Big Data for Automated Driving Technology, Transportation Planning, - - PowerPoint PPT Presentation

▶
big data for automated driving technology
SMART_READER_LITE
LIVE PREVIEW

Big Data for Automated Driving Technology, Transportation Planning, - - PowerPoint PPT Presentation

Apr 13, 2023 332 likes •726 views

2018 SF Bay Area ITE/ITS CA Joint Transportation Workshop Big Data for Automated Driving Technology, Transportation Planning, and Engineering Big Data Sources and Methodologies Gary Carlin, PE, PMP, PTP Thousands Use INRIX Real-time Traffic and

slide-1
SLIDE 1

Big Data Sources and Methodologies Gary Carlin, PE, PMP, PTP 2018 SF Bay Area ITE/ITS CA Joint Transportation Workshop Big Data for Automated Driving Technology, Transportation Planning, and Engineering

slide-2
SLIDE 2

INRIX powers more country, state & city agencies than any other company

  • Fusion of private and roadside sensor data on a

country-wide basis

  • Country-wide traffic services based exclusively on

GPS probe data

  • Innovative traffic analytics to understand origin and

destination

  • Corridor-wide multi-state traffic monitoring web site
  • Pay-for-performance contract with payments tied to

data

  • Exclusive sourcing deals and industry partnerships

A Histor

  • ry

y of ITS Public ic Sector

  • r Firsts

ts

Thousands Use INRIX Real-time Traffic and Analytics

Public ic Sector

  • r Customers
  • mers & Pa

Partner ers

2

slide-3
SLIDE 3

Mining Data On The Road

3

We use a connected network of sensors, devices, car and drivers to develop robust insights

slide-4
SLIDE 4

Global Scale and Impact

4

Powered by global relationships and coverage, INRIX takes on the big transportation and population movement challenges

4

100B+

Real-time data points aggregated, processed and delivered each month

350M+

Real-time vehicles and connected devices we crowdsource

5M+

Miles of road we cover in 50 countries

60+ 60+

Countries we are live in

1PB+

Data analyzed every day

15M+

Connected cars in the world powered by INRIX services

450+ 450+

B2B/B2G customers we serve

29M 29M

Parking spots we cover

slide-5
SLIDE 5

Movement Today & Tomorrow

Technology is fundamentally reinventing transportation, creating a unique opportunity

Smarter Transportation

IoT Sustainability

Use of Big Data for Decision Making

Urbanization Analytics Autonomous Connected Electric

Transformation of Automotive Industry

Shared

The convergence of the connected car and smart cities

slide-6
SLIDE 6

Autonomous

Connected

Electric Shared

Industry Inflection Point: The ACES

slide-7
SLIDE 7

Autonomous Electric Shared

Industry Inflection Point: The ACES Connected

slide-8
SLIDE 8

The Promise of Big Data

  • Improved Intelligence
  • More Data (every day…)
  • Better Data/Relational/Location Based Databases
  • Better Spatial Granularity and Coverage
  • Achilles Heel
  • DRIP (Data Rich Information Poor)
  • Drowning in Data
  • Don’t have the Staff/Resources/Tools to Effectively

Store/Analyze/Communicate the Data

One day y worth th of Origin ins s and Desti tina nati tion

  • ns in Seattl

ttle

slide-9
SLIDE 9

WHAT IS BIG DATA?

slide-10
SLIDE 10

You Can’t Handle th the Dat ata! a!!! !!

Big g Da Data ta: /biɡ/ /ˈdadə/: noun.

  • 1. Too big to fit in Excel
slide-11
SLIDE 11

2010 2011 2012 2013 Actual 2014 2015 2016 2017 2018 2019 2020 Forecast

Steady growth in global auto sales (units in Millions) Rapid rise in car connectivity (new connected car penetration rate in %)

Source: IHS Automotive and internal sources

73

  • 76
  • 80
  • 83
  • 86
  • 90
  • 94
  • 97
  • 100
  • 102
  • 104
  • 3%

4% 5% 7% 9% 13% 19% 26% 35% 42% 51%

  • 20
  • 40
  • 60
  • 80
  • 100
  • 120
  • Growth in Connected Vehicles
slide-12
SLIDE 12

Connected Cars Require a Lot of Software

INRIX Confidential 12

slide-13
SLIDE 13

Connected Cars Use a Lot of Data

INRIX Confidential 13

Current AV’s generate 2 GIGs/secon econd!

slide-14
SLIDE 14

Data Mining the Connected Car

Fuel Level Wipers Status Tire Pressure Speed Location

Raw Data

Fog Lights Camera Traction Control Engine Diagnostics Mirror Sensors LiDAR Sensors

Contextual Services

Temperature

Self-tuning Machine Learning

slide-15
SLIDE 15

There are More Mobile Devices Than People

slide-16
SLIDE 16

By 2020, More People Will Have Mobile Phones Than Electricity

slide-17
SLIDE 17

Data Privacy

  • Changes (like winter) are coming…
  • Who owns what data?
  • Impact of recent events/legislation
  • Numerous private sector data breaches
  • Russian hacking
  • Facebook Congressional hearings
  • Europe’s GDPR (General Data Protection Regulation)
  • etc., etc…

Data Privacy cy Benef nefit its s of Shared red Data

slide-18
SLIDE 18

Traditional Transportation Data Sources

  • Speed/Travel Time Data
  • Lane by lane
  • Volume Data (ADT/AADT)
  • Origin-Destination Data/Trip Purpose
  • Full Modal Split/Occupancy Data
  • Incidents
  • Construction
  • Weather
  • Events
  • etc.
slide-19
SLIDE 19

New/Expanding/Non-Traditional Data Sources

  • CV/AV Data
  • Numerous Safety Applications: Windshield Wipers, ABS, Air Bags, etc.
  • User Generated Information (UGI)
  • Socio-Economic Data
  • Land Use Data
  • Location Based Services (LBS) Data
  • Provides Context/Trip Purpose
  • Snow Plow Data
  • etc.
slide-20
SLIDE 20

Data “Layer Cake”

Speed d Data ta Land Use Data Socio-Eco Economi nomic c Data Origin in-Destin Destinat ation

  • n Data

Transit sit Service ice Data Const st./I