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Human versus Computer Performance - 2014 Automated Vehicle Symposium SF Serge Lambermont

2014 Automated Vehicle Symposium - Serge Lambermont


https://onlinepubs.trb.org/onlinepubs/conferences/2014/AutomatedVehicleSymposium2014Proceedings.pdf#page129


Summary:


The Tuesday breakout session discussed the concept of digital infrastructure and mapping in order to begin

exploring the following questions:

  • What elements are included in the definition of digital infrastructure?

  • What data are needed and how will the data used by the vehicle? By the infrastructure?

  • What is the government’s role and responsibility in digital infrastructure and mapping?

  • What is the relationship between industry and infrastructure owners and operators in an automated vehicle environment?

Mr. Serge Lambermont’s presentation provided an overview of digital infrastructure

and other interrelated activities supporting the development of automated vehicles,

including the role that suppliers play in this environment. Two key areas were

highlighted: 1) understanding the strengths and weaknesses of technology today

and how digital infrastructure can be used to further support automated vehicles;

and 2) exploring the uses and impacts of digital infrastructure in adjacent markets

today that could then lead to further developments in automated vehicles. The

following are points raised from these two key areas:


Human versus computer vision/lidar/radar detection and classification:

  • Assuming that human are perfect drivers, how would this compare to machines? A quadrant diagram with computer recognition and human recognition on each axis was presented to demonstrate the strengths and weaknesses of both groups (see figure below)

  • Maps for localization and lane markings can immediately address areas where human recognition is strong but machine recognition is lacking, including road boundary detection, curved lane marking, crossing lane marking, adjacent lane marking, stop lines and lines for lane marking.

  • ADAS maps can address stop lines, traffic lights, traffic signs, and lines for lane markings, which can be recognized fairly consistently by machine but this could provide improvement and redundancy.

  • V2I functionality can be used for determining trajectories of other vehicles/objects, and reading traffic lights and traffic signs, as well as V2V redundancy.

  • Adjacent market developments and impacts on Digital Infrastructure


figure, human versus computer detection and classification



Passenger Car Market & Commercial Vehicles: This market continues to

be driven by improvements to active safety and New Car Assessment

Program changes. This includes automated braking, detection systems,

active collision avoidance, automated highway lane change. This market

uses digital infrastructure for ADAS maps, V2X, functional safety and

cybersecurity.

Low Speed Autonomous – no steering wheel: This is a somewhat new

market; it is envisioned that these vehicle types would primarily be used

for retirement, airports, entertainment, work campus, care free city

centers, manufacturing, etc. There is more confidence today for

programs at low speeds; we are seeing a large number of low speed

prototyping vehicles emerging. These vehicles use maps but are also very

dependent on the sensor suite. Digital infrastructure is used for

localization.

Tech enabled car share and rideshare: This market is already using

digital infrastructure to a small extent as information is being transferred

to the cloud and the vehicle. This requires dynamic digital infrastructure

– optimal booking-routing, real-time cloud based updates, new physical

infrastructure, and call on demand.

Personal Rapid Transit: This includes smaller vehicles (2/3 wheel, limited

width), coming to market for fuel efficiency and individual mobility

purposes. These vehicles may need to share lanes with regular vehicles

and could impact the use of digital infrastructure.

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