Monday, 7 April 2014

RANJITH KUMAR , BATRODY HOUSE



































Cooperative Adaptive Cruise Control



VISVESVARAYA TECHNOLOGICAL UNIVERSITY
JnanaSangama, Belgaum-590018

                                                                                
A SEMINAR REPORT
                                                                        ON                                                 
“Cooperative Adaptive Cruise Control”

Submitted in partial fulfilment of the requirements for the award of the degree of
BACHELOR OF ENGINEERING
IN
ELECTRONICS AND COMMUNICATION
Submitted by
            Ranjith Kumar                                                                4CB10EC064


                                        
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
CANARA ENGINEERING COLLEGE
BENJANAPADAVU, MANGALORE -574219
2013-2014




CANARA ENGINEERING COLLEGE
BENJANAPADAVU, MANGALORE – 574219
Department of Electronics & Communication Engineering


CERTIFICATE

Certified that the seminar entitled Cooperative Adaptive Cruise Control is a bonafide work carried out by Ranjith Kumar           with USN 4CB10EC064 in partial fulfilment for the award of  Bachelor of Engineering in Electronics and Communication of the Visvesaraya Technological University, Belgaum during the year 2013-2014.  It is certified that all corrections/suggestions indicated for Assessment have been incorporated in the report. The seminar report has been approved as it satisfies the academic requirements in respect of seminar prescribed for the said Degree.





                                                                       



Cooperative Adaptive Cruise Control

 ABSTRACT
A real-time on-road vehicle tracking method is presented in this work. In recent years many studies on intelligent vehicles have been devoted to solve problems such as driver burden reduction, accident prevention, traffic flow smoothening. Every minute, on average, at least one person dies in a crash. Mentally, driving is a highly demanding activity - a driver must maintain a high level of concentration for long periods and be ready to react within a split second to changing situations. Cooperative Adaptive Cruise control (CACC) system has been developed to assist the driver for driving long distances on highways. Cruise control can perform only velocity control.
The Cooperative Adaptive Cruise Control system (CACC) attempts to maintain a constant forward vehicle speed, as specified by the driver. In addition, using a combination of forward radar and camera sensors, CACC detects when another vehicle (called the target vehicle) is in its forward path and adjusts its own speed via throttle and braking control to maintain a safe following distance behind it. The vehicle also receives GPS information (location, speed, and direction) from vehicles ahead of it, and broadcasts GPS information to vehicles behind it. This additional information can be used to set up a platoon of vehicles that follow a lead vehicle, with safe spacing between each vehicle. Each vehicle in the platoon uses a combination of GPS information from vehicles in front of it, together with information from its own radar and vision sensors, to control its throttle and brakes to achieve a safe following distance. In turn, each vehicle broadcasts its own GPS information to vehicles behind it.
Cooperative Adaptive Cruise Control (CACC) system, for which a respective model is shown in Figure 1 below. The CACC system is an embedded control system for automobiles which automatically monitors and adjusts a vehicle speed according to the traffic conditions in its immediate vicinity.In CACC mode, the preceding vehicles can communicate actively with the following vehicles so that their speed can be coordinated with each other.








                                                                                                                                                             

TABLE OF CONTENTS
                                                                                                                                     PAGE NO.
LIST OF FIGURES                                                                                                         iii
CHAPTER 1: INTRODUCTION                                                                   1
CHAPTER 2: ADAPTIVE CRUISE CONTROL                                          3
CHAPTER 3: PROPOSED SOLUTION                                                 5
                     3.1Cooperative adoptive cruise control 
                        3.2 Dedicated short range communication (DSRC)
                        3.3 Vehicle to Vehicle (V2V)
                     3.4 Wireless access in vehicular environment (WAVE)
CHAPTER 4: CACC INSTALLED TO NISSAN   FX45 VEHICLE              7
                        4.1 Working
CHAPTER 5: CACC CONTROLLER DESIGN                                              9
                     5.1 State Machine of the CACC Controller
                        5.2 Design of the Gap Closing Controller
CHAPTER 6: EXPERIMENTAL RESULTS                                                   11
CONCLUSION                                                                                                18
REFERENCES                                                                                                 19







                                                                                                                                                                                                
LIST OF FIGURES
Fig 2.1.1(a) Doppler Effect.
Fig 2.1.1(b) Doppler Effect.
Fig 3.1 Cooperative adoptive cruise control.
Fig 4.1 CACC Configured to FX45.
Fig 4.2 Preceding vehicle Configuration.
Fig.4.3 Following vehicle Configuration.
Fig 5.1 State machine for the prototype CACC Controller.
Fig 6.1 Proving Ground Test: Steady State Performance.
Fig 6.2 Preceding Car Braking While Following Car is approaching
Fig 6.3 Preceding Car Brakes and Accelerates repeatedly
Fig 6.4 Brake Pressure Percentage when preceding vehicle brakes and accelerates repeatedly.
Fig 6.5 Three Car Platoon Test
Fig 6.6 Public Highway Testing Result










