Feng Chia University, Hsin-Chien, Wang

06 May 2017

#1 – Introduction

Briefly describe SAE automated vehicle classifications:

  • Level 0 – No automation:

Automated system has no vehicle control, but may issue warnings.

  • Level 1 – Driver Assistance:

More than one kind of Driver Assistance systems in the vehicle, for instance, adaptive cruise control (ACC), Parking Assist with automated steering and Lane Keeping Assist (LKA).

  • Level 2 – Partial Automation:

The automated system executes accelerating, braking, and steering. The automated system can deactivate immediately upon takeover by the driver.

  • Level 3 – Conditional Automation:

The system including monitoring of the driving environment, under certain conditions (e.g. traffic jams on motorways) and needs to alert the driver in advance if conditions require transition to driver control.

  • Level 4 – High Automation:

The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so.

  • Level 5 – Full Automation:

The automatic system can drive to any location where it is legal to drive.




NAVYA introduces its fully autonomous NAVYA ARMA Shuttle to the U.S. market at Michigan City, and the University of Michigan’s simulated city for testing autonomous vehicles. This is one of the most prestigious testing grounds in the world and is managed by the University of Michigan. The NAVYA ARMA is it the only European shuttle bus on the site.

The shuttle has been designed to ensure the specific functions of an autonomous vehicle whilst optimizing on navigation and safety. It is equipped with a multitude of sensor technology to provide 3D vision which enables it to map out the environment, detect obstacles in its path and identify traffic and road signs. The NAVYA ARMA shuttle can reach speeds of 45 km/hr.

The shuttle bus is the result of 10 years’ R&D experience that has enabled it to gain the highest level of autonomy possible, making it a fully autonomous and driverless production vehicle.




Olli is a 3D-printed self-driving electric shuttle bus designed by the online community and built by Local Motors. Designed to streamline shared transportation systems around the world, this self-driving car could be the answer to public transportation issues.

“The Olli system is responsible for all aspects of vehicle operation: localization, object detection, steering, acceleration/braking, emergency/safety sequence, and so on,” said Local Motors Product Manager Jonathan Garrett.

The vehicles have already been tested in Maryland and avoided accidents during trials, despite facing additional stress tests from pranksters.

Olli is Level 4 and uses LIDAR for its “vision” unit versus the forward-facing cameras and radar. Local Motors has suggested the use of Olli to fill gaps in city transit systems, transporting students across campuses, or even transporting employees across corporate grounds. Taking self-driving vehicles to the next level, Olli is ready to get to work, as soon as regulations allow it.


4 possible applications for autonomous vehicles

  1. The autonomous end-to-end supply chain

The so-called last-mile, the delivery to the doors of businesses and consumers, is probably the most complex task in the supply chain. The automated delivery vehicles could take this task easily.

  1. Personal Rapid Transit: https://youtu.be/5G9X0voSi2Y

PRT is designed as an extension of existing pod cars and serves as a subway car on demand, and is used in areas where the demand for transport systems is irregular and high during peak hours.

  1. Driverless intercity bus and autonomous freight transport

This application could reduce the cost of road haulage costs, margins and profits and the disadvantage of human factor, and also solve the driver shortage crisis.

  1. Non-stopped autonomous bus system

This system is combined with one main autonomous bus and one autonomous shuttle. People can get on the main bus easily by taking the shuttle in the bus stop, and then the shuttle will connect to the main bus when it pass by. Another shuttle, which is connected at the previous stop will separate itself from the main bus to the next stop. It’s a pattern which can greater efficiency of public transportation because the main bus just keep going from first stop to last stop.



  1. AdaptIVe system classification and glossary on Automated driving(PDF).
  2. http://www.sae.org/misc/pdfs/automated_driving.pdf
  3. http://navya.tech/wp-content/uploads/2016/12/NAVYA_MCITY_PRESS_RELEASE.pdf
  4. https://localmotors.com/olli/
  5. Wolfgang, Lehmacher (01 Mar 2017) “How automated delivery vehicles will transform your city?”
  6. https://youtu.be/5G9X0voSi2Y

Author: wangznpb

CDIO pre-assignment

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