İSTANBUL TEKNİK ÜNİVERSİTESİ BİLGİSAYAR VE BİLİŞİM FAKÜLTESİ OTOMATİK PARK SİSTEMİ

Transkript

1 İSTANBUL TEKNİK ÜNİVERSİTESİ BİLGİSAYAR VE BİLİŞİM FAKÜLTESİ OTOMATİK PARK SİSTEMİ Bitirme Ödevi Fikret Aktaş Bölüm: Bilgisayar Mühendisliği Anabilim Dalı: Bilgisayar Bilimleri Danışman: Yrd. Doç. Dr. Feza BUZLUCA Haziran 2013

2 I İSTANBUL TEKNİK ÜNİVERSİTESİ BİLGİSAYAR VE BİLİŞİM FAKÜLTESİ OTOMATİK PARK SİSTEMİ Bitirme Ödevi Fikret Aktaş Bölüm: Bilgisayar Mühendisliği Anabilim Dalı: Bilgisayar Bilimleri Danışman: Yrd. Doç. Dr. Feza BUZLUCA Haziran 2013

3 II Özgünlük Bildirisi 1. Bu çalışmada, başka kaynaklardan yapılan tüm alıntıların, ilgili kaynaklar referans gösterilerek açıkça belirtildiğini, 2. Alıntılar dışındaki bölümlerin, özellikle projenin ana konusunu oluşturan teorik çalışmaların ve yazılım/donanımın benim tarafımdan yapıldığını bildiririm. İstanbul, Fikret AKTAŞ

4 III OTOMATİK PARK SİSTEMİ ( ÖZET ) Bu çalışmada araba ve benzeri araçların otomatik olarak paralel park etme problemi ile ilgilenildi. Aracın kendi kendine park etmesini sağlayan sistem için ilk örnek gerçeklemek ve bu sistem sayesinde sürücülerin daha kolay bir şekilde araçlarını park edebilmelerini sağlamak projenin amacıdır. Park yapılabilecek kadar bir alanın olup olmadığının hesaplanması ve yeterli alan bulunduğunda sürücünün herhangi bir yardımı olmadan aracın duyargalar yardımı ile park edilmesi amaçlandı. Paralel park için iki farklı durum değerlendirildi. İlk durum da duvar ya da kaldırım yanına park işlemi gerçeklendi. Bu durumda, iki araç arasındaki park edilecek alanın çok geniş olması, yeterince geniş olması ve yeterince geniş olmaması gibi alt durumların yanı sıra park yerinde sadece bir aracın bulunması gibi alt durumları göz önüne alındı. Duvar kenarına park etme işlemi başarıyla sonuçlandı. Diğer ana durum olan duvarsız alana park etme işlemi gerçeklendi. Bu durumda iki aracın arasındaki mesafenin yeterince büyük olması ve yeterince büyük olmaması alt durumları göz önüne alındı. Duvarsız alanda park işlemi de başarıyla gerçeklendi.

5 IV AUTOMATIC PARKING SYSTEM ( SUMMARY ) This research deals with the automatic parking problem of a vehicles such as a car. This research deals with parallel parking for rectangular space. This system works in two phases which are data collection and parking phases. In data collection phase, information of park location is collected by ultrasonic sensor which is on the vehicle. This information is essential for clear and confident parking. If only one car is in the parking area, other vehicle is assumed to be until specific distance away. If parking space is not enough, parking operation is stopped. Minimum parking space is 1.52 times the length of the vehicle. In parking phase, vehicle moves to parking space. Clear parking may requires backward and forward maneuvers too times. Motion of vehicle is modeled according to nonholomic constraints. In this paper, proposed a basic and efficient algorithm for the automatic parking system. With this algorithm, vehicle could controlled to move to an aimed position within an assigned limit. The performance is authenticated with software and hardware. The aim of the project is generally, implementing a prototype for automatic parking system that allows the vehicle to park itself. According to park system, without driver assistance, vehicle is parked safely and comfortable. This requires finding the shortest path between the start and end points. Kinematic Model Nonholonomic constraint for the car can be as follows: θ angle of the x-axis is done with the vehicle. α angle of the front wheel of the vehicle is done with the body of the vehicle. x and y Location of the center point of the rear axle.

