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VTS - Active Safety > Active Safety > Flashcards

Active Safety Flashcards

1
Q

Example of three Active Safety assistance systems

A

Night Vision, Adaptive Cruise Control, Queue Assist

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2
Q

Example of three Active Safety warning systems

A

Pedestrian warning, Lane departure warning, Collision warning.

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3
Q

Example of three Active Safety emergency systems

A

Crash avoidance, pedestrian impact mitigation, active bumpers.

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4
Q

Behaviour based safety: Explicit Coaching

A

Monitor driver with i.e a video camera. Later review videos and get coaching from “boss” etc. What could have been done differently?

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5
Q

Behaviour based safety: Implicit Coaching

A

“Nudging”.

Make driver a better driver by implicit feedback, like sounds and “feelings” like speed bumps, rumble strips.

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6
Q

Behaviour based safety: Safety Policies

A

Set up by companies to promote safe driving instead of fast deliveries etc. Zero tolerance for speeding etc.

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7
Q

Different types of active safety evaluation techniques.

A 
Simulator (Low fidelity)
Simulator (High Fidelity)
Test Track
Real World (Controlled Observations)
Real World (FOT & NDS) -- Vet inte vad det betyder ännu. 
Counterfactual Simulations
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8
Q

Four different longitudinal sensors.

A

Vision, Radar, Lidar,GPS

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9
Q

Comparison between LIDAR and RADAR?

A

LIDAR: More moving parts, often better angular resolution, so far more expensive (scanning), More weather issues.
RADAR: Velocity by Doppler effect, not possible with LIDAR.

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10
Q

Why is camera-based applications usefull?

A
  • Detection and tracking of vehicles
  • Lateral positionoing
  • Pedestrian detection and tracking
  • Sign recognition
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11
Q

List some methods for evaluating active safety methods

A 
Simulatior, 
Test-track, 
Real world (controlled observation),
Real world (FOT & NDS)
Counterfactual simulations
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12
Q

Difference between frame-transfer and rolling-shutter.

A

Frame transfer, captures whole image at once.
Rolling shutter, reading out line-by-line. First line will be a earlier capture of the scene than the last, leading to image distortion.

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13
Q

What does eye-tracking measure?

A

The direciton of the drivers gaze. (Direction the eyes are pointing). Used for eye-on-road-measurements.

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14
Q

LSB = ?

A

Least significant Bit

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15
Q

Interlace cameras are as good as progressive scan for image processing.

A

False

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16
Q

How does a GPS work?

A

Triangulation between three satellites. Time of flight from the three satellites is used to determine your position.
Very important that all satellites function through a common CLOCK.

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17
Q

One can say that there is three V’s for big data. Name these.

A
  • Volume
  • Velocity
  • Variety
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18
Q

One can say that there is four M’s for Naturalistic Data. Name these.

A
  • Much
  • Many
  • Missing
  • Messy
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19
Q

Name three plans for Development and evaluation of

active safety systems.

A

Validation Plan
Test Plan
Verification Plan

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20
Q

What is Field Data?

A

Field data is data collected in real-traffic often according to an experimental protocol, which may define driver type (e.g. test engineer) and driving conditions (e.g. itinerary). It may require instrumented cars/trucks and infrastructures.

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21
Q

What is Field Operational Test (FOT)?

A

Field operational test are large collections of real-traffic
data, often performed in a naturalistic fashion, but with the aim of evaluating a system (e.g. an active safety system). As a consequence, a treatment and a baseline phase are often present in a FOT.

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22
Q

What can Heinrich’s Triangle be used for?

A
  • A widely used theory in safety research
  • Shows the importance of injuries
  • Suggests a relation between near crashes and crashes*
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23
Q

Why is it a good idea to use data from near-crashes instead of “real” crashes?

A

crashes in naturalistic datasets are just a few

crashes in naturalistic datasets tend to be mild
anyway (so we still need to climb the Heinrich’s
triangle)

if near-crashes are indeed a good surrogate for
crashes, it may not be ethically correct to ”wait” for
crashes to be recorded.

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24
Q

Time accuracy of GPS?

A

3 ns

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25
Q

How does a GPS work?

A

Triangulation between three satelites

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26
Q

GPS DATA types.

A

Satellite Almanac Data - Satellite location (valid: days)
Satellite Ephemeris Data - Satellite ranging (hours)
Signal Timing Data - Time-tag, for positioning of user
Ionospheric Delay Data
Satellite Health Message

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27
Q

GPS Errors

A
  • Ionospheric Propagation Errors - Wave propagation, 1m at night, 5-15m at daytime.
  • Tropospheric Propagation Errors - 2.5m in zenith, 10-15m for low altitude satellite angles.
  • Multipath Errors - bouncing.
    These have been solved with DGPS:
    Ephemeris Data- and On-board clock-errors. Both below 1m.
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28
Q

GPS protocol: NMEA messages. (National Marine Electronics Association)

A
  • Starts with $, ends with CR/LF
  • Max 80 characters
  • Data items separated by commas
  • ASCII
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29
Q

What does natural data offer?

