International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 13, December 2018, pp. 578 585, Article ID: IJMET_09_13_060 Available online at http://www.iaeme.com/ijmet/issues.asp?jtype=ijmet&vtype=9&itype=13 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 IAEME Publication Scopus Indexed ADAPTIVE CRUISE CONTROL AND COOPERATIVE CRUISE CONTROL IN REAL LIFE TRAFFIC SITUATION Ravikumar C V, Venugopal P, Jagannadha Naidu K and Satheesh Kumar S School of Electronics Engineering, VIT, Vellore, Tamilnadu, India Srinivas Koppu School of Information Technology and Engineering, VIT, Vellore, India ABSTRACT In today scenario driver assistance systems such as adaptive cruise control play an important role not only in avoiding accidents but also regulating traffic. The traditional Adaptive cruise control (ACC) system have been added vehicle to vehicle (V2V) communication which enables to transfer speed, acceleration, sensor which plays a key role in the Cooperative adaptive cruise control. The ACC system compared to the CACC system lacks string stability, which is an important factor for smooth transition between states. This paper describes the key features of the ACC system with the advantages of the CACC system. Also we have analyzed the modern predictive control of the ACC system which is an important factor for fuel saving. Keywords: Autonomous vehicle, adaptive cruise control, Traffic, Gap-Registration, Gap-closing, Perception. Cite this Article: Ravikumar C V, Venugopal P, Jagannadha Naidu K, Satheesh Kumar S and Srinivas Koppu, Adaptive Cruise Control and Cooperative Cruise Control in Real Life Traffic Situation, International Journal of Mechanical Engineering and Technology, 9(13), 2018, pp. 578 585. http://www.iaeme.com/ijmet/issues.asp?jtype=ijmet&vtype=9&itype=13 1. INTRODUCTION This paper talks about the Cooperative Adaptive Cruise Control. The ability of car to detect the presence of traffic and adjust the speed would help in reducing the traffic flow. The Adaptive Cruise Control has the ability to reduce the speed when a car or obstacle is detected. The adaptive cruise control with wireless communication between cars leads to Cooperative Adaptive-Cruise Control. In the recent years significant developments have been made in area of Advanced Driver Assistance Systems (ADAS).Vehicle to Vehicle communication plays an important role for this is particular advancement. http://www.iaeme.com/ijmet/index.asp 578 editor@iaeme.com
Adaptive Cruise Control and Cooperative Cruise Control in Real Life Traffic Situation 2. ADAPTIVE CRUISE CONTROL It is also called as autonomous cruise control is advance version of the cruise control system that automatically adjust the speed of the car in order to maintain safe-distance with the preceding car. The speed control part is based on the information from the sensor [1]. The sensor used can be LIDAR/RADAR.As the sensor detect an obstacle in front of the device it sends the information to the controller and will be used to reduce the speed of the car [2]. If the vehicle in the front slows down, the host car also slows down and controls the clearance between ACC vehicle and forward vehicle. If the car detects no vehicle in front it then the ACC car will accelerate till the set cruise control speed. The speed of the vehicle is controlled via engine throttle control and limited brake operation [3-4]. Figure 1 Basic representation of Adaptive Cruise control system. The Cooperative Adaptive-Cruise Control (CACC) system is a next upgrade/extension of Adaptive cruise control(acc) system. The CACC system uses the forward vehicle data such as speed or acceleration along with the data of the feedback loop which uses the LIDAR or the RADAR information (used to drive the distance/ range of vehicle in front of it). The ACC system similar to human driver does not exhibit string stability. Thus the oscillation introduced by braking and deceleration will be amplified. Which will lead to phantom traffic jam? The cooperative cruise control system varies from the ACC system as it obtain the speed information of the preceding vehicle. The CACC system utilizes the vehicle to vehicle communication so, it has information not just on the vehicle immediately on front of it but also the data of the vehicles leading it. 3. CONTROL ARCHITECTURE The control architecture consists of 3 phases: perception, planning and actuation. 3.1. Perception Phase The phase in which the sensor receives the information from the surrounding. The data to be sensed is distance, speed and acceleration of the preceding vehicle. This also includes detection of vehicle. The on-board sensors are also used such as the odometer and accelerometer. 3.2. Planning The planning stage is where it decides to switch between modes. There are 2 modes for the ACC system to control which is the speed-control mode and the spacing-control mode. In the speed control mode the vehicles speed needs to be controlled as the preceding vehicles speed http://www.iaeme.com/ijmet/index.asp 579 editor@iaeme.com
