet? The numerous scenarios these vehicles will face your real world and the conditions they require to operate in become the main reasons of holding back manufacturers from releasing them in the market. Multiple automation systems for vehicles were developed to address these numerous situation. One of these systems is the tracking system that sets the location for the vehicle. A system developed by Quddus and Noland [5], uses a digital road map, which is a machine vision of the road that detects the actual boundaries and curb using a Light Image Detecting and Ranging (LIDAR) sensor, to keep the vehicle centered between road limits by using the by-wire controls consistent with Davis [6]. On the work done by Kojima et . [7], a tracking system uses GPS positional data to roughly estimate the vehicle's location and a laser scanner observe the vehicles surroundings to roughly estimate the vehicle's location by coordinates and enhance it with relative positional changes of surrounding points. In addition, marker tracking systems position automobile by adhering to special markers or lines according to Zhu and Chen [8]. Other automation systems include collision avoidance systems. When facing a possible collision, a driver may have two options, either brake or steer. Labayrade et al. [9], [10] applied a longitudinal collision avoidance system to control the braking of this vehicle to either stop the vehicle before reaching the obstacle or maintain safe distances utilizing vehicles. A lateral collision avoidance system steers the vehicle away from an accident based on the situation of the collision event similar to the work of Glaser et al. [11], or as the whole devised by Scacchiolia et al. [12] that applies intentional instability by controlling the vehicle's brakes to drift it away from potential danger when neither steering nor slowing down is enough for avoiding a collision. Additional existing systems are self-parking systems discussed by Paromtchik et al. [13] and lane departure systems presented by Enache et . [14]. Driverless cars often give you the user with digital pre-saved maps of roads where he can make his preferred route via a touch screen as stated by Kaller [15]. Don't wish to has a drawback, as digital maps are not updated frequently by manufacturers and do not include all roads. The strategy of setting the route in this paper addresses this problem. Indeed, the user has to push his car manually over his desired route limited once while the GPS tracking system memorizes the rd. This gives the liberty of choosing any path, does not bound to a particular pre-saved routes, and enables updating the roads instantly when they change. This paper focuses on this method alone. However, to get the best of both worlds, the typical and the proposed method can double together where the driver sets the route using digital maps, then update these maps when asked. This paper presents a mechatronics system for autonomous vehicles. The proposed system is able to memorize a route based on a GPS tracking system. For more practical applications, furthermore, it includes the following features: collision avoidance, bump detection. The proposed design commits to be able to tight budget by building model from the autonomous vehicle using cheap microcontrollers and sensors. It can be used to transport passengers inside campuses, airports and even on paths. Moreover, it could be used to handle loads and transport these questions certain facility or factory reducing workmanship and expenditure. 2. Proposed design 2.1. Mechatronics system The systems proposed in this particular paper were implemented on a prototype dependent upon a small scale vehicle that was modified for getting by-wire controls and matches all sensors and electronic hardware. It features a metal chassis on which a motor-gearbox drivetrain and a by-wire rack and pinion steering assembly are in place. It also holds in the guts the Arduino Mega microcontroller programmed using C++ language which accommodates multiple sensors distributed among different locations in automobile as shown in Fig. 1. Download high-res image (409KB)Download full-size image Fig. a single. Prototype of the proposed autonomous vehicle. The connections of the various sensors and actuators relative to their position on the prototype are presented in Fig. several. Download high-res image (401KB)Download full-size image Fig. ii. Proposed mechatronics procedure. The various electronic components and their usages are represented in Table 12. Table 7. Electronics list. Electronic Components Usage Error range Arduino mega Microcontroller N/A 5* HC-SR04 ultrasonic sensors Reads distances up to 3m 5% error rises in longer distances Android phone Includes the GPS sensor nil.51m reading variations HC-06 bluetooth module Receives GPS