Monday, 7 April 2014
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
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
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
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.
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