6 V Ultrasonic Sensor In this sensor type, a receiver located in a transmitter sensors. Detecting reflective surface and calculating the time it takes for a pulse are essential for this system. Ultrasonic sensors are used calculating distance of objects which are on the back or side of the vehicle. In this project, 14 sensors are used. Sonar sensor rays whose angle of incidence exceeds pi / 8 radians (22.5 degrees) are lost and hence ignored for distance computation. In other words, there is no sensed obstacle for rays with large angle of incidence. Automatic Parking System This system works in two phases which are data collection and parking phases. Assume that we will park A and B vehicle in Figure3.3. When vehicle continues the way by ten kilometer an hour in data collection phase, distances of between A-vehicle, B-vehicle and wall-vehicle are calculated. According to data, vehicle understands environment of park places. The vehicle will be parked with this data. In park phases firstly, R at Figure3.1 and car A are aligned with the point of the back. The purpose of this process are simplify the parking and preventing accidents with the vehicle in front. Data Collection Phases Parallel Parking Data collection algorithm for parallel parking has seven cases. First case is initial case. When drivers want to autonomous parallel parking, system enters the initial case of data collection algorithm and data from the sensors are read one time in 50 millisecond. Some decisions are made based on the values from the first sensor in Figure3.2. If first sensor measures more than 3m distance, algorithm passes the set distance phases. Because more than 3m distance shows 3m away from the vehicle on the right side or any vehicle that is not. In either case, we want the distance to the desired level before parking. If first sensor passes the car on the right side, algorithm enters the measure distance case. In all cases, the security check is performed once every 50ms. If an object in front of the vehicle is close than 2m, vehicle is braked and expected to move away from the object. In measure distance case, when 8 th sensor passes the car on the right side, we understand whether it is on the wall by looking at the sensor one and eight. To decide whether the two sensor looking at the wall are more secure. Because the sensors can be instantaneous noise can occur. After the decisions, algorithm passed set distance state. In set distance state, data from sensors are taken for understanding whether or not the wall. If such a wall, the distance between the wall and the vehicle should be 4.6m. When the first sensor detects the vehicle which is in front of the park field, width of park field is calculated. If length of the park is greater than 7.61m, algorithm passes to ready for parking phase. If length of the park is less than 7.61m, algorithm passes to initial phase.

7 VI Although parking area measured 15.2 m, if first sensor does not detect the vehicle which is in front of the park field, we decide that single car is in the park field and then passed to ready for parking no vehicle in front state In ready for parking no vehicle in front case; steering wheel straight optimized, vehicle is stopped. Counter is reset and passed end search state. In ready for parking state, the vehicle is optimized parallel to the wall. If the adjacent vehicle distance is less than 2m, steering is turned straight. Vehicle is stopped. Counter is reset and passed end search state. In this case, asked to be closer 2m to adjacent vehicle in terms of security. In end search case, the vehicle is not moved for a second. Depending on whether the wall through the appropriate algorithm is used. Vertical Parking Data collection algorithm for vertical parking has six cases. First case is initial case. When drivers want to autonomous vertical parking, system enters the initial case of data collection algorithm and data from the sensors are read one time in 50 millisecond. Some decisions are made based on the values from the first sensor in Figure3.2. If new value of first sensor is 4m longer than old value of first sensor, algorithm passes the measure distance phases. In all cases, the security check is performed once every 50ms. If an object in front of the vehicle is close than 2m, vehicle is braked and expected to move away from the object. In measure distance case, car distance from the wall are set 8.7m. When the first sensor detects the vehicle which is in front of the park field, width of park field is calculated. If length of the park is greater than 4.81m, algorithm passes to ready for parking phase. If length of the park is less than 4.81m, algorithm passes to initial phase. Although parking area measured 12.5m, if first sensor does not detect the vehicle which is in front of the park field, we decide that single car is in the park field and then passed to ready for parking no vehicle in front state In ready for parking state, the vehicle is optimized parallel to the wall. When the eighth sensor detects the vehicle which is in front of the park field, steering wheel straight optimized, counter is reset and algorithm passes to end search algorithm. In ready for parking no vehicle in front case; steering wheel straight optimized, vehicle is stopped. Counter is reset and passed end search state. In end search phase, vehicle is moved 2.77m, waited one second. Vertical parking algorithm is called.