coordinates from phone Exact readings 3* 10K potentiometers Steering servo, LCD contrast, set PWM Exact readings GY-85 magnetometer Provides yaw angle of automobile Consists of 2 variation 2* infrared modules Detects obstacles considerably 30cm 5% error Remote control module Radio control signal receiver Exact readings Hall effect sensor Drive shaft RPM counter 20% error 2*12V DC motors Steer-by wire motor, driver motor N/A Red LED Indicates faults N/A 1602 LCD screen Displays readings and modes N/A 4*Tip 120 transistors Controls driver motor relays N/A LM293 H-bridge Controls steering motor direction N/A Relay motor driver Controls driver motor direction N/A 2.2. Tracking of the trail In order to navigate a certain path autonomously, the driver has they are the vehicle on the required path only for once while a GPS tracking system memorizes the road by saving GPS waypoints received out of the GPS sensor of an onboard Android phone and distances calculated from the velocity sensor based on a control sequence as shown in Fig. two. Download high-res image (173KB)Download full-size image Fig. 5. Flowchart of control sequence for the tracking process. Fig. 4 illustrates how a forward path that doesn't include any left or right bends is saved by the tracking procedure. The starting point is the datum that the distance covered, D, is calculated from the velocity provided coming from the velocity sensor while to come. Download high-res image (47KB)Download full-size image Fig. iv. Heading forward tracking criterion. This distance ends once the vehicle encounters a turn as shown in Fig. 5. Download high-res image (55KB)Download full-size image Fig. couple of. Saved distance. The final distance will likely be saved a great array to be able to called next in the autonomous adventure. As the steering occurs, present-day coordinates on the vehicle are saved as shown in Fig. an affordable vacation. Download high-res image (61KB)Download full-size image Fig. a number of. Saved way point. When a turn ends, a forward path starts again in which a new starting point is taken and the gap covered is measured as explained within the. This phase is illustrated in Fig. a number of. If the vehicle encounters another turn, replacing procedure is made as shown in Fig. 8. Download high-res image (90KB)Download full-size image Fig. six. New forward path. Download high-res image (98KB)Download full-size image Fig. several. New way point. The same procedure repeats until ultimate destination is reached as shown in Fig. six. This way of tracking the path enables the vehicle to calculate the turning angles of each bend and the instants a bend is encountered as explained in Section 2.3. Download high-res image (110KB)Download full-size image Fig. 9. Saved full path example. 2.3. Autonomous navigation After the road has been memorized through the tracking trip, the vehicle can now navigate this path with no driver disturbance. The same path illustrated in Fig. 9 will be regarded as in it. The procedure of navigating autonomously is explained in the flowchart presented in Fig. 10. Download high-res image (268KB)Download full-size image Fig. eleven. Flowchart of control sequence within the autonomous direction-finding. The driving motor with the vehicle is switched on automatically after selecting the autonomous style. For the forward path, the saved distance, D, is compared with distance Dc which may be the current distance covered along with vehicle. If Dc is less than D, car will continue moving straightforward as shown in Fig. 11(a), two distances are equal as depicted in Fig. 11(b). Download high-res image (148KB)Download full-size image Fig. 11am. Forward path in autonomous mode; (a) the covered distance is as compared to the saved distance, (b) the covered distance is equal to the saved distance. The end of the forward path indicates the beginning of a turn. Therefore the first and second waypoints these are known as in order to calculate the turning direction and angle as shown in Fig. twelve months. Download high-res image (91KB)Download full-size image Fig. 6. Turn angle example. In order to calculate the turn angle , the coordinates, latitude (LAT) and longitude (LON) values, of earlier waypoint are subtracted from the coordinates with the next waypoint. The longitude and latitude differences are and , respectively, as expressed in Eqs. (1), (2). (1) (2) Using the functions of the triangle, the angle can be calculated as shown in Fig. 13 and Eq. (3). (3) Download high-res image (67KB)Download full-size image Fig. thirteen. Turn angle calculation. This case is only applicable if your vehicle approaches the start of turn in the same direction of the road as shown in Fig. 14(a). If your vehicle approaches the turn at an angle as shown in Fig. 14(b), the previous calculation