Ravikumar C V, Venugopal P, Jagannadha Naidu K, Satheesh Kumar S and Srinivas Koppu reduces and in the spacing control mode it maintain the set gap between in the preceding vehicle. The switching between the modes is decided by the controller. 3.3. Atuation Based on the decision made by the controller the actuation part controls the throttle and the brake. The acceleration is increased if the preceding vehicle is not present in front and decreased to maintain a safe gap between the preceding vehicles. Figure 2 Control Architecture 4. CONTROL DESIGN The CACC systems goal is to maintain the driver desired time gap between preceding vehicle and host vehicle in traffic conditions with accuracy and smoothness. The CACC is controller is managed by the ACC driver. The ACC system is used for developing the CACC system. The system will include option for increasing and decreasing the cruise control system as well as setting the gap. The shortest time gap taken is 0.6 sec and is based on separation estimations required to avoid the crash in case of emergency situations. The controller has two stages where the first stage is activated during CACC mode and vehicles are present in front of it. For the 2nd stage the gap closing controller needs to be smooth so that there is smooth transition to the gap regulation controller. When the vehicle joins the vehicle in front, the second stage controller will implement the vehicle following path depends on the gap setting which is set by the driver. 4.1. Gap Regulation Controller The gap regulation control is switched on when the vehicle is close enough. The ACC system reduces the gap error between the host vehicle and the vehicle in front of it. The LIDAR information is required to reduce the error gap between the required relative distance & time gap. When we exchange the information between the vehicles wirelessly this allows in improving the vehicles response and reduces the time gap. String stability is the main goal in the CACC system. 4.2. Gap-Closing Controller The gap closing controller uses a simple equation which is based on the relative speed, distance between cars & deceleration when approaching a car. This can be set according to driver s preference. The ego-car s braking depends on the desired deceleration. Once the car detects a vehicle in front, the time gap changes sharply. As this instant the system/ controller switches from the gap regulation controller to the gap-closing controller. http://www.iaeme.com/ijmet/index.asp 580 editor@iaeme.com
Adaptive Cruise Control and Cooperative Cruise Control in Real Life Traffic Situation 5. SIMULATION RESULTS 5.1. Step Response for Acceleration Cycle of the Vehicle System The acceleration cycle of the vehicle system is given by ( ) (1) k is the gain constant, ωn is the natural frequency and ϴ is the damping factor of the system. The step response of a system is the response of a system for and when a step function is given as the input to it. In the above equation the step input is provided with a delayed timing of Td. For acceleration the parameter values considered were, k = 0.156 (as it is acceleration k is positive), ωn = 0.661, ϴ = 0.396, Td = 0.146. Figure 3 The response for accelerating maneuver Though the graph shown in figure.3 is ideally should settle as soon as the value of the amplitude reaches 1, but as we can observe this is not the case. A more pragmatic result is that the response goes high to a certain peak before it settles down to the final value. This is called the peak overshoot. The response takes certain time to settle and is called the settling time which is approximately 20 seconds in our case. The transfer function (tf equation) for representing the behavior of the vehicle was chosen to show the tradeoffs between simplicity and goodness in fit which is Over 95 %. The response for both the models to speed changes are shown the below figures. It include both the low - level controller & dynamics of the vehicle which is in responsible for throttle and brake actions. Table 1 Design parameters K ϴ ωn Td Accelerating 0.156.661.396.146 Braking 1.136.5 1.067 0.287 The transfer function have been plotted using MATLAB for both acceleration and deceleration http://www.iaeme.com/ijmet/index.asp 581 editor@iaeme.com
