Just a T.A.D. (Traffic Analysis Drone)

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Transcription:

Just a T.A.D. (Traffic Analysis Drone) Senior Design Project 2017: Preliminary Design Review 1

Meet the Team Cyril Caparanga (CSE) Alex Dunyak (CSE) Christopher Barbeau (CSE) Matthew Shin (CSE) 2

Problem Traffic data needs to be more comprehensive as more and more cars are on the roads In addition, data needs to analyzed quickly Detect and track vehicles Develop statistical models and conclusions about traffic density, flow, etc. 3

Current Solutions Floating Car Data (FCD) Costly communication Requires all drivers to have FCD and all data available on a single platform for analysis Privacy concerns Video Camera Static placement Limited coverage Limited angle of view Difficult to see behind car 4

Motivation Current traffic data collection methods are expensive and/or insufficient Traffic is expected to increase by 50% over the next 16 years $124 billion in direct/indirect losses for Americans in 2013 Could rise to $186 billion by 2030 Source: http://www.forbes.com/sites/federicoguerrini/2014/10/14/traffic-congestion-costs-americans-124-billion-a-year-report-says/#dd89866252b0 5

Our Approach An Unmanned Aerial Vehicle (UAV) can be used to provide aerial image and video This data is sent to a server in the cloud for processing and analysis Image processing will analyze the image/video for car density and spacing 6

Block Diagram 7

Traffic Analysis Concepts Space sensor data - information provided by aerial sources (UAV) Spacing Density Space-mean speed Source: Traffic Flow Theory: A Unified Perspective, Ni (2015) 8

Image Processing Requirements Detecting Cars from a top down view Counting the amount of cars in the picture Distinguishing between different lanes of a highway Determining spacing between cars in each lane 9

Image Processing Approach Background Subtraction Drone takes images as initial background Uses recursive averaging to create estimate of background image Cropping Remove traffic in opposite direction Remove extraneous roads (ramps) and nonroad components Vehicle Detection Use background subtraction as vehicles are only moving objects Vehicles can be better segmented from background through thresholding 10

Drone - UDI U818A Used for preliminary testing Retrieve test images Suboptimal for final design 10 min flight time 50g payload capacity 30m flight range 11

Drone Alternative - 3DR Iris+ Cost: $550 Payload: 0.8lb Flight Time: 20 minutes Range: 1km Programmable Autopilot 12

Internet Connection Take pictures at one second intervals Transmit images over 3G to data server 13

Data Server Server receives images from the drone and performs image processing Displays data on web page and file for download 14

Price Estimation - UDI U818A Drone Raspberry Pi 3G Dongle 3G Subscription Battery (Pi) FAA Registration $50 $35 $20 $30 $20 $5 Total $160 15

Price Estimation - 3DR Iris+ Drone Camera Raspberry Pi 3G Dongle 3G Subscription Battery (Pi) FAA Registration $550 $50 $35 $20 $30 $20 $5 Total $710 16

Design Alternatives Process images on board and only transmit data Collect all data and then return for offline processing Collect data and return for WiFi transmission to data server Have a GUI for the end user to view data Ex. Google Maps interface Calculate space-mean speed of vehicles and determine flow 17

MDR Deliverables Alex/Cyril: Image processing Identifies 80% of visible cars in ideal conditions in sample tests Identifies distances between cars to within one car Has 35 distinct test cases for our image processing software Matt: Data server for performing image processing and storing data is set-up Chris: Camera and network system can send image data to data server via 3G 18

Thank You! Questions? 19