A

Naturalistic environment

Long term (adaptation, learning, new strategies,
etc.)
  • Wider population (demographics, styles, etc.)
  • Different driver status

• Different driving contexts

• Network effect (several road users interacting;
mixed traffic)

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30
Q

Large naturalistic driving studies provide big data (True/False?)

A

True

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31
Q

Data collected on a public road are naturalistic data (True/False?)

A

False

32
Q

In a naturalistic dataset, data are seldom missing (True/False?)

A

False

33
Q

Naturalistic data are increasingly available (True/False?)

A

True

34
Q

Naturalistic datasets do not support human factors

research (True/False?)

A

False

35
Q

What are Odds Ratios?

A

Analysis methodology from epidemiology.

• Assess the association between the absence or presence of two properties.
• Because there are 2 properties and can have 2 states (present and non-present)
all possible combinations are representable in a contingency table with 2 rows
and 2 columns

Example:

Odds of crashing when
texting: A/B
Odds of crashing when
non-texting: C/D
Odds ratio: (A/B)/(C/D)
36
Q

Name some facts about the 100 car study

A

• Approximately 2,000,000 vehicle
miles

• Almost 43,000 hours of data

• 241 primary and secondary
drivers participated

• 12 to 13 month data collection
period for each vehicle

• Five channels of video and many
vehicle state and kinematic
variable

37
Q

Name some Data Types in Nat Datasets

A
  • Objective
    • Videos
    • CAN (environment, driver, vehicle)
    • Extra sensors (eye tracking)
  • Subjective
    • Interviews
    • Diaries
    • Demographics
    • Annotations (manual coding of videos)
38
Q

What are Odds Ratios?

A

Analysis methodology from epidemiology.

• Assess the association between the absence or presence of two properties.
• Because there are 2 properties and can have 2 states (present and non-present)
all possible combinations are representable in a contingency table with 2 rows
and 2 columns

Example:

Odds of crashing when
texting: A/B
Odds of crashing when
non-texting: C/D
Odds ratio: (A/B)/(C/D)
39
Q

What is driver behaviour?

A

Driver behaviour is a collection of actions performed during driving in interaction with the vehicle and the environment

40
Q

DGPS

A

Differential GPS - Uses land(earth) based stations to increase GPS position.

41
Q

Name some Important human factors aspects to consider during the design of active safety systems / automated driving:

A 
Expectancy
Situation awareness
Trust
Acceptance
Behavioural adaptation

Importante!

42
Q

Autonomous vehicles - mapping.

A

Building virtual model of world using ex. LIDAR.

Two mapping runs, one for verification.

43
Q

Autonomous vehicles - SLAM

A

Simultaneous Localization and Mapping. Building model and mapping on the fly. The same as “Electronic Horizon”

44
Q

How can GPS be used in Autonomous vehicles.

A

GPS typically not good enough for positioning, but can be used as a complement to ex. SLAM

45
Q

Map projection standards.

A

WGS84, RT90

46
Q

Multipath-error is typically the main issue with DGPS?

A

True

47
Q

Dilution of precision is a measure of time synchronization

in GPS implementations

A

False

48
Q

With differential GPS precision can not go above 0.5m

A

False

49
Q

What is a Human Machine Interface (HMI)?

A

“all parts of an interactive system (software or hardware)
that provide information and control that is necessary
for the user to complete a certain task with the interactive
system.”

50
Q

What is user-centered design? And state three major phases of user-centered design.

A

“User-centered design emphasizes that the purpose of
the system is to serve the user, not to use a specific
technology, not to be an elegant piece of programming.
The needs of the users should dominate the design
of the interface, and the needs of the interface should
dominate the design of the rest of the system”

  1. Understanding users => observe people and tasks
    by them performed up to the point of empathy
  2. Creating prototypes => combine understanding of
    people and human characteristics, interface
    guidelines and principles of human behaviour
  3. Evaluating => heuristic evaluations and usability
    tests with low-fidelity mock-ups or prototypes
51
Q

Name three HMI modes.

A

Visual
Auditory
Haptic

52
Q

What is driver behaviour?

A

Driver behaviour is a collection of actions performed during driving in interaction with the vehicle and the environment

53
Q

Name some Factors influencing driver behaviour

A

– Individual characteristics (e.g. age, personality)

– Socio-cultural values/norms (e.g. perception of traffic
offences)

– Technological factors (e.g. active safety systems)

– Driver motives (e.g. hurry)

– Driving context (e.g. traffic density)

54
Q

Name some Important human factors aspects to consider during the design of active safety systems / automated driving:

A 
Expectancy
Situation awareness
Trust
Acceptance
Behavioural adaptation
55
Q

ECU

A

Engine Control Unit - connecting sensors and acctuators in vehicle.

