# Adaptive Cruise Control (ACC)

Adaptive Cruise Control (ACC)

ELG 4152 Project

Group Memebers:

Mirza Abdel Jabbar Baig (3256498)

Mohammad Ali Akbari (3299852)

Navid Moazzami (3413826)

Hasan Ashrafuzzaman (3384661)

Reference



A Safe Longitudinal Control for Adaptive Cruise Control and Stop
-
and
-
Go Scenarios

Martinez, J.
-
J.; Canudas
-
de
-
Wit, C.; Volume 15,

Issue 2,

March 2007 Page(s):246

258



Modeling a Cruise Control

http://www.library.cmu.edu/ctms/ctms/examples/cruise/cc.htm



Highway Speed Controller

http://www.site.uottawa.ca/~misbah/elg4392/HC12CodeWarriorC/HighwaySpeedController/p
roject.c



W. Jones, “
Keeping cars from crashing,

IEEE Spectrum
, vol. 38, no.

9, pp. 40

45, Sep. 2001.

 M. A. Goodrich and E. R. Boer, “
Designing human
-
centered automation:

Tradeoffs in collision avoidance system design,

IEEE Trans. Intell.

Transp. Syst.
, vol. 1, no. 1, pp. 40

54, Mar. 2000.

Problem Statement

The main problem regarding the normal Cruise
Control technology is that it is not aware of
other vehicles’s movement

The driver must be always aware. Hence,
possibility of mistakes

Possibility of collision with the leading car if not
manually slowed down

Proposed Solution

Introduce Adaptive Cruise Control for
longitudinal control of the vehicle

Speed would be automatically adjusted for safe
inter
-
distance

Once safe inter
-
distance is reached, the speed
would return to the desired speed set by the
driver

Technical Objectives

To design a control system for ACC.

No overshoot

Settling Time of about 4
-
7 seconds.

No oscillation (because no overshoot)

-
state error of 0

Vehicle Characteristics

If the inertia of the wheels is neglected, and it is
assumed that friction (which is proportional to
the car's speed) is what is opposing the motion
of the car, then the problem is reduced to the
simple mass and damper system shown in the
next slide.

Vehicle Characteristics

System Block Diagram 

Controller Selection

Which kind of Controller is the best?

No controller.

P controller.

PI controller.

PID controller.

PD controller.

Controller Selection

P Controller

No Controller

Step Response
Time (sec)
Amplitude
0
20
40
60
80
100
120
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0.02
System: untitled1
Settling Time (sec): 76.7
Settling time = 76.7 s

Steady state error > 98%

Kp = 10000

Settling Time = 0.389s

Steady state error = 2%

Step Response
Time (sec)
Amplitude
0
0.1
0.2
0.3
0.4
0.5
0.6
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
System: untitled1
Settling Time (sec): 0.389
Controller Selection

Kp=800, Ki=40

Settling time = 4.89 s

Steady state error = 0

Step Response
Time (sec)
Amplitude
0
1
2
3
4
5
6
7
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
System: untitled1
Settling Time (sec): 4.89
PI Controller

*Final
choice is PI
Controller*

Distance Checking 

Three scenarios:

d
r >
d
0
, cruises at desired speed, ACC inactive

d
r

< d
c
, danger zone, ACC enables to slow down

d
0

< d
r

< d
0
, ACC is enable to reach safe inter
-
distance

Implementation of Distance
Checking 

The distance checking algorithm only requires a
minimum distance and a range.

The algorithm calculates the actual minimum
distance (> provided distance) and maximum
distance and then outputs the new speed of the
vehicle.

The user can also provide a maximum and
minimum speed for the vehicle.

Implementation of Distance
Checking

temp=(300*(speedmax
-
speedmin))/(12*range)

minimum_Distance=(minimum_Distance*32)/10

max_Distance = minimum_Distance + (3*range)

if (distance > (max_Distance))

speed = speedmax;

if (distance < minimum_Distance)

speed = 0;

if ((distance < max_Distance) and (distance>minimum_Distance))

if leader_speed > 0

speed = ((100*speedmin
-
(kvit*(minimum_distance))) + temp * distance)/100;

else

speed = ((100*speedmin+(kvit*(max_Distance))) + temp * distance)/100;

Simulation

Maximum follower vehicle speed = 100 m/s

Minimum follower vehicle speed = 0 m/s

Minimum distance = 40 m

Range = 20 m

Initial distance = 80 m

Kp = 800

Ki = 40

b = 50

m = 1000

The following parameters were used for the simulation:

Final Model (simplified)

Simulation

Yellow:

Distance between two vehicles

Blue:

Speed of the leader vehicle

Purple:

Speed of the follower vehicle

Limitations/Conclusion

Not a complete transfer function of the vehicle
and environment.

Linear distance
-
checking model.

No limitations on the acceleration and jerk.

Our model is simplified compared to real
-
time
models, but can be used to implement a practical
ACC.