8 VII Parking Phases Parallel Parking with Wall Parallel parking with wall algorithm has eight cases. Firstly, algorithm enters initial state. In this case, distance to vehicle from the right side is checked again. If distance is less than 2m, algorithm enters maneuver phase. Besides if no vehicle in front of park field, distance to vehicle from wall should be less than 4.6m. In other cases, vehicle will not continue to parking process. Initial process has a security case. If an object behind the vehicle is close than 80cm, vehicle is braked and expected to move away from the object. In maneuver phase, the vehicle's steering wheel rotated to the right. According to data that are taken ninth and tenth sensor, vehicle is closed the wall. Approaching the wall 2.2m, round up state is entered. Maneuver phase does not have security. The vehicle s steering wheel rotated to the left in round up state. In this phase, asked to become the vehicle parallel to the wall. When vehicle becomes parallel to the wall, algorithm pass to back up phase. If vehicle closes 1.5m to behind car, tight space forward case is entered. In tight space forward state, the vehicle's steering wheel rotated to the right and vehicle moves by five kilometer an hour. Car tries to be made parallel to the wall. If vehicle is closer 1.5m and parallel to wall, vehicle is passed to end park case. When distance between vehicle-vehicle in front is less than 80cm, tight space back is entered. In tight space back state, vehicle go to back. If distance of behind car is less than 1.8m, vehicle's steering wheel rotated to the left. If distance is less than 1.3m, algorithm pass in tight space forward case. Car tries to be made parallel to the wall in back up state. When vehicle closes 3m to behind car, end park case is entered. Steering wheel of vehicle is straight and vehicle is stopped in end park state. Vertical Parking with Wall Vertical parking with wall algorithm has third cases. In its initial state, the vehicle is made vertical to the wall. And then end state is reached. When the vehicle approaches 80cm to wall, the vehicle is stopped and the parking process ends. In both cases, the security check is made. Parallel Parking without Wall Parallel parking without wall algorithm has four cases. In initial case, essential algorithm is implemented. Firstly park field is compared with needed park length. Needed park length changes linearly according to distance between vehicle-right side cars. Besides distance

9 VIII from vehicle to right side car should be 81cm-4m due to security, otherwise vehicle is stopped. When this distance is between 81cm-4m, (1) and (2) equations are implemented. In this equations, L should be constant number. We choose two times length of vehicle that is 10.5m for L. When θ is found, algorithm passes in maneuver state. Security control is made in maneuver state. Vehicle's steering wheel rotated to the right and go back until the angle θ. And then passed the state end park. In end park maneuver, vehicle's steering wheel rotated to the left and go back until the angle θ. And park process is finished. Results Variety tests are performed in Webots simulation program. And results were obtained. According to these results, the data ware requested in data collection state. Security is provided as referred. However, some problems were encountered. The sonar sensors return always because rays whose angle of incidence exceeds pi / 8 radians (22.5 degrees) are lost and hence ignored for distance computation. In other words, there is no sensed obstacle for rays with large angle of incidence. This case is considered in design process. Parallel parking with wall process is achieved as desired result. In parallel parking without wall state was a problem in terms of process safety. When an object behind the car stops at the initial stage. The process continues from where it left off when object moves away. However, car parking is incorrect. Error is not believed to be caused design.

10 IX İÇİNDEKİLER 1 GİRİŞ PROJENİN TANIMI VE PLANI Projenin Tanımı Proje Planı Projenin Kapsamı Projeye İlişkin Kestirimler Risk Yönetimi Zamanlama Proje Kaynakları KURAMSAL BİLGİLER Kinematik Model Ses Ötesi Duyarga Otomatik Park İşlemi Bilgi Toplama Park Etme ANALİZ VE MODELLEME Bilgi Toplama Evresi Senaryo Grubu SG1: Bilgi Toplama Süreci Park Etme Evresi Duvar Yanına Park Etme Senaryo Grubu SG2: Duvar Yanına Park Süreci Duvarsız Alana Park Etme Senaryo Grubu SG3: Duvarsız Alana Park Süreci Duvar Önüne Dikey Park Etme Senaryo Grubu SG4: Duvar Önüne Dikey Park Süreci TASARIM, GERÇEKLEME VE TEST Bilgi Toplama Evresi Paralel Park Dikey Park Park Etme Evresi Duvar Yanına Park Etme Duvarsız Alana Park Etme Duvar Önüne Dikey Park Etme DENEYSEL SONUÇLAR SONUÇ ve ÖNERİLER KAYNAKLAR... 23

