Traffic Jams Non Zero Ratio

A NEW PROBLEM-SOLVING TOOLBOX
APPLIED ON TRAFFIC CONGESTION

VERHAERTINNOVATIONDAY – OCTOBER 20th, 2006

“Non-Zero Ratio”, a new
www.mastersininnovation.com

problem-solving toolbox
applied on traffic
congestion
Piet Holbrouck
piet.holbrouck@pandora.be
www.pietholbrouck.be - www.nonzeroratio.org

Commercially confidence – This presentation contains ideas and information which are proprietary of Powered by Piet Holbrouck, it is given in confidence. You are authorized to open and
view the electronic copy of this document and to print a single copy. Otherwise, the material may not in whole or in part be copied, stored electronically or communicated to third parties
without prior agreement of Powered by Piet Holbrouck.

20.10.2006 Slide 1


Content

• My background
• Non-Zero Ratio, a “new” problem-solving toolbox
• Application : Traffic jams / congestion

20.10.2006 Slide 2


My background
Test cases :
Unsolved problems

in society

Non-Zero Ratio
The Ultimate
Problem-Solving
Toolbox

Product
Development
Fuzzy
Problem-Solving and and
Front
Decision-Making Innovation
End
Research Consultancy

Powered by
Piet Holbrouck

20.10.2006 Slide 3


What is problem-solving?
Problem-Solving Expertise

(re-normalisation) (normalisation)

When expertise fails, one needs problem-solving.
Problem-solving is the discipline everybody needs.

20.10.2006 Slide 4


Introduction to Non-Zero Ratio : what?

• Tool to solve the toughest problems

• Two conjugate parts:
• PANDORA Problem-Solving toolbox/process
• Non-Zero Behaviour : Specification of the
environment (attitude) needed to “run”
PANDORA

20.10.2006 Slide 5


Validation of Non-Zero Ratio?

• Must succeed in providing solutions to hitherto

unsolved problems
• => Test-demo cases in different categories:
• Renormalisation
• Segmentation: traffic jam
• Filters of certainty
• Decision-making
• …

20.10.2006 Slide 6


What makes Non-Zero Ratio different?

• Distillation / selection of the finest sets of insights and

tools relevant especially to toughest problems
• Builds upon:
• Goldratt’s Theory Of Constraints – Thinking Processes
• Kahneman’s results on our Decision-Making in uncertainty
• John Nash’ win-win theorem
• Sync – complexity – evolution theories
• Altshuller’s TRIZ concepts
• Thomas Kuhn’s The Structure of Scientific Revolutions
• Derivatives
• Kotter, Senge, Coleman, …

20.10.2006 Slide 7

Key Insights 1 : Role of (re)normalisation to generate
new reinforcing Vision

• Breakthrough solutions break the norms
• “Structure of scientific revolutions” (T. Kuhn)
• Through a cycle : abnormal perspective
becomes normal after providing a
“normalised perspective” (examples:
Einstein’s Theory of General Relativity)
Normal => Abnormal (= absurd) <= New (normal) perspective

20.10.2006 Slide 8


Key insights 2 : The relevance of win-win

20.10.2006 Slide 9


Key insights 3 : Role of Segmentation
• Segmentation = different local optimizations, each local

optimization taking a different starting point, leading to different
types of solution
• Segments develop structures that tend to sustain themselves
• Each segment has its distinct advantage(s) and disadvantage(s)
• If segmentation exists, one can identify an ideal final solution as
the solution that combines all advantages of the different segments
while having no disadvantage; related to ideal final solution:
• TRIZ
• TOC (mapping of logic behind desirable and undesirable effects)
Stephen Covey 2nd habbit : begin with the end in mind
•
• The Ideal Final Solution will have properties mixed from several
segments

20.10.2006 Slide 10


Key insights 4 : synchronized evolution path

• From complex systems theory

• Changing / modifying entire segments and
their structure leads to :
• Need to synchronize (Crf. Steven Strogatz)
• Evolution to ideal final solution over
consecutive steps “next-adjacent-possible”
(Cfr. Stuart Kauffmann)

20.10.2006 Slide 11


Key insights 5 : Embrace uncertainty

• When leaving the “normal” zone, it
requires exploration to find those
“abnormal” (most people will say “absurd”)
assumptions that are key to the ideal final
solution path. During this exploration, the
attitude is to allow everything to be
questioned and seek new perspectives
supporting the “abnormal” directions …

20.10.2006 Slide 12

Key insight 6 : Use TOC-Thinking Processes and
SCRIPTS Decision-making under uncertainty

• To map the complex logic and allow to
discuss it in a complete and traceable way
(Miller : 7+-2)
• To overcome the biases we make when
making decisions in uncertainty
(Kahneman Nobel Laureate 2002)

20.10.2006 Slide 13


What could we learn from Non-Zero Ratio in the case
of traffic congestion?