                                                                                                                                                                









                              
                          

 CHAPTER 1
INTRODUCTION
 Adaptive cruise control (ACC) systems are now commercially available on high-end vehicles. Compared with conventional cruise control (CC) systems which regulate vehicle speed only, An ACC system  allows drivers to maintain a desired cruise speed if there is no preceding vehicle as well as a desired following gap with respect to a preceding vehicle. The ACC system senses the range and range rate to the preceding vehicle with a radar or LIDAR sensor. Such information is used to generate appropriate throttle or brake command to maintain a pre-set following gap to the preceding vehicle. With the development of wireless communication technology such as Dedicated Short Range Communication (DSRC), a vehicle can exchange information with its surrounding vehicles through vehicle-to-vehicle communication. As an enhancement to ACC systems, a cooperative adaptive cruise control (CACC) system further incorporates vehicle-to-vehicle communication to make use of rich preview information about the preceding vehicle. Previous research has shown that CACC systems could achieve tighter following gaps, more smooth and “natural” ride in comparison to ACC systems. Other benefits of CACC technology include improvement of traffic safety and traffic efficiency.
                  ACC systems have been studied extensively from highway speed to stop-&-go. An extensive review can be found in a CACC system design and test results are presented. Instead of local range sensors, Global Positioning System (GPS) is used to provide the positions of the preceding vehicle and the following vehicle; upon receiving the positions of the preceding vehicle through vehicle-to-vehicle communication, the following vehicle computes relative positions for ACC control. However, GPS problems such as signal blockage or multipath may cause performance degradation, especially around urban areas. Model predictive control (MPC) is a control framework which can optimize performance criterion under multiple design constraints. The formulation of MPC usually results in a constrained optimization problem which can be solved by various solvers. Due to its complexity of computation, MPC used to be applied on chemical process control where plant dynamics is slow and real-time computation requirement is not that stringent. With computer getting cheaper and more powerful, MPC has extended its applications to other fields such as vehicle control. MPC has been employed to develop ACC systems.
The CACC system described in this paper is developed under a California PATH research project on methods for mitigating congestion via the application of Intelligent Transportation Systems (ITS). The primary focus of this project is a human factor study on driver experiences of different time gaps, especially relatively short time gaps, with CACC systems in live traffic. Since CACC systems are not commercially available yet, two Infinity FX45s that are equipped with ACC systems are retrofitted with the CACC system designed by California PATH. The factory installed ACC system has three relatively long time gap settings, 2.2, 1.5 and 1.1 second time headway, which are not sufficient for the proposed human factor study. Therefore, the objective of CACC system design is to enable shorter time gap settings from 0.6 s to 1.1 s under live traffic on public road for the purpose of the human factor study. Hence, this paper is not intended to provide solutions for a generic CACC design; instead, it aims to describe how we formulate a real-world application with multiple constraints into a control problem and presents the successful field testing at both vehicle proving ground and public highway.
This paper is organized as follows: Section II describes CACC system setup retrofitted on the two Infinity FX45s; Section III details CACC controller design including design challenges, the controller structure, and the time-gap regulation controller based on the indirect adaptive MPC; Section IV presents experimental results from field testing at NISSAN Arizona vehicle proving ground and public highway around San Francisco, CA.





***













CHAPTER 2
ADAPTIVE CRUISE CONTROL

2.1 THE PRINCIPLE OF ADAPTIVE CRUISE CONTROL
As already mentioned each car with ACC have a micro wave radar unit fixed in front of it to determine the distance and  relative speed  of any vehicle in it’s path. The principle behind the working of this type of radar is- the Doppler Effect.
2.1.1 Doppler Effect:
  Doppler Effect is the change in frequency of the waves when there is a relative motion between the transmitting and receiving units. The two figures below clearly show the Doppler Effect.
1.     Higher  Pitch Sound
2
Fig 2.1.1(a) Doppler effect
In this case the vehicle is speeding towards the stationary listener. The distance between the listener and the car is decreasing. Then the listener will hear a higher pitch sound from the car, which means the frequency of sound, is increased.

