PROCEEDINGS OF THE INSTITUTE OF VEHICLES 3(99)/2014

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1 PROCEEDINGS OF THE INSTITUTE OF VEHICLES 3(99)/2014 Wojciech Skarka 1, Katarzyna Jezierska-Krupa 2, Maciej Krysiak 3 COMPARISON OF TWO VERSIONS OF BLIND SPOT INFORMATION SYSTEMS IN BYTEL AND MUSHELLKA TWO RACE VEHICLES 1. Introduction Since 2012 the Smart Power Team [12] has been actively participating in worldwide competition The Shell Eco-marathon (SEM). The main idea behind this event is to gather and encourage students from all over the world to invent and build the most energy efficient vehicle possible. This year SEM edition will be our third start in Prototype category, but also, hopefully successful, debut in Urban category. Our first child MuSHELLka [7] (Fig. 1), is a prototype vehicle, the second one Bytel, is an urban car. Fig. 1. Vehicle MuSHELLka on Shell Eco-marathon 2013 in Rotterdam Netherland Since the beginning our team has put a lot of pressure on the safety issues [8, 9]. MuSHELLka is equipped with such safety systems as: BLIS [1, 2, 3] (Blind Spot Information System) and CDIS (Collision Detection and Information System). Especially for Bytel not only have we improved previously mentioned systems but also we have developed new Active Driver Assistance Systems: OHRS (Overtaking Horn Reminder System), DPMS (Dew Point Measurement System) and MSS (Main Supervision System). In this article we have focused on comparison of Blind Spot Information System that is already implemented in MuSHELLka and, for now just designed, BLIS for Bytel. 1 Prof. Wojciech Skarka, Institute of Fundamentals of Machinery Design, Silesian University of Technology 2 Eng. Katarzyna Jezierska-Krupa, Institute of Fundamentals of Machinery Design, Silesian University of Technology 3 Eng. Maciej Krysiak, Institute of Fundamentals of Machinery Design, Silesian University of Technology 119

2 Fig. 2. Methodology of verification and virtual prototyping of automation systems on the basis of MuSHELLka race vehicle 2. BLIS sytem for MuSHELLka and Bytel BLIS, used in MuSHELLKA vehicle, was a prototype system which was elaborated for researching the possibilities of using it in a race vehicle and therefore, inexpensive versions of sensors were used. The system research with the aid of virtual prototyping environment based on tailor made methodology [5, 6] for this example, confirmed the purposefulness of using this system and its potentials (Fig. 2). The consecutive research carried on the race track and test loop in Gliwice endorsed the features of the system and allowed its validation [6]. Fig. 3. Model of urban category Bytel vehicle 120

3 The subsequent research is much easier due to the elaboration of virtual environment of the race spot i.e. the racing track in Rotterdam. The necessity to implement improvements in BLIS was triggered by experiences, we had opportunity to gather, and also by new technologies we have come to learn. BLIS system in a new Bytel vehicle (Fig. 3) is tested in the environment of virtual prototyping, which was elaborated in Prescan system [11] with Matlab/Simulink and it consists of the model of race track, the vehicle, the model of automation system of the set with the models of used sensors. 3. Comparision of two versions of BLIS system The main difference in these two systems is the type of sensor used in MuSHELLka s BLIS we used two sonars and one fotoelectric sensor, while in Bytel we plan to use one Hokuyo lidar. This way we want to not only improve the range of our measurements but also the system s accuracy. At the design stage of a new version of BLIS expected use of photoelectric sensors (Fig. 4a), Microsoft Kinect devices (Fig. 4b) and Hokuyo lidar (Fig. 4c). Fig 4. Concepts of BLIS system for Urban type vehicle Optimal solution, due to the range, accuracy and compact design is the use of the Hokuyo lidar. It is characterized by an angular range of 270 degrees and the detectability of objects up to 50 meters. Figure 4 shows a graphical comparison of the scope of the systems. For a system based on Hokuyo lidar showing the scan area with a radius of 4m would not obscure figure. Scan angle is limited by the rear of the vehicle (Fig. 5). BLIS system in the vehicle MuSHELLka (Fig. 6)has a smaller scan angle despite the use of a larger number of sensors. Due to the amount of data provided by Hokuyo Lidar is required a PC. Data processing using a single board computer Kontron PiTX. Displays information for the driver will be show via Tablet. Tablet offers a high screen resolution in a small screen. The use of a computer requires a greater demand for energy. Hokuyo Lidar itself requires energy needs of about 5W, single board computer with a hard disk drive requires 30W of power. Compared to the system applied MuSHELLka, the energy demand increases 2.5 times. 121