• Win-win : identify stakeholders. If traffic
congestion is solved, who would loose? =>
Public transport! : Tug-of-war : find win-win
• Segments : cars, public transport, trucks,
boats, airplanes, …
• Construct Ideal Final Solution
• Find evolutive “next-adjacent-possible” path.

20.10.2006 Slide 14


From undesirable effects to ideal final solution

• Car transport : Undesirable effects

• No alcohol (=> not possible to drive to parties with alcohol)
• Good eye-sight needed (=>elder, blind)
• Attention needed (=> accidents)
• Skill needed (=> accidents)

• Public transport (bus-train) : undesirable effects
• Less-flexible in timing
• Not end-to-end

• Derived Ideal Final Solution : combine all positives; drop the negatives
• Automated driving (alcohol, blind, no attention/skill, flexible, end-to-end)

20.10.2006 Slide 15


From Ideal Final Solution to Next Adjacent Possible

• Mix of car and train? …

• At traffic congestion points it is already
now desirable to mix car and train
properties:
• If clusters of cars could now behave as a
train, the throughput at congestion points
would significantly increase
• How? … …

20.10.2006 Slide 16


How to accomplish the next-adjacent-possible?

• Suggestion for the “next-adjacent-possible”:

• ALL (!) cars equipped with cruise-control that acts upon
distance to car before
• How to establish : synchronisation to have add-on to all cars
• Local infrastructure modified to avoid lane crossings at
traffic congestion points
• Mix stakeholders : public transport + car (to avoid forcing
public transport in a “loose” position)
• Note how abnormal (absurd) this direction is …

20.10.2006 Slide 17


What about the feasibility?

• Technical : OK

• Financial?
• Cost:
• Belgium : 5.000.000 cars x 2 k€/car=10.000 M€ cost to install
system
• + modifications to infrastructure …
• Return?
• Cost of traffic congestion : 2002, Belgium : about 500 M€
• Other elements :
• Car accidents : 12.000 M€/yr (only partially to t
• Injuries and deaths
• ROI ranges from over 20 yrs ((10.000+X)/500) to far shorter

20.10.2006 Slide 18


Traffic jam threat as major opportunity
• From “Scripts” (Murnighan & Mowen) : missed opportunities if we

don’t do:
• Cities can maximize traffic throughput at rush hours rerouting traffic
circulation
• Car drivers can decide to use also in non-traffic congestion areas
• Learn to co-operate between segments (public transport – cars –
infrastructure – government – industry – individuals …)
• Learn to manage a massive synchronisation project
• Development of new products with economic potential (jobs, export)
• Recognition of Flanders/Belgium as world-wide leader
• Potential to extend this synchronisation to next steps (next-adjacent-
possible), such as control of steering
• Concluding : SCRIPTS leads to “do it”, especially as expected car
accidents (costing 12.000 M€/yr) can be expected to be dramatically
reduced

20.10.2006 Slide 19


Concluding

• Of course, there are obstacles, but:

• What are they? Can they be overcome?
• Isn’t the direction of the solution evident, in the end?
• Isn’t the exercise besides exciting, potentially extremely
learningful with strong economical, political and social
potential?
• Why should we NOT take the opportunity?
• What next?

Feedback appreciated : piet.holbrouck@pandora.be

20.10.2006 Slide 20


Verhaert New Products & Services nv
Hogenakkerhoekstraat 21
9150 Kruibeke
Belgium
Tel +32 (0)3 250 19 00
Fax +32 (0)3 254 10 08
www.verhaert.com
info@verhaert.com

20.10.2006 Slide 21

Traffic Jams Non Zero Ratio

Recommandé

Recommandé

Contenu connexe

Plus de Verhaert Masters in Innovation

Plus de Verhaert Masters in Innovation (20)

Dernier

Dernier (20)

Traffic Jams Non Zero Ratio