2. Lower pitch sound
3
Fig 2.1.1(b) Doppler effect
In this case the vehicle is moving away from the listener. The distance between and the car is increasing. Then the listener will hear a lower pitch sound from the car, which means the frequency of sound, is decreased. So that is the Doppler Effect in case of sound waves.
2.2 Working
Similarly the radar unit in ACC will be continuously transmitting radio waves. They will be reflected and echo singles (reflected waves) will be having the same frequency or different frequency depending on speed/position of the object due to which the echo singles originate. If the echoes singles have the same frequency it is clear that there is no relative motion between the transmitting and receiving ends. If the frequency is increased it is clear that the distance between the two is decreasing and if the frequency is decreased it means that the distance is increasing.
The embedded system is connected to the radar unit and its output will be sent to breaking and accelerating unit as early mentioned the embedded system is a device controlled by instructions stored in a chip. So we can design the chip or ACC having an algorithm such that it will give output only when the input signals are less than the corresponding safe distance value. So only when the between the car and the object  in front of it is less then the same distance value the embedded system will give output to the breaking and the accelerating units. Thus the safe distance will be kept always. That’s how the ACC works.
CHAPTER 3
PROPOSED SOLUTION
3.1    Cooperative adoptive cruise control

Fig 3.1 Cooperative adoptive cruise control
CACC realises longitudinal automated vehicle control. In addition to the feedback loop used in the ACC, which uses Radar or LIDAR measurements to derive the range to the vehicle in front, the preceding vehicle's acceleration is used in a feed-forward loop. The preceding vehicle's acceleration is obtained from the Cooperative Awareness Messages it transmits using DSRC or WAVE technology (IEEE 802.11p). Generally, these messages are transmitted several times per second by future vehicles equipped with ITS capabilities.




3.2 Dedicated short range communication (DSRC)
Dedicated short-range communications were one-way or two-way short- to medium-range wireless communication channels specifically designed for automotive use and a corresponding set of protocols and standards.
In October 1999, the United States Federal Communications Commission (FCC) allocated 75MHz of spectrum in the 5.9GHz band to be used by Intelligent Transportation Systems In August 2008 the European Telecommunications Standards Institute (ETSI) allocated 30 MHz of spectrum in the 5.9GHz band for ITS.

3.3 Vehicle to Vehicle (V2V)
Vehicular Communication Systems are an emerging type of networks in which vehicles and roadside units are the communicating nodes providing each other with information, such as safety warnings and traffic information. As a cooperative approach, vehicular communication systems can be more effective in avoiding accidents and traffic congestions than if each vehicle tries to solve these problems individually.
V2V (short for vehicle to vehicle) is an automobile technology designed to allow automobiles to "talk" to each other. The systems will use a region of the 5.9 GHz band set. V2V is also known as VANETs (Vehicular Ad Hoc Networks). It is a variation of MANETs (Mobile Ad Hoc Networks), with the emphasis being now the node is the vehicular

3.4 Wireless access in vehicular environment (WAVE).
IEEE 802.11p is an approved amendment to the IEEE 802.11 standard to add wireless access in vehicular environments (WAVE), a vehicular communication system. It defines enhancements to 802.11 (the basis of products marketed as Wi-Fi) required to support Intelligent Transportation Systems (ITS) applications. This includes data exchange between high-speed vehicles and between the vehicles and the roadside infrastructure in the licensed ITS band of 5.9 GHz (5.85-5.925 GHz). IEEE 1609 is a higher layer standard based on the IEEE 802.11p.



CHAPTER 4
CACC installed to NISSAN   FX45 vehicle
4.1 Working
The CACC system designed by PATH consists of two Infinity FX45s, as shown in Fig.1. One FX45, driven by a PATH staff, serves as the CACC preceding vehicle, while the other serves as the CACC following vehicle which is driven by test subjects during this human factor study. Both FX45s are equipped with factory installed ACC systems, which use LIDAR to detect vehicles in front and measure relative distance and speed. All the vehicle information such as vehicle speed, engine/transmission state, brake state, and LIDAR measurements can be accessed through vehicle CAN bus. The CACC system designed by PATH is essentially an add-on system retrofitted on the two FX45s.