56
Q

Electrical architecture challenges

A 
Lower cost
Reduced mass
Improved functionality 
Smaller packaging
Improved reliability
57
Q

Whats the aim of a active safety system?

A

PREDICT safety-critical situation and TAKE ACTION before this develops into a crash.

58
Q

What is road crash data?

A

Data collected about crashes in road traffic, typically

organized in a database

59
Q

Name some sources of information for road crash data

A 
Police report
Insurance claim
On-scene investigation
EDR
Interview, questionnaire
60
Q

Name some levels of detail for road crash data

A
  • Macroscopic data
  • Intermediate level data
  • Microscopic data
61
Q

Name some common uses of road crash data

A

Identify priorities:
– Accident scenarios
– Road user groups mostly affected
– Black spots (locations with most crashes)
– For comparisons of risk, exposure data is needed!

• Evaluate technology performance
– Retrospective: actual effectiveness of a safety feature
already on the market based on the real-world
experience

  – Prospective: estimating expected effectiveness in 
      the productdevelopment phase

Determine new requirements

62
Q

Name some issues with road crash data

A

• Access to databases is typically limited

• Underreporting can bias results; examples:
– Single bicycle accidents are often not reported to the
police;
– Reported and actual (estimated) number of accidents
can differ substantially

• Different coding protocols can make data in different 
   databases incomparable (e.g. definition of accident type!)
63
Q

Macroscopic level of data. From where? Used for what? Number of variables?

A 
• Data collection
– Police
• No of variables
~ 50-100
• Usage
– National statistics
– Accident trends
– Identify black spots
– Road ranking (EuroRAP)
64
Q

Intermediate level of data. From where? Used for what? Number of variables?

A 
• Data collection
– Insurance, hospital, research, private companies,
authorities, police
• No of variables
~ 100-500
• Usage
– Injury follow-up
– Casualty cost calculation
– Policy making
– Judicial
65
Q

Microscopic level of data. From where? Used for what? Number of variables?

A 
Data collection
– Insurance, hospital, research teams,
private companies, authorities
• No of variables
> 500
• Usage
– Active and passive vehicle safety system development
– Infrastructure improvements
– Development of standards
– Policy making
66
Q

Integrated Safety systems

A

Typically enhances passive systems so that they provide the best protection.

67
Q

PRE-crash functionalities.

A

PRESET:
PRE-crash SETting of algorithmic thresholds.
PREFIRE:
PRE-crash FIring of reversible REstraints (restraints)
PREACT:
PRe-crash Engagement of ACTive safety devices. (AEB)

68
Q

Automated interventions are initiated only once a crash is unavoidable.

A

False

69
Q

Each active safety system may use one and only sensor.

A

False

70
Q

Lane departure warnings support longitudonal control.

A

False

71
Q

What are cooperative systems?

A

CS are intelligent transportation systems which rely on wireless communication to enable data exchange. For ex. V2V communication. Emergency vehicle approaching or road works.

72
Q

Communication challenges.

A
  • Multi path propagation, fading and ISI
  • Spectral limitations
  • Limited energy
  • User mobility.
73
Q

Some active safety challenges:

A
  • Data management (safety, privacy)
  • Wireless transmission capability (Bandwidth, reliability, ISI, speed)
  • Position estimation
  • Standards for communication
74
Q

$GPGGA,123519,4807.038,N,01131.000,E,1,08,0.9,545.4,M,

46.9,M,5,,*47

A

– GGA - Global Positioning System Fix Data
– 123519 - Fix taken at 12:35:19 UTC (satellite time)
– 4807.038,N - Latitude 48 deg 07.038’ N
– 01131.000,E - Longitude 11 deg 31.000’ E
– 1 - Fix quality
– 08 - Number of satellites being tracked
– 0.9 - Horizontal dilution of position
– 545.4,M - Altitude, Meters, above mean sea level
– 46.9,M - Height of geoid (mean sea level) above WGS84
– 5 - time in seconds since last DGPS update
– DGPS station ID number (empty here)
– *47 - checksum data, always begins with *

75
Q

Driver motives:

  • Excitatory Motives
  • Inhibitory Motives
A

Excitatory: Behavioural norms, social group pressure, can push driver to take smaller safety margins.
Inhibitory: Risk aversion, can push driver to take larger safety margins.

A combination of these determine which zone the driver experiences. Zone of control or outside?

76
Q

Categories of human errors.

A

Slips (actions not planned)
Lapses (memory failures)
Mistakes (deficiencies in judgement.)

77
Q

Temporary driver impairments.

A

Drowsiness
Intoxication
Distraction

VTS - Active Safety (1 decks)

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