PRE2017 3 Groep10

1) Problem statement:

Can the everyday delivery method of packages be improved by means of drones?

Objectives:

- Human aspect; who is responsible when something goes wrong?

- Delivery method; How accurate can a drone pick up and deliver packages?

- Transport efficiency; what is the time gain of trucks vs drones? Including airspace restrictions.

2) Who are the users?

The Buyer and supplier

3) What do they require?

Supplier: quick, easy, safety. Buyer: easy and cheap delivery.

4) Approach, milestones and deliverables

Approach: literature study, surveys, models, experiments

Milestones: testing with Blue Jay, at least 75 surveys, CAD design for delivery method, 25 scientific articles, simulate the time gain of drones

Deliverables: report

5) Who’s doing what?

- Nol & Marc: responsible for the CAD design

- David & Thibeau: responsible for the simulation of the time gain

- Pam: responsible for the survey

Assumptions

Backed up assumptions Group 10

Coaching Questions

Coaching Questions Group 10

Simulation model to analyse delivery efficiency

GOAL: Determine the time gain by using drones for the 'last-mile-delivery' instead of using cars/vans.

APPROACH: A number of random locations within a dutch city are picked. These locations are assumed to be destinations for packets to be delivered. Then for both methods the time spent on 'last-mile-delivery' is estimated using simulations.

METHODS: 1) Delivery is done by a typical delivery car or van. The main restrictions taken into account are the speed limits. To start off, delay due to busy traffic isn't explicitly implemented yet in this simulation(this might be done later on). An assumption for this method is that only 1 vehicle is used to deliver all packets within that city (Max 10 packets). For now, the actual delivery (parking the vehicle, getting out, get the package to the receiver) is approximated by a constant that can be altered (1-5mins).

2) Delivery is done by drones. The main restrictions are: cruise speed, obstacles (airfields, power lines, windmills) and max range. Later on, if enough time is left, more complex factors can be simulated such as wind(speeds), changing the travel time and range. Multiple drones can be used for a single city. Can be altered to study efficiency relation. All of these drones are deployed from a single location in the city (place where the truck is stopped). For now, the actual delivery is approximated by a constant that can be altered (30s-2mins).

State of the art

State of the art Group 10