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CO-OPERATIVE ADAPTIVE CRUISE CONTROL (CACC) BASED ON CAN PROTOCOL USING MICROCHIP ABSTRACT Intelligent vehicle cooperation based on reliable communication systems contributes not only to reducing traffic accidents but also to improving traffic flow. Adaptive cruise control (ACC) systems can gain enhanced performance by adding vehicle vehicle communication to provide additional information to augment range sensor data, leading to cooperative ACC (CACC). This project presents the design, development, implementation, and testing of a CACC system. It consists of two controllers, one to manage the approaching manoeuvre to the leading vehicle and the other to regulate car speed. In the prototype, we are going to design the ACC using a PIC18F458 micro-controller as the Main controller and another PIC18F458 as the Low level controller. Using Controller area network (CAN) protocol the slave module will transmit the data i.e. GPS location, Speed using speed sensor and distance based on ultrasonic sensor interface. The data will be transmitted to the Master Controller for analysing, then will control the motor (i.e. Engine). INTRODUCTION Significant developments in advanced driver assistance systems (ADAS) have been achieved during the last decade. Intelligent systems based on on-board perception/ detection devices have contributed to improving road safety. The next step in the development of ADAS points toward vehicle-to-vehicle (V2V) communications to obtain more extensive and reliable information about vehicles in the surrounding area, representing cooperative intelligent transportation systems (ITS).Using wireless communication, potenti al risk situations can be detected earlier to help avoid crashes, and more extensive information about other vehicles motions can help improve vehicle control performance. Research projects have been conducted throughout the world to define the requirements for an appropriate vehicular communication system and its possible applications. Although most of the V2V cooperative ITS applications have been focused on

improving collision avoidance and safety, the extension of the commercially available adaptive cruise control (ACC) system toward the cooperative ACC (CACC) system has a high potential to improve traffic flow capacity and smoothness, reducing congestion on highways. By introducing V2Vcommunications, the vehicle gets information not only from its preceding vehicle as occurs in ACC but also from the vehicles in front of the preceding one. Due to this preview information, oscillations due to speed changes by preceding vehicles can be drastically reduced. LITERATURE SURVEY Benefits from including communications in ACC systems have been widely studied in recent years. Prior experimental results using vehicle vehicle cooperation to improve vehicle-following performance were achieved by the California Partners for Advanced Transit and Highways (PATH) in 19 97when a platooning manoeuvre involving eight fully automated cars was carried out using wireless communication among vehicles, mainly for longitudinal control, and magnetic markers in the infrastructure, mainly for lateral control. Based on the idea of a leading vehicle guiding several followers, the Safe Road Trains for the Environment (SARTRE) European Union project has developed virtual trains of vehicles in which a leading vehicle with a professional driver takes responsibility for each platoon, That concept of the professional driver in the first vehicle was originally developed in the European project called CHAUFFEUR. Specifically related to CACC implementations in production cars, two important projects were recently conducted in the Netherlands. The Connect & Drive project, funded by the Dutch Ministry of Economic Affairs, carried out a CACC demo using six passengervehicles adopting a constant time gap spacing policy. For the Grand Cooperative Driving Challenge competition in 2011, nine heterogeneous vehicles from different European research institutions tried to perform a twolane CACC platoon. This competition revealed some of the most important problems to be solved before bringing this technology into production, including communication systems reliability. From the control point of view, most of the implementations were based on proportional proportional-derivative feedback/feed forward controllersor model predictive control techniques. When it comes to designing a CACC system, string stability plays a key role.

The goal is designing a system able to reduce disturbances propagated from the leading vehicle to the rest of the vehicles in the platoon. There are two different approaches to car-following gap regulation, i.e., one based on constant spacing or one based on constant time gap. A comparative study between them, where CACC stability was discussed, was presented in. Several papers have dealt with string stability analysis and simulations, based on simplified theoretical models of ACC vehicle-following behaviour, and have shown encouraging results. PROBLEM STATEMENT Using wireless communication, potential risk situations can be detected earlier to help avoid crashes, and more extensive information about other vehicles motions can help improve vehicle control performance. FEATURES Ultrasonic sensor is used to measure the speed of the front vehicle. GPS is used to measure the location continuously and it will be displayed on the lcd. BLOCK DIAGRAM LCD LCD PIC 18F458 (SENSING UNIT) CAN MCP2551 PIC 18F458 (ENGINE UNIT) L293 DC Motor DRIVER ULTRASONIC SENSOR GPS 2 WHEEL ROBOT(60rpm) COMPONENTS PIC18F458 CAN Microcontroller LCD,

