#2 PRE-ASSIGNMENTS – CDIO ACADEMY 2017

PRE-ASSIGNMENTS – CDIO ACADEMY 2017

Feng Chia University, Hsin-Chien, Wang

12 May 2017

#2 – Technological

AUTONOMOUS VEHICLE TECHNOLOGIES

Figure_2_Autonomous Vehicle Technologies.jpg

Resources: http://www.css.snre.umich.edu/sites/default/files/Autonomous_Vehicles_Factsheet_CSS16-18.pdf

 

RARDAR APPLICATION IN AUTONOMOUS VEHICLE

  • How is it currently being used?
  1. lane-change assistanse
  2. blind-spot detection
  3. self-impact
  4. cross-traffic alert
  5. brake-assistance/ collision avoidance
  6. adaptive cruise control
  • What are its benefits and drawbacks?

Benefits of radar:

  1. The radar can see through the medium consisting of fog, snow, rain, darkness, clouds etc.
  2. Radar signal can penetrate and see through insulators.
  3. It can help find out following parameters of object or target:
  • Range
  • Angular Position
  • Location of Target
  • Velocity of Target
  1. It can distinguish fixed as well as moving target types.

Drawbacks of Radar:

  1. It can not distinguish and resolve multiple targets which are very close like our eye.
  2. It can not recognize color of the targets.
  3. It can not see targets which are in the water and are too deep.
  4. It can not see targets which are placed behind some conducting sheets.
  5. It is also difficult to recognize short range target types.
  6. Switching time of radar duplexer is very crucial when targets are very close. In this situation reflected pulses arrive much earlier than the time required to connect receiver part with the antenna by the duplexer. This results into “reflected pulse is not received by the radar”.
  • What is its future potential?

3D mapping of the traffic situation

In terms of further challenges, 3D mapping for autonomous driving in future will be the next level. There are two main ways to acquire data for HD maps in 3D. The first way involves instrumented, high-tech equipped vehicles for efficient and accurate 3D mapping of roads. The second way involves unmanned aerial vehicle systems equipped with similar lightweight sensors such as LiDAR or stereo cameras, providing a novel platform for photogrammetry. This is where LiDAR seems destined to prove advantageous. LiDAR works according to the same principle as radar and is based on measurement of the reflection of a transmitted signal. While radar relies on radio waves, LiDAR makes uses of light beams (e.g. laser). The distance to the object or surface is calculated by measuring the time that elapses between the transmission of a pulse and when a reflection of that pulse is received. The big advantage of LiDAR is that the technology enables much smaller objects to be detected than is possible with radar. In contrast to a camera, which views its environment in focal planes, LiDAR delivers an accurate, relatively detailed 3D rendering. This allows autonomous fast data acquisition, low errors, and dense point clouds for the realization of precise 3D maps. Once autonomous driving is implemented, HD maps in 3D will become essential.

Proximity Detection 340x340

Resources: https://www.melexis.com/en/insights/knowhow/how-sensor-technology-shape-cars-future

 

  • References:
  1. http://www.css.snre.umich.edu/factsheets/autonomous-vehicles-factsheet
  2. http://big5.xinhuanet.com/gate/big5/news.xinhuanet.com/auto/2012-12/04/c_124046607.htm
  3. http://www.rfwireless-world.com/Terminology/Advantages-and-Disadvantages-of-Radar.html
  4. https://www.melexis.com/en/insights/knowhow/how-sensor-technology-shape-cars-future
  5. http://www.sciencedirect.com/science/article/pii/S2095809916309432

Author: wangznpb

CDIO pre-assignment

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