m. tech. project presentation automatic cruise control system by: rupesh sonu kakade 05323014 under...
Post on 31-Mar-2015
241 Views
Preview:
TRANSCRIPT
M. Tech. Project Presentation
Automatic Cruise Control System
By: Rupesh Sonu Kakade05323014
Under the guidance of
Prof. Kannan Moudgalya and
Prof. Krithi RamamrithamIndian Institute of Technology, Bombay
10 July 2007
Overview Introduction Objectives Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Introduction
Conventional Cruise Control
Difficulties:1. Useful only in sparsely populated roads
2. Disengagement may result in driver
loosing control of a car.
Velocitycontrol
Driver Set
Speed
Introduction
Automatic Cruise Control (ACC) System
Control Objectives:
1. Follow-the-leader car
2. Adapt to leader velocity
Introduction - ACC
Introduction - ACC
Safe Inter-vehicle distance Rule:1. Constant spacing policy – Safe distance is independent
of vehicle parameters such as maximal velocity, deceleration, etc.
Introduction - ACC
2. Constant time-gap policy:
Difficulties with ACC:
1. Federal and State laws prohibits the use of ACC system below
certain speed value.
2. Human driving often results in
excessive accelerations and
decelerations. Thus violating
comfort specifications.
Introduction
Stop-and-go scenario demands a different behavior from vehicles.
Control in stop-and-go scenarioControl Objectives:
1. Safety Constraint: Stop the vehicle before it reaches a critical distance, .
2. Comfort specification: Keep the
deceleration and jerk bounded.
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Objectives of Project
Design control systems for1. Speed control - in conventional cruise control
2. ACC controller
3. Controller for stop-and-go traffic
and4. Integrate controllers on
low-cost platform
Approach used
Zones:
1. Blue Zone: Cruise control
2. Green Zone: Automatic cruise control
3. Orange Zone: Stop-and-go traffic control
4. Red Zone: Safety critical zone
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Automatic Cruise Control
Control Objectives:
1. Follow-the-leader car, i.e., distance error should be minimal. Distance error is computed from
where,
2. Adapt to leader velocity, i.e., relative velocity between two vehicles should be minimal.
ACC Control Law: The first time-derivative of distance error is
computed and solved the following equation
which ensures the distance error reduces to zero. We have
ACC
The control structure is similar to PD controller with,
1. Proportional gain
2. Derivative gain
p
kk
h
1dk h
ACC Control Scheme
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Control during stop-and-go scenario
Control Objectives:1. Safety Constraint: Stop the vehicle before it reaches a
critical distance, . 2. Comfort specification: Keep the deceleration and jerk
values bounded for all t.
Reference model:Input: Lead vehicle velocity and
Output: Reference distance andreference acceleration
Control during stop-and-go scenario
Control during stop-and-go scenario
Reference model has twofold objectives:
1. Reference distance computation:
2. Reference acceleration computation:
Safety and comfort constraints
rd
Control during stop-and-go scenario
Objectives: To find constraints on c and so that safety and comfort specifications are satisfied for all initial conditions and .
Initial conditions are defined as
where t = 0 s, is the time when
Orange Zone is reached.
Solving and
Control during stop-and-go scenario
where =rfx
Control during stop-and-go scenario
Solving the previous expression, we have
The maximum penetration distance is
This gives us a lower bound on c
Control during stop-and-go scenario
Next we find upper bound on c. Substitute in expression for reference acceleration, i.e.,
The maximum value of reference
breaking is computed from
Control during stop-and-go scenario
Substitute in , we have
Control during stop-and-go scenario
Now we consider comfort specification, i.e., jerk values must also be bounded. This gives us another upper limit on value for c.
The maximum value of jerk is
believed to depend on extremes of
Control during stop-and-go scenario
The expression has two solutions.
i.e., estimated lead velocity assumed
to be zero. Therefore maximum value
of jerk could be computed from
Control during stop-and-go scenario
To proceed we assume
i. e., negative acceleration is always greater than positive acceleration.
The maximum jerk will be
bounded as
Control during stop-and-go scenario
Assuming sufficiently large for The previous expression
yields another upper bound on value for c.
C1 and c2 are associated with safety
Whereas c3 is associated with comfort
Control during stop-and-go scenario
In the Orange Zone, priority is given to safety, i.e.,
Next we determine the lower bound on the value of .We use the above expression together with
If takes the smallest value thenc takes on the largest value.
Control during stop-and-go scenario
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Results
We implemented ACC controller on Dexter-6C. This platform is relatively reach in a sense that it has
1. Independent steering controller
2. Independent drive controller
3. Independent controller for white line sensing Our objective was to implement control system on a
low cost platform, such as CDBOT.
The experimental results on CDBOT are also presented.
Results
Figure: Dexter-6C, a test car
Results - On Dexter-6C
Fig.: Speed control loop performance Fig.: Car-following (ACC) results
Results - On Dexter-6C
Fig.: Time-gap results
Results – On CDBOT Inner speed control loop performance test
ACC Results – On CDBOT
Results – On CDBOTControl in stop-and-go scenario
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Conclusion Different traffic densities is found to demand different
behavior from vehicles.
Controllers for longitudinal speed control of cars during sparsely populated road, moderate traffic, and stop-and-go scenarios are designed.
Controllers were integrated on robotic platform, CDBOT. Also ACC controller was implemented on Dexter-6C.
Overview Introduction Objectives of project Automatic Cruise Control (ACC) Control in stop-and-go traffic Results Conclusion Future Improvements
Future Improvements
1. ACC controller used PD structure. Due to its non
perfect tracking, jerk values are some times higher.
This aspect could be improved by using advanced
controller such as controller based on adaptive control
theory.
2. String (or platoon) stability problem is not analyzed
here.
top related