1. A FCW, CIB and DBS benefit estimation method developed in ACAT program
Hirofumi Aoki, Masami Aga, Yoshiki Miichi, Yoshiaki Matsuo, and Shin Tanaka
Toyota Motor Corporation
Thank you Mr. Fanke for introducing me.
I’m very grad to be here.
And I’m also very grad to live
near Washington DC for some years,
for I have many good memories in the United States.
Our company has an unpleasant memory though.
Today I would like to talk about
“A FCW, CIB and DBS benefit estimation method”.
The target system is mainly designed to help reduce
or mitigate rear-end collisions.
The estimation method had been developed a few years ago,
and we made some modifications applying it to our systems,
the concept has not changed.
I would like to present you
the essence of our method.

2. Developing Systems to Reduce/Mitigate Rear-end Collisions
Subaru
Toyota
Mercedes
Honda
As you all well aware,
various systems have appeared in the market
over the past several years.
The sensors to detect proceeding vehicles
vary
from system to system,
and their control strategy also vary
from system to system.
Volvo

3. CIB (Automated braking)
Control Sequence
Ordinary Driving
Collision
Time
Speed
DBS (Brake Assist)
FCW
CIB (Automated braking)
The full system has 3 functions shown here.
They are
FCW or collision warning,
DBS or brake assist,
CIB or automated braking.
[Click]
They work together
to provide collision mitigation
or collision avoidance.
Toyota’s objective in ACAT was to investigate
how these 3 functions affect on the system benefit.
However, it is not easy.
The objective in ACAT
FCW, DBS and CIB
specification
System
benefit

4. Drivers reaction to Benefit
Ordinary Driving
Collision
FCW
+ DBS
CIB
DBS (Brake Assist)
FCW
CIB (Automated braking)
Time
Speed
Imagine that the drivers show higher response to the warning,
[Click]
then FCW & DBS are beneficial and CIB’s role is small.

5. Drivers reaction to Benefit
Ordinary Driving
Collision
FCW
+ DBS
CIB
DBS (Brake Assist)
FCW
CIB (Automated braking)
Time
Speed
Imagine that the drivers show poorer response to the warning,
[Click]
then FCW & DBS are less effective and CIB’s role is larger.
It means that (Thus),
Each benefit significantly depends on
“how drivers react before collisions”.
So,
So…
Each benefit significantly depends on
“how drivers react before collisions”.

6. Driver behavior investigation
using the Driving Simulator
To measure such driver responses,
Toyota created rear-end collision scenarios in the driving simulator.
More than 100 ordinary drivers participated in the test.

7. Driving Simulator Test Example
Here, I will show you a driving simulator test example.
[Video]
Here, the warning was issued just before a collision.
The collision scenario was given just once for each participant.
After the tests, most of the drivers said
that was their first rear-end collision experience
and they were very astonished.
We consider that drivers act in the same manner
in actual rear-end collisions. 7

8. Driver Reaction Before Collisions
[m/s2]
Maximum
deceleration s s
60s - 10
(31 persons in total) 8 6 4 2
This chart shows the result.
Here, the X-axis indicates
the period from warning to braking onset,
and the Y-axis indicates the maximum deceleration.
It indicates
that the driver reaction varies from person to person,
And there’s poor relation between
the period from warning to braking onset
and the maximum deceleration.
It means
that both variables are considered to be independent.
0.0
1.0
2.0
[s]
Period from warning to braking onset

9. Rear-end Reconstruction Concept
How are rear-end collisions happening?
Traffic accidents are happening incidentally
Then, how are rear-end collisions happening in the real world?
[Click]
We hit upon an idea that the traffic accidents are happening incidentally. 9

10. Rear-end Collision Modeling
Rear-end collisions are happening by a combination of
Various brake trigger timings
Brake trigger timing
* Various response delays
Braking
Braking
patterns
* Various braking patterns
Coasting
This slide that better explains our idea.
Rear-end collisions are happening by a combination of
[Click]
Various trigger timings,
which are the timings that drivers notice a collision danger,
Various response delays,
which are dependent on driver characteristics,
And various braking patterns,
which are also dependent on driver characteristics.
Then,
how was the hypothesis verified?
How was the hypothesis verified 10 10

11. EDR Data Analysis Source : NHTSA EDR database Speed reduction (mph) 30
CDR system connected
to a crashed vehicle
Speed reduction (mph)
(Total 70 cases) 30 28
3m/s 2
4m/s
5m/s 20
- 20 20
Number of cases 11
- 40 10
It was verified with actual rear-end collisions.
The actual rear-end collision data.
were obtained by the analysis of the NHTSA EDR database.
The graph on the left hand side
shows a histogram by braking onset.
You can see that nearly 70% started braking
less than about 1 second before the crash.
The graph on the right hand side
shows the speed reduction by braking onset.
As you can see, the average deceleration was
3.7 meter per square second. 6 4 1
- 60
None
-1s
-2s
-3s
-4s
-5s
None
-1s
-2s
-3s
-4s
-5s
Braking onset before a crash
Braking onset before a crash
Source : NHTSA EDR database
ftp://ftp.nhtsa.dot.gov/NASS/EDR_Reports/