Ravikumar C V, Venugopal P, Jagannadha Naidu K, Satheesh Kumar S and Srinivas Koppu 5.2. Model Predictive Control Model Predictive Control (MPC) is a controlled technique for multivariable control problems. The controlled variables or CVs re the output variables in In MPC applications while manipulated variables or MVs are called the input variables. The feed forward variables are also called the measured disturbance variables / DVs. 5.3. Advantages of MPC Figure 4 The response for braking maneuver The dynamic and static interactions between the DV, input& output are captured by the process model. Inputs and outputs Constraints are captured in a systematic manner. The calculations of the optimum set can be coordinated or synchronized by controlled calculations. Early warnings of potential problems can be mitigated and predicted using accurate models. Figure 5 Model Predictive Control block diagram. 5.4. Adaptive Cruise-Control System The Adaptive Cruise Control (ACC) system is equipped with sensor (Radar) which is used to measure the distance from the host car to the preceding car in the same lane, also it measures the relative-velocity of the preceding car. There are two modes of operation for the Adaptive Cruise Control system: http://www.iaeme.com/ijmet/index.asp 582 editor@iaeme.com
Adaptive Cruise Control and Cooperative Cruise Control in Real Life Traffic Situation Speed-Control: The Host car is made to travel in the driver set speed. Spacing-Control: Safe distance is maintained between the host car and the preceding car. The ACC system decides mode of operation. Figure 6 Spacing between vehicles. If the distance between the preceding car & the host car is faraway, then it will be in speed control and if the distance between the preceding car & the host car is less than the safe distance then it switches from speed control to spacing control, where it maintains safe distance between the host car and lead car. The parameters passed to the Adaptive Cruise-Control system is Host car velocity Set velocity(by Driver) Actual distance from the preceding car Velocity of the preceding car 5.5. Design Of Lead Car & Host Car Figure 7 Simulation diagram of the controller Figure 8 Acceleration plot http://www.iaeme.com/ijmet/index.asp 583 editor@iaeme.com
Ravikumar C V, Venugopal P, Jagannadha Naidu K, Satheesh Kumar S and Srinivas Koppu Figure 9 Velocity plot Figure 10 Distance between host and lead car plot Figure 11 Spacing error plot When the system is turned on, as the Host car is far away from the preceding car (Lead car), the host car will accelerate to reach the driver set velocity at full throttle in the first three seconds. But the Lead car accelerates slowly, so Host car accelerates with much slow rate so that the safe distance is maintained between the host car and Lead car from 3 to 13 seconds. As shown in fig. 9 the Host car maintains the velocity set by the driver From 13 to 25 seconds. However the spacing error starts moving to 0 after 20 seconds as the lead car reduces its speed. As the Lead car slows down and accelerates again from 25 to 45 seconds, the Hostcar keeps a distance from the preceding car. This is shown in the above plots. The spacing error is above 0 from 45 to 56 seconds. The host car reaches the speed set by the driver. The sequence repeats for 56 to 76 seconds, as from 25 to 25. 6. CONCLUSION This paper has presented a design of an adaptive cruise control and how the vehicle to vehicle communication can bring a great difference in improving the ACC system. The ACC system responses were implemented in MATLAB and its comparative study was carried out. The Cooperative adaptive cruise control system takes the added advantage of wireless communication and we can see a significant reduction in the inter-vehicle gaps. The Adaptive cruise control system is needs to be further studied and implemented with the capabilities of the CACC system. REFERENCE [1] Vicente Milanese, Steven E. Shladover, John Spring, Christopher Nowakowski,Hiroshi Kawazoe, and Masahide Nakamura, (2013) Cooperative Adaptive Cruise Control in Real Traffic Situations, IEEE Transactions On Intelligent Transportation Systems, 15(1), 296-305. [2] Moser, D., Schmied, R., Waschl, H., & del Re, L. (2018). Flexible spacing adaptive cruise control using stochastic model predictive control. IEEE Transactions on Control Systems Technology, 26(1), 114-127 http://www.iaeme.com/ijmet/index.asp 584 editor@iaeme.com
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