Fig 4.1 CACC Configured to FX45
A PC104 computer is installed to interface with vehicle CAN bus. A DSRC Wave Radio Module (WRM) supplied by DENSO is used to broadcast the state information of the preceding vehicle, such as vehicle speed, throttle percentage, brake percentage, gear position, and engine speed etc.
Fig 4.2 Preceding vehicle Configuration


Fig.4.3 Following vehicle Configuration.
A (PATH) PC104 computer which hosts the CACC control receives the information of the preceding vehicle from the DSRC WRM and accesses the information of the following vehicle through its CAN bus. In order to control the time gap between the following vehicle and the preceding vehicle, it is necessary for the PC104 computer to actuate the engine and brake system of the following vehicle. Ideally, direct access to the engine and brake system will provide more freedom for the CACC controller design. However, actuating engine/brake directly would involve extensive modifications to the existing vehicle hardware and software, which is not preferred under this project.
Also shown in Fig.4.3 is the factory installed ACC system. Its LIDAR sensor sends the relative distance and speed of the preceding vehicle to the NISSAN ACC controller through the CAN bus (dashed line in the figure). A simple way for implementing the cooperative vehicle longitudinal control is that the prototype CACC controller intercepts the LIDAR sensor measurement information and sends out its own virtual relative distance and speed commands to the NISSAN ACC controller instead. For example, if the following vehicle follows the preceding vehicle at exactly the set time gap, a virtual relative distance command that is smaller than current LIDAR measurement will increase the actual time gap between the preceding vehicle and following vehicle. Although this includes the existing NISSAN ACC controller in the CACC control loop and poses additional difficulties for the CACC controller design, it requires minimal modifications to the existing NISSAN ECU firmware and was therefore adopted in the system design.
CHAPTER 5
CACC Controller Design
The design objectives of the CACC controller are to maintain the time gap (i.e. from 0.6 s to 1.1s) set by driver under all traffic conditions and to provide riding comfort at least comparable to manual driving. There are several difficulties inherent in the design of the CACC controller. First of all, the controller does not have direct access to vehicle’s engine and brake system. This greatly limits the freedom of the controller design. Second, the control loop has to include NISSAN’s ACC controller, which we know little about and is hard to identify. Finally, the braking capability that can be actuated is limited to 0.3g by the NISSAN system.
5.1 State Machine of the CACC Controller
Fig 5.1 state machine for the prototype CACC Controller.
Fig.5.1 illustrates the state machine for the prototype CACC Controller. When the vehicle in front of the following vehicle is not the CACC preceding vehicle with wireless communication, the LIDAR sensor measurements will be forwarded to the NISSAN ACC controller directly and the function of factory installed ACC system will be restored. Whenever the CACC preceding vehicle is identified as the vehicle directly in front, the controller enters the CACC mode. The function of target identification mode is to identify if the target detected by the ACC LIDAR is the CACC preceding vehicle with wireless communication. This problem would be much more complicated if there are multiple vehicles with DSRC wireless communication around. Since there are only two DSRC equipped vehicles during our testing, a simple method is adopted for the target identification purpose. Experimental results show that the relative speed from the LIDAR sensor has about 0.5 s delay compared with vehicle speed from DSRC communication when the CACC preceding vehicle is in front of the following vehicle directly. This characteristic is used by the simple method to confirm the target identity.
5.2 Design of the Gap Closing Controller
When the relative distance between two vehicles is much larger than the desired time gap, controller saturation will occur if a high-gain CACC gap regulation controller is engaged immediately. Such controller saturation induces oscillating responses which make the driver uncomfortable. One way to resolve this problem is to introduce controller switching. A CACC gap closing controller will be engaged before the relative distance reaches a predetermined threshold value. The CACC gap closing controller is a “semi” open loop controller.










CHAPTER 6
 EXPERIMENTAL RESULTS
To fine tune the control design and controller parameters, two testing trips were made to the Nissan’s vehicle proving ground in Arizona. At the end of the second field trip, a series of scenarios was performed to test the performance of the final controller.
Fig.6.1 shows a scenario when the following car was approaching the preceding car and the time gap setting was changed from 1.1 s to 0.9 s. Both the actual time gap and the speed show that, under the control of the CACC controller, the following car approached the preceding car smoothly and the time gap was then well regulated at 0.9 s.
Fig.6.2 shows a scenario when the preceding car braked at about 0.16 g while the following car was approaching. With the feed-forward information (including the brake and throttle of the preceding vehicle) from the wireless communication, the CACC controller reacted very quickly. Therefore, the following car responded to the speed change of the preceding car quickly and regulated the time gap at the desired time gap setting in the gap regulation mode.
To further illustrate the advantages of the feed-forward information from wireless communication, Fig.6.3 shows a scenario when the preceding car repeatedly made braking and acceleration transitions. The largest magnitude of braking is around 0.25 g, which is close to the maximum capability of the brake actuator (0.3g). As shown in Fig. 6.3, the following car was always able to track the preceding vehicle’s speed, even with this aggressive braking and acceleration. Fig.6.4 also show that the following vehicle braked almost immediately after the preceding car braked with the information provided via wireless communication.