12. Comparison between EDR
and simulation result
EDR
Simulation result shows similarity to EDR
[%]
Simulation result 50
-30
-20
-10
-40
-50 40 30
Speed reduction [mph]
Frequency 20 10
Assuming that the EDR is equipped with the vehicles
in rear-end collision simulation,
the red bars and red broken line were obtained.
The comparison indicates
that the simulation result shows
close similarity to EDR property.
Thus, rear-end collision simulation was created and verified.
None
-1s
-2s
-3s
-4s
-5s
None
-1s
-2s
-3s
-4s
-5s
Braking onset before a crash
Braking onset before a crash 12 12

13. Rear-end Collision Simulation
Without a System
+FCW,DBS & CIB
With a System
Warning Q S P R T
DBS
CIB
Braking
patterns A
Danger is
noticed
later
than
warning
onset
Braking
will be
sooner
Coasting
Braking B C D
Danger is
noticed
prior to
warning
onset E
This sketch shows the rear-end collision simulation without a system.
By adding FCW, DBS and CIB effects onto all cases,
[Click]
A rear-end collision simulation “with a system” was generated.
For the cases like A and B,
the danger is noticed later than the warning onset,
the warning is expected to help the driver notice danger sooner
and apply braking sooner.
Furthermore, DBS and CIB effects are overlaid onto driver response.
For the cases like D and E,
the danger is noticed prior to the warning onset,
therefore the warning itself is not effective,
DBS and CIB effects are overlaid onto driver response.
By comparing P with A, Q with B, C with R and so on and summing them up,
the system benefit can be estimated.
System benefit can be estimated by comparing
P v.s. A, Q v.s. B, R v.s. C and so on. 13 13

14. Simulation 1 FCW onset DBS onset CIB onset
= 1.7 sec = 0.8 sec = 0.45 sec
SV = 20m/s
*Under the Japanese MLIT
guideline in 2003
Not expected
to push
brake pedal*
Expected to
push brake pedal
*e.g., sleepy or fell asleep
FCW
+DBS
+CIB
CIB
Speed
reduction
Crash
avoidance
ratio
3.2mph
4.5mph 5
6.3mph
8.1mph 10
(mph) 15
FCW
+DBS
+CIB
CIB
This and the next slides show
what we got as a result of our ACAT program.
The control onsets applied in the simulation
is shown in the box on the top.
For those who are expected to push the brake pedal,
it is estimated that a system with FCW, DBS and CIB
could reduce 8.1mph of speed reduction and 1.0% of crash avoidance.
And for those who are not expected to push the brake pedal,
due to sleepiness or falling asleep,
only CIB is activated and it could reduce 4.5mph
but could not reduce crashes.
You may feel that the results show very poor crash avoidance ratios.
This is due to the settings shown on the top.
These settings are based on the Japanese MLIT guideline in 2003;
Ministry of Land industry and transport guideline at that time.
As I stated at the beginning of the presentation,
the system has been developing year by year.
The current guideline permits stopping before a crash.
0.0%
0.0%
0.0%
1.0% 5 10
(%) 15 14

15. Simulation 2 FCW onset DBS onset CIB onset
= 2.0 sec = 1.1 sec = 0.75 sec
SV = 20m/s
Not expected
to push
brake pedal
Expected to
push brake pedal
FCW
+DBS
+CIB
CIB
Speed
reduction
Crash
avoidance
ratio
5.7 mph 5
9.1 mph 10
12.3 mph
15.4 mph
(mph) 15
FCW
+DBS
+CIB
CIB
This slide shows the result of another parameter setting.
All control onsets were set to engage sooner compared to the previous slide.
It is shown that FCW plus DBS contributes crash avoidance
at the speed of 20m per second.
Thus, the method makes it possible
to calculate the benefits
for each function and for each control setting.
0.0%
0.0 %
7.9 % 5 10
13.5 %
(%) 15 15

16. Conclusions An estimation of the benefit of FCW, CIB
and DBS was developed.
Driver response before collisions was measured in the driving simulator. It was shown that response varied widely from person to person.
Rear-end collisions were reconstructed. The result was validated with the EDR data analysis.
Estimation method demonstrated the benefit difference by each specification.
This slide summarizes the conclusions. 16

17. Current Study; LDW benefit estimation
Here I show you our current study.
Toyota is developing the LDW benefit estimation
using traffic accident data in Japan.
For the United States,
[Click]
Toyota is not familiar with the detailed traffic accident data.
We found that Dr. Gabler of Virginia Tech
is the expert of this kind of research,
We are proceeding with the research together.
Both works are in the first stage.
The results of the studies will be published
at the upcoming SAE World congress.

18. End This is the end of my presentation. Thank you for your attention.18 18