ULTRASONIC SENSOR, GPS, L293 DCM DRIVER And DC Motor SOFTWARE USED IDE: MPLAB TOOL:PICKIT2 METHODOLOGY Front vehicle speed: 30 kmph CACC vehicle speed: 60 kmph (More gap) Front vehicle speed: 30 kmph CACC vehicle speed: 50 kmph (Medium gap) After some time, timer exceeds the threshold level CACC vehicle overtake the front vehicle. Front vehicle speed: 30 kmph CACC vehicle speed: 30 kmph (Less gap) Timer will start CACC vehicle follow the front vehicle s speed DESCRIPTION The Global Positioning System (GPS) is a satellite based navigation system that sends and receives radio signals. A GPS receiver acquires these signals and provides the user with information. Using GPS technology, one can determine location, velocity and time, 24 hours a day, in any weather conditions anywhere in the world for free. Ultrasonic sensor The sensor is primarily intended to be used in security systems for detection of moving objects, but can be effectively involved in intelligent children s toys, automatic door opening devices, and sports training and contact-less-speed measurement

equipment. The ultrasound transmitter TX is emitting ultrasound waves into sensor ambient space continuously. These waves are reflecting from various objects and are reaching ultrasound receiver RX. There is a constant interference figure if no moving objects are in the placement.any moving object changes the level and phase of the reflected signal, which modifies the summed received signal level. CAN is a multi-master serial bus that broadcast messages to all nodes in the network system. The CAN system offers a transmission speed of up to 1 Mbit/s with reliable and error detection method for effective transmission.can uses carrier sense multiple access protocol with collision detection (CSMA/CD) and arbitration on message priority as its communication protocol [C. Han,2012]. This communication protocol allows every node in CAN to monitor the bus network in advance before attempting to transmit a message. When no activity occurs in the network, each node has the same opportunity to transmit a message. Additionally, this communication protocol allows collision to be solved using bit-wise arbitration, based on a pre-programmed priority of each message in the identifier field of a message. DEMO POINTS Here Ultrasonic sensor detecting obstacles within 30 cm is employed, but in real time application ultrasonic sensors can detect obstacle across distances, measured in meters. Here 2 wheel robot is used as a vehicle. GPS is used to measure the location of the vehicle. ADVANTAGES Accidents can be reduced. Traffic jam will be reduced. CONCLUSION & FUTURE SCOPE

The data set of commuting trips gathered during this experiment was examined in terms of overall commuting time and opportunity for ACC or CACC use, as measured by the number of events when the motor was travelling at different speeds. Most of the baseline following events that were collected during this study were relatively short, with the mean speeds during the events ranging from just over 60-90 mph (the cut-off for this analysis) up to freeway cruising speeds. In future, the system can be improved and reduce the cost of the implementation. REFERENCES 1. Q. Wang, S. Leng, H. Fu, and Y. Zhang (Jun. 2012), An IEEE 802.11p -based multichannel MAC scheme with channel coordination for vehicular ad hoc networks, IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 449 458. 2. C. Han, M. Dianati, R. Tafazolli, R. Kernchen, and X. Shen (Jun. 2012), Analytical study of the IEEE 802.11p MAC sublayer in vehicular networks, IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 873 886. 3. V. Milanés, J. Villagrá, J. Godoy, J. Simó, J. Pérez, and E. Onieva (Mar. 2012), An intelligent V2I-based traffic management system,ieee Trans. Intell. Transp. Syst., vol. 13, no. 1, pp. 49 58. 4. V. Milanés, J. Alonso, L. Bouraoui, and J. Ploeg (Mar. 2012), Cooperative maneuvering in close environments, IEEE Trans. Intell. Transp. Syst., vol. 12, no. 1, pp. 15 24 5. L. Xiao and F. Gao (Dec. 2011), Practical string stability of platoon of adaptive cruise control vehicles, IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1184 1194 6. S. Moona, I. Moon, and K. Yi (Apr. 2001), Design, tuning, and evaluation of a full range adaptive cruise control system with collision avoidance, Control Eng. Pract., vol. 17, no. 4, pp. 442 455 7. J. Ploeg, B. T. M. Scheepers, E. van Nunen, N. van de Wouw, and H. Nijmeijer (Oct. 2011), Design and experimental evaluation of cooperative adaptive cruise control, in Proc. IEEE Conf. Intell. Transp. Syst., Washington, DC, pp. 260 265

8. S. C. Calvert, T. H. A. van den Broek, and M. van Noort (Oct. 2011), Modeling cooperative driving in congestion shockwaves on a freeway network, in Proc. IEEE Conf. Intell. Transp. Syst., Washington, DC, pp. 614 619. 9. C. Desjardins and B. Chaib-draa (Dec. 2011), Cooperative adaptive cruise control: A reinforcement learning approach, IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1248 1260. 10. vannunen, M. R. Kwakkernaat, J. Ploeg, and B. D. Netten (Sep. 2012), Cooperative competition for future mobility, IEEE Trans. Intell. Transp. Syst., vol. 13, no. 3, pp. 1018 1025 11. Naus, R. Vugts, J. Ploeg, R. van de Molengraft, and M. Steinbuch (Nov. 2010), String-stable CACC design and experimental validation: A frequency domain approach, IEEE Trans. Veh. Technol., vol. 59, no. 9, pp. 4268 4279. 12. Kural (2006), Adaptive cruise control design, M.S. thesis, Dept. Mech. Eng., Istanbul Tech. Univ., Istanbul, Turkey.