4 Fig 5. Comparision of two versions of BLIS system Fig. 6.Location of BLIS system sensors in Mushelka: 1 - Ultrasonic sensors HC-SR04; 2 - photoelectric sensor Datalog S

5 Sensors Range of activity Mushellka 2 ultrasonic, 1 fotoeletric Range: 2-3,5m, Angle: 160 Table 1. BLIS versions summary Bytel 1 laser range scanner Range: 4-50m, Angle: 190 Signal analysis device Arduino Due One board micro computer Informing the driver diodes Touchscreen System cost About 600 zł Depending on the scanner model: zł 4. Conclusions The proposed support safety system is much more expensive than the previous version (Tab. 1), but such a system increases the accuracy of vehicle detection. The use Hokuyo lidar allows for further development of the system towards the creation of an autonomous vehicle. Based on data from the signal of an autonomous vehicle can determine whether it can change lanes. Such a sensor can also be used for automatic parking. When creating a new version of BLIS thought about using cameras and image recognition, but this would require massive computing power to analyze real-time image in such a dynamic environment. References [1] Gietelink O.J., Ploeg J., De Schutter B., (2009) Development of a driver information and warning system with vehicle hardware-in-the-loop simulations. Mechatronics, The Science of Intelligent Machines, An International Journal, A journal of IFAC, the International Federation of Automatic Control, Volume 19, Issue 7, pp s [2] Wua B.-F., Huang H.-Y., Chen C.-J., Chen Y.-H., Chang C.-W., Chen Y.-L.. A vision-based blind spot warning system for daytime and nighttime driver assistance. Computers and Electrical Engineering 39 (2013) [3] Skarka W., Otrębska M., Zamorski P., (2013) Simulation of dangerous operation incidents in designing advanced driver assistance systems, XII International Technical Systems Degradation Conference: Liptowský Mikulaš, Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne, Warsaw [4] Skarka W., Otrębska M., Zamorski P., Cichoński K. Designing safety systems for an electric racing car. Activities of transport telematics. 13th International Conference on Transport Systems Telematics. TST 2013, Katowice-Ustroń, Poland, October 23-26, Selected papers. Ed. Jerzy Mikulski. Berlin: Springer, 2013, s , bibliogr. 14 poz. (Communications in Computer and Information Science ; vol ). 123

6 [5] Sternal K., Cholewa A., Skarka W., Targosz. M. Electric vehicle for the students Shell Eco-marathon competition. Design of the car and telemetry system. Telematics in the transport environment. 12th International Conference on Transport Systems Telematics. TST 2012, Katowice-Ustroń, Poland, October 10-13, Selected papers. Ed. Jerzy Mikulski. Berlin : Springer, 2012, s , bibliogr. 9 poz. (Communications in Computer and Information Science; vol. 329) [6] Reoski A. (2011) Active safety of a car. Suspension and braking systems and steering (In Pl.), Oficyna Wydawnicza Politechniki Warszawskiej, Warsaw pp , [7] Pihowicz W. (2008) Technical safety engineering. Basic issues (In Pl.), Wydawnictwa Naukowo-Techniczne, Warsaw [8] Web page - Prescan, Tass (2014) [9] Web page - Modeling of Design Students Association (2014) - Abstract Since 2012 the Smart Power Team has been actively participating in worldwide competition The Shell Eco-marathon. From the beginning, the team is working to increase driver safety on the road. This article focuses on the comparison of systems to detect objects in the blind spot of the vehicle used in Mushellka and the proposed Bytel vehicles. Key words: BLIS, driver safety, Shell Eco-marathon PORÓWNANIE DWÓCH WERSJI SYSTEMU DO WYKRYWANIA OBIEKTÓW W MARTWYM POLU W LUSTERKACH W POJAZDACH WYŚCIGOWYCH BYTEL I MUSHELLKA Streszczenie Zespół Smart Power od 2012 roku bierze udział w zawodach Shell Eco-marathon. Od początku zespół pracuje nad zwiększeniem bezpieczeństwa kierowcy na drodze. W tym artykule skupiono się na porównaniu systemów wykrywających obiekty w martwym polu zastosowanych w pojeździe Mushellka oraz w projektowanym pojeździe Bytel. Słowa kluczowe: Martwe pole, bezpieczeństwo kierowcy, Shell Eco-marathon, 124