 

Fig 6.1 Proving Ground Test: Steady State Performance









Fig 6.2 Preceding Car Braking While Following Car is approaching
As part of the performance testing, a three-car platoon was formed to test the string stability effect and compare the performance between the conventional ACC controller and the CACC controller. A manually driven Infiniti G35 led the platoon and the preceding Infiniti FX45 followed it with the factory ACC controller turned on. The following Infiniti FX45 followed the preceding FX45 with the CACC controller turned on. The lead G35 made aggressive braking and acceleration repeatedly. As shown in Fig. 6.5, the ACC equipped preceding FX45 tracked the lead G35’s speed with a much larger time lag compared with the CACC equipped following FX45’s tracking performance. Therefore, the ACC equipped preceding FX45 exhibited a much larger variation in time gap regulation as well. More importantly, the amplification of the time gap variations for the conventional ACC shows a potential loss of string stability, which is compensated successfully by the CACC’s enhanced vehicle following capability.
Fig 6.3 Preceding Car Brakes and Accelerates repeatedly







Fig 6.4 Brake Pressure Percentage when preceding vehicle brakes and accelerates repeatedly
Fig. 6.6 shows the testing result on a section of public highway in live traffic with the smallest gap setting of 0.6 s. Again, the CACC controller performed well and tracked the desired time gap setting with just a relatively small steady state error.






Fig 6.5 Three Car Platoon Test





Fig 6.6 Public Highway Testing Result












CONCLUSION
This paper describes the design, implementation, and testing of a CACC system on two Infiniti FX-45 vehicles that were provided by Nissan Motor Company. The CACC system has been developed by adding a wireless vehicle-vehicle communication system and new control logic to an existing commercially available ACC system. The CACC is intended to extend the vehicle-following capabilities of ACC to provide drivers with vehicle-following time gaps shorter than those provided by commercial ACC systems. A CACC controller structure is proposed and a gap regulation controller is designed based on the indirect adaptive MPC. The gap regulation controller utilizes additional information from the DSRC wireless communication for the enhanced following performance. Extensive field testing was conducted on both vehicle proving ground and public highway. Testing results show consistent performance under different scenarios and demonstrate its advantages over the conventional ACC system. The enhanced performance makes it possible for the CACC equipped vehicle to operate at time gaps between 0.6 s
 and 1.1 s, compared to a range of 1.1 s to 2.2 s with the ACC system; these shorter CACC time gaps could enable significant increases in highway capacity. The currently on-going human factor study with the CACC system will provide insights on drivers’ experiences with different time gaps, especially those shorter time gaps.

Submitted by:
RANJITH KUMAR
Batrody House,
Allipade post, Bantwal Taluk,
Dakshina Kannada,
Karnataka-574211
INDIA.
Cell: +91 8861496020
Email: ranjithbatrody@gmail.com




REFERENCES
[1] Ministry of Transport, Public Works and Water Management, Nota Mobiliteit; Naar een betrouwbare en voorspelbare bereikbaarheid, 2004, TheHague. (in Dutch).
[2] European Commission, Final Report of the eSafety Working Group on Road Safety, Nov. 2002, Brussels, Belgium: EC DG IST.
 [3] Q. Wang, S. Leng, H. Fu, and Y. Zhang, “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, Jun. 2012.
[4] G. Naus, J. Ploeg, R. van de Molengraft, and M. Steinbuch, "Explicit  MPC design and performance-based tuning of an Adaptive Cruise  Control Stop-&-Go," in Intelligent Vehicles Symposium, 2008 IEEE,  2008, pp. 434-439.
[5] B. v. Arem, C. J. G. v. Driel, and R. Visser, "The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics," IEEE  Transactions on Intelligent Transportation Systems, vol. 7, pp.  429-436, 2006.
[6] A. Vahidi and A. Eskandarian, "Research advances in intelligent collision avoidance and adaptive cruise control," Intelligent Transportation Systems, IEEE Transactions on, vol. 4, pp. 143-153, 2003.
[7] D. d. Bruin, J. Kroon, R. v. Klaveren, and M. Nelisse, "Design and Test of a Cooperative Adaptive Cruise Control System," in IEEE Intelligent Vehicle Symposium, Parma, Italy, 2004, pp. 392-396.
[8] J. M. Maciejowski, Predictive Control with Constraints: Prentice Hall, 2002.
[9] S. Shladover, “Review of the state of development of advanced vehicle
control systems (AVCS),” Vehicle Syst. Dyn., vol. 24, pp. 551–595, July
1995.
[10]  R. French, Y. Noguchi, and K. Sakamoto, “International competitiveness
in IVHS: Europe, Japan, and the United States,” in Proc. 1994 Vehicle
Navigation and Information Systems Conf., Yokohama, Japan, July
1994, pp. 525–530.