Transportation
❯
Autonomous driving
❯Self-driving aircraft towing vehicle
Autonomous apron truck
For:
Transporter
Scope:
Automated transportation of luggage (carts) to requested destinations on an airport apron while following local traffic rules and resolving unplanned
conflicts.
Goal:
Improve Operation Efficiency
Government
Defense & Military - Autonomous Vehicle
For:
Military Operatives.
Scope:
Using computer vision to implement perimeter safety for Autonomous Vehicles.
Goal:
Improved Product Development / R&D
AI components for vehicle platooning on public roads
Scope:
Trains of vehicles that drive very close to each other at nearly equal speed
(platoons) on public roads, in particular platooning trucks on motorways.
Goal:
Improve Operation Efficiency
Autonomous trains (Unattended train operation (UTO))
Scope:
Freight and passenger trains operate autonomously, excluding any crew
presence on board, but with remote operator attention involved.
Goal:
Improve Operation Efficiency
Self-driving aircraft towing vehicle
Scope:
Self-Driving towing vehicle for aircrafts, operating on an airfield autonomously.
Goal:
Improve Operation Efficiency
Self-driving aircraft towing vehicle
Goal:
Improve Operation EfficiencyProblem addressed
A towing vehicle that would, on command, autonomously navigate to an
assigned aircraft, attach itself, tow the aircraft to an assigned location (a runway
for departures, a gate for arrivals), autonomously detach itself, and navigate to
an assigned location, either a staging area or to service another aircraft.
Scope of use case
Self-Driving towing vehicle for aircrafts, operating on an airfield autonomously.
Description
Advances in self-driving automobiles make it technologically
feasible to apply this technology for the purpose of taxiing
planes to the runway from the terminal gate and vice-versa.
Deploying self-driving vehicles for this purpose offers fewer
technical challenges than deploying them on roadways and
highways.
Routes from gates to runways and runways to gates are
typically pre-determined, with little or no possibility for
alternatives. In addition, to ensure safety, constraints on
taxiing operations are rigid and unambiguous.
Rules such as separation constraints between taxiing aircraft
and those governing right-of-way at intersection points are
clearly documented and enforced by ramp and ATC
controllers. These rules and procedures reduce the overall
uncertainty in the operational environment and therefore
potentially simplify the models that are expected to be
employed by self-driving vehicles.
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Nominal autonomous operation of the towing vehicle (tug) is
captured as the following sequence (for the case of
departures): a tug sits at a tug depot, a designated area of the
airport surface where tugs recharge and return when not in
service. When the tug receives a message, describing time,
route, and gate, it travels to the specified gate following the
provided route. As the tug approaches the specified gate, it
navigates to a designated ready position. Once the ground
marshal attending the gate signals readiness for attachment,
the tug assesses the environment to verify the surroundings
are obstacle-free before moving to dock with the aircraft.
Once a taxi navigation plan is received from the centralized
route planner and the aircraft crew and ground marshal both
signal ready to push back, the tug pushes the aircraft away
from the gate and begins navigation through its assigned
route. When reaching a designated location in the take off
queue near the runway, the tug autonomously detaches from
the aircraft, moves to a safe position away from the aircraft,
signals to the aircrafts crew through a cockpit display that it
is detached, and navigates back to the depot along the route
provided by the planner.
Sensor Network - IOT
Live Video
AI: Perceive