is false and a new turn angle, , should be calculated. Download high-res image (119KB)Download full-size image Fig. 12. Turn angle conditions; (a) direction of vehicle along line, (b) vehicle approaching the turn at an angle. To calculate , Eq. (3) in order to modified to pay for the heading of the vehicle at the entry purpose. This compensation depends on the heading angle of your vehicle measured from the north from your orientation sensor as illustrated in Fig. 15. Download high-res image (70KB)Download full-size image Fig. 13. Presentation of heading angle . After acquiring this angle at the entry reason for the turn, the angle can be calculated dependent upon quadrant conditions and the sign of as illustrated in Table several. Table a few. Equations of turning angles. The equations presented in Table 2 will be used to calculate the turn angle of essential turn the actual planet considered path shown previously in Fig. 9 keeps growing vehicle is approaching the turn at an angle and not along the vertical line as shown in Fig. seventeen. Download high-res image (144KB)Download full-size image Fig. seventeen. Second bend turn angle. If the calculated turn angle is positive, then the vehicle should turn right and if it is negative, automobile should turn left. Car will keep turning so that the orientation sensor reads a rotational displacement equal to the calculated turn angle. After that angle is reached, automobile heads forward and operates procedure explained in it is done again. 2.4. Collision avoidance In order to avoid crashing into other vehicles and any obstacles arrive near the autonomous vehicle, a collision avoidance will be a must in an autonomous vehicles. The system installed in this version of the autonomous vehicle consists of three ultrasonic proximity sensors mounted for your vehicle's nose and facing forward as shown in Fig. 20. They serve to detect any obstacle that comes within the width within the vehicle. These sensors can read up together with a distance of 3m with high accuracy and return the exact position among the obstacle compared to the suv. Download high-res image (108KB)Download full-size image Fig. seventeen-year-old. Ultrasonic proximity sensors. The collision avoidance operation consists of two portions. The first phase is triggered if an obstacle falls within 1m in front of car. The car is then ordered to stop until the highway is clear again. It can be noteworthy that the first phase is triggered if superb sensor reads an obstacle within 1m, as illustrated in Fig. 18. Download high-res image (132KB)Download full-size image Fig. 17. First phase collision avoidance; (a) one sensor detects an obstacle, (b) two sensors detect the hurdle. The second phase is triggered when an obstacle suddenly falls in front of car at a distance as compared to 0.5m. Car is then ordered to do an evasion maneuver since it cannot completely stop within 0.5m and will inevitably collide with the obstacle. Instead, the vehicle steers beyond your obstacle. If your left sensor detects the obstacle, car steers right and or viceversa as shown in Fig. 19. Download high-res image (185KB)Download full-size image Fig. 19. Second phase collision avoidance. The evasion maneuver explained hereafter has two sequences; the first is shown in Fig. 20 that many second is shown in Fig. 18. When an obstacle suddenly falls within 0.5m, the vehicle steers immediately dodging the obstacle. Automobile stops steering when the obstacle isn't observable. The actual dodging sequence, the deviation angle is noted so that you can retain the original heading. When the vehicle steered by an angle into the right, it steers again to the left from the same understanding. The vehicle now is parallel towards the original track as shown in Fig. 20. It can be noted that the solid line represents the normal path and also the dashed line represents the evasion piste. Download high-res image (119KB)Download full-size image Fig. approximately. First evasion sequence. Download high-res image (129KB)Download full-size image Fig. 22. Second evasion sequence. The second sequence could be the opposite for this first the vehicle steers back using the original path by the same deviation incline. The vehicle then steers back right to take back the original path as shown in Fig. 21. 