https://www.youtube.com/watch?v=fmZDRL9P-v4&list=PLqJzTtkUiq54DDEEZvzisPlSGp_BadhNJ&index=9 To make an autonomous vehicle more cognitive, it needs the implementation of advanced cognition theories and AI theories. In this work, we firstly make a brief overview of current advanced theories of cognition in Psychology and Computer Science. Then we mainly analyze and compare the architectures of the autonomous vehicles winning DARPA Challenges. The layout of sensors and the design of software system are critical to the winning autonomous vehicles. By comparing different autonomous vehicles, we find some common points shared among them and more differences due to the various sensors layouts and the difference among cognition architectures, which could give some valuable directions to the researchers in both computer science and cognition fields. Then we will link decision-making to intelligence decision-making and its algorithm using example.

1. Cognitive computing in Autonomous Vehicle
Pranav
Graduate Student in Computer Science Dept.
At
Semantic-Cognitive-Perceptual Computing Class, Summer 2016
Wright State University
1

2. Agenda
(1) Defining cognitive in autonomous vehicle scenario. (cognitivism,
connectionism and Embodied cognition)
(2) Architecture of autonomous vehicle. (hardware + software in brief)
(3) Further discussion on the Intelligent System of Decisionmaking (ISD)

3. References
1. http://www.escience.cn/system/download/68692
1. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4564448/pdf/12559_2015_Articl
e_9320.pdf

4. Cognition
Cognition can be briefly defined as acquisition of knowledge
Cognition mainly focused on pattern recognition, attention, memory, vision image, language, problem
solving and decision making.
Vision, audition, tactile, olfaction and gustation as low level perception of cognition
Language understanding, problem solving and decision making into high level cognition.
How to bridge low level perception with high level cognition and how human intelligence
forms lead to different research topics in Psychology.

5. Cognitivism, Connectionism and Embodied Cognition
Cognitivism is a theoretical framework for understanding the mankind mind. It was
cognitivists tries to disclose the internal relations between perception and action.
Cognitivism believes that symbol computing is the core of intelligence.
Connectionism believes that numerous connected units network is the basis of
generating intelligence.
Embodied cognition theory, cognition is not about intellectual demonstration but
more related to the body and its surrounding physical environment

6. Definitions of cognition in AI into four categories
(1) Thinking like a human
(2) Acting like a human
(3) Thinking reasonably
(4) Acting reasonably

7. Thinking like a human
That computer programs may think like a
human requires us understand how human thinks
firstly.
We should have a whole understanding of the
inner progress of mind.

8. Acting like a human
Being acting like a human, the computer programs should be
with the ability of automated reasoning, machine learning,
computer vision, and so on.
They also need to pass the Turing Test.

9. Thinking reasonably
To think reasonably requires computer programmers first find
the "Law of Thought" proposed by the ancient Greek
philosopher Aristotle and others.
The law tries to find "the right way of thinking".

10. Acting reasonably
Acting reasonably requires computer programs can
● operate automatically
● percept environment
● adapt to the change of environment
● create and pursue goals
● make the best decision under uncertain situations

11. Architecture of autonomous vehicle
According to Embodied Cognition theory, the cognition system of an autonomous
vehicle can be divided into two parts:
● Environment perception
● Driving decision
The two parts in the vehicle interact with each other to ensure the vehicle move to
the destination safely.
The two parts correspond to the low level perception and high level cognition
separately, where environment perception via sensors belongs to the low level
cognition, navigating and decision making belong to the high level cognition.

12. Cognition architecture of autonomous vehicle
Environment perception Driving decision
low level high level
perception
cognition
environment perception via sensors navigating and decision
making
belongs to the low level cognition belong to the high level cognition

13. PERCEPTION MODULES
● Short memory systems
● Obstacle detection
● Localization and mapping
● Some necessary but not discussed modules
○ Traffic lights detection
○ Traffic sign detection and recognition

14. Obstacle Detection & Localization and Mapping

15. NAVIGATION AND DECISION MAKING

16. NAVIGATION AND DECISION MAKING

17. NAVIGATION AND DECISION MAKING

18. Survey Results
(1) There's no systematic discussion of the robustness of the autonomous vehicle.
(2) As 80% of information obtained by a human driver is from his/her vision, it's
valuable for researches in computer vision field to improve reliability of computer
vision methods.
(3) Not so much papers published in the evaluation of the reliability of the vehicle's
cognition level.

19. Intelligent System of Decisionmaking (ISD)
Such a system which implements models of cognitive and personality (motivation)
psychology for a control system.
Many design methods are based on artificial intelligence
● Fuzzy systems
● Neural networks
● Evolutionary algorithms or rule-based methods

20. Abstract layers of ISD in case of AV or UGV
The systems for autonomous driving are quite complex and can be divided into
few subsystems
● perception system
● traffic rules interpreter
● decision system (behaviour controller)
● low-level car controller

21. ISD System Adaptation
The adaptation of the ISD system to the driver tasks is performed in three steps: –
● Integration of the perception systems
with the simulated environment
● creation of an interpreter of traffic rules
● designing an adequate set of reactions
and needs (H) according to emotional
context (n

22. The model of an adopted ISD
● The environment is constructed on
the basis of a certain scenario
○ position, velocity and
acceleration
● The shape of perception area
strongly depends on the scenario
○ especially on bends and slopes
of the road
● Computes the estimated position of
objects
○ according to the state of the car
○ its current scene

23. The model of an adopted ISD (continue..)
● Effects of the current traffic regulations
and the objects in the view area can be
assigned to the xDriver states (of all its
needs H and emotion n)
● Easily find the new reaction
● Feedback: the reaction affects
accordingly the current state of the car
● Note that this model is a derivative of
cognitive psychology, adapted for the
purposes of the autonomous driver. It
simply mimics the way in which the
driver reacts to certain stimuli

24. Needs and Emotions
● Needs and emotions constitute a crucial
part
● human motivational system
● Allow us to ’control’ the Driver’s desire
to act.
● The symbol g represents the degree of
non fulfilment of a certain need and
hereinafter g will be called a need
● It is an abstract fuzzy value,
● which takes one or more (two) of three
states: satisfaction (lowest), prealarm
and alarm (highest)

25. Needs and Emotions (continue..)
● It can, for instance, be partially satisfied
and partially prealarmed (according to
its actual crisp value)
● A need is completely satisfied whenever
its crisp value is equal to zero
● This importance is described by a
weighting function, which takes the form
of a sigmoid curve.
● The weighting emphasizes the
importance of alarmed needs.
● It is easier for xDriver to choose those
needs that require immediate reaction
and fulfilment.

26. Need and Maslow Pyramid
● Physiological (principal) level: energy
optimization
● Physiological level: goal achievement
● Safety level: security of car
● Safety level: traffic regulations
● (self-)esteem level: speed
● (self-)esteem level: confidence
● self-actualization level: creativity.
Ref: Image from wikipedia

27. Making the Decision

28. Making the Decision (continue..)

29. Making the Decision (continue..)

30. Thank you, and please visit us at http://knoesis.org
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