11 1 1 GİRİŞ Aracın kendi kendine park etmesini sağlayan otomatik park sistemi için ilk örnek gerçeklemek ve otomatik park sistemi sayesinde sürücülerin daha kolay bir şekilde araçlarını park edebilmelerini sağlamak projenin ana problemdir. Bu problemi gerçeklerken başlangıç ve bitiş noktaları arasında en kısa yol bulunması istenir. Birçok yazar bu probleme değişik çözümler üretmiştir. Demirli ve Khoshnejad [1], otomatik paralel park işlemini araba benzeri robotlar için bulanık sinir ağı stratejisini duyarga tabanlı kontrol yaklaşımı ile sundular. Bu yaklaşımda park alanı boyutunun ölçülemez olduğu durum üzerinde durdular. Bu sistem herhangi bir oluşturup izleme gerektirmez. Denetleyiciye duyargalardan gelen bilgilere göre hareket yönüne karar verebilmesi öğretilir. Gomez-Bravo, Cuesta ve Ollero [2], holonomik olmayan tekerlekli araçların hem paralel hem de çapraz park etme sistemleri üzerine yaklaşım sundular. Çarpışmayı önlemek amacıyla bazı kısıtlamalar kullandılar. Ama park işlemini çok sayıda manevra ile yapmak yerine tek seferde park etme işlemi üzerinde durdular. Bu da park yerinin yeteri kadar büyük olmasını gerektirir. Yanan Zhao ve Emmanuel G. Collins Jr.[3], bulanık mantık ile dar alanlarda otomatik park etmek için bir yöntem önerdiler. Bu yaklaşımda manevra işlemini üç adımda gerçeklendi. Ters hareket bulanık mantık denetleyicisi için üyelik fonksiyonları ve ölçekleme faktörlerinin belirlenmesinde genetik algoritması kullanıldı. Oluşturulan algoritmayı ATRV-Jr robotuna entegre ettiler. Sungon Lee, Minchul Kim, Youngil Youm, Wankyun Chung [4], araba benzeri robotların part etmesi için diğerlerinden farklı olarak bulanık sinir ağlarını kullanmadılar. Belirli girdiler için matematiksel denklemlerle belirli çıktılar üretme yöntemini sundular. Kinematik model ile ilgilenip, belirli kısıtlar altında denetleyici tasarladılar. Jiang [5], duyargalı aracın park işlemini tarama, pozisyon alma ve manevra işlemi olmak üzere üç sürece ayırdı. Manevra işlemi sürecinde yolu birbirine teğet olarak bağlanmış iki yaydan oluşturdu ve çarpmayı önlemek için yasaklı bölge tanımladı. Ankit Gupta, Rohan Diverkar, Mohit Agrawal[6], park işleminden önce aracın duruş açısına göre ve park alanının büyüklüğüne göre araç kinematiğini kullanarak otomatik park işlemini sağladılar. Duyargadan alınan verilere göre farklı durumlar tanımladılar. Yapılan çalışma ise holonomik olan araçlar üzerinde gerçeklendi. Aracın park edilmesi gereken yerin bulunması ve park etme işlemi sırasında çevresel faktörleri göz önünde bulundurmak amacıyla ses ötesi duyargalar kullanılması uygun bulundu. Algoritma olarak belirli girdilere için matematiksel denklemlerle belirli çıktılar üretme yöntemi kullanıldı. Algoritma temelde park yeri bulma ve park etme olmak üzere ikiye ayrıldı. Park yeri bulma algoritması aracın park edebileceği bir alan ararken aynı zamanda duvar kenarına mı yoksa duvarsız alana mı park yapılacağına karar verdi. Park etme algoritmasında ise duvarın olup olmaması göre ve eğer araç duvar kenarına park edilecek ise park alanındaki araç sayısına göre park işlemini gerçekleştirildi. Bu işlemler gerçeklenirken duyargalardan alınan girdilere göre değişik durumlara geçilmesi sağlandı. Arama işlemi ve park etme işlemleri gerçeklenirken gerekli güvenlik önlemleri sağlandı. Raporun genel yapısı şu şekildedir: Bölüm 2 de projenin tanımı ve planı, bölüm 3 te kurumsal bilgiler yer almaktadır.