2.5. Bump detection In order to cope with changing road conditions, the proposed vehicle is equipped with a bump detection system that spots any speed bumps while traveling and slows the vehicle's speed to avoid damage and compromise passenger discomfort. Fashioned consists of two infrared emitter detectors mounted before front wheels and pointing on the way. As long as the sensors read a regular distance on the ground, which means that the road is flat as shown in Fig. 22(a). If ever the distance read by one of the several sensors decreases, it refers to a bump encounter killing the respective wheel as shown in Fig. 22(b). Then, the vehicle is ordered to decrease the pace of until automobile covers a distance of 0.7m so that the rear wheels pass the bump as presented in Fig. 22©. Download high-res image (164KB)Download full-size image Fig. 24. Bump detection; (a) no bump detected, (b) bump detected by one of the sensors, © speed is reduced until the rear wheels pass the bump. 3. Test results and discussion 3.1. Autonomous navigation results The data obtained by testing the tracking system was analyzed to approve the proposed design. The realistic proportions of the saved track presented in Fig. 23 were measured using a measuring tape and a protractor. The saved GPS coordinates and distances from the tracking trip are presented in Fig. twenty-four. Download high-res image (349KB)Download full-size image Fig. 8. Path realistic dimensions. GPS tracking system unveiled for Alzheimer's patients -res image (331KB)Download full-size image Fig. per day. Saved parameters of the path. Now the turn angles of every curve could be calculated when using the equations of turning angles presented in Table 2. Taking the first curve as an example, yields: (4) (5) Since and , then from Table 2, it makes sense that: (6) (7) Realistically the angle of your first curve is 69 while the calculated angle is 67. This is due to some error in the GPS readings and this error can relatively be accepted. In the autonomous trip, the realistic proportions of the path are shown in Fig. 25 for the red1 line represents the saved track and nowhere line represents the autonomous track. On the other half hand, the type measured with the velocity sensor and the angles calculated based on your equations caved Table 2 are shown in Fig. 26. Download high-res image (373KB)Download full-size image Fig. 27. Autonomous trip realistic results. Download high-res image (371KB)Download full-size image Fig. twenty-six. Calculated parameters. It is observed that the errors obtained with the measured distance and calculated turn angles are in reasonable proportions. As illustrated in Fig. 26, the blue line rrs extremely close for the red line which defines an error range from 0.5 to 1m from the saved record. These errors may be reduced further by using more precise but expensive GPS modules, more accurate odometers, and further localization tools. 3.2. Bump detection results The monitored parameters were the velocity and the pulse Width Modulation (PWM) benefit. The PWM is a technique that would control the rotational velocity of the driver motor by reduction of or helping the current flow to the DC generator. Once the sensors detect the bump, the PWM value is dropped right down to zero for you to instantly lessen vehicle's speed drastically before climbing the bump. Then after 1s, the PWM increases to 150 rear wheels pass the bump. Next, the PWM is restored to major value of 255 which corresponds towards original velocity as shown in Fig. 27. Fig. 28 shows the time history within the velocity of this vehicle. Download high-res image (55KB)Download full-size image Fig. tenty-seventh. Pulse Width Modulation time history. Download high-res image (51KB)Download full-size image Fig. tenty-seventh. Velocity time history. It is observed how the velocity dropped drastically as a PWM went from 255 to 0 then became approximately constant when the PWM value increased to 150. To learn vehicle's rear wheels passed the bump, the PWM was restored to 255 and the rate increased back to its original value. Time intervals as well as the change in PWM value were set after experiment in order to get the suitable velocity to pass over the bump gently. It was observed that the suitable velocity was between 3 and 3.5km/h and the PWM values were set so. 4. Conclusions In this paper, a mechatronics system for autonomous vehicles was proposed. It addresses thought of pre-saved digital maps that aren't frequently updated and don't contain all roads and shortcuts. This proposal the particular tracking system to introduce unknown roads to the traditional digital google maps. The methods of tracking were discussed in details. Approach to to create safe autonomous vehicle, a limited of systems for collision avoidance and bump detection were integrated as sufficiently. Several tests and experiments were conducted on a small-scale car in order to prove that the proposed systems are practical and available. It turned out that the product operated with acceptable errors. The proposed autonomous vehicle can serve normal, disabled, and elderly people. GPS Tracking Systems Explained can be utilized on roads and even inside facilities like campuses, airports, and factories to lug passengers or loads thus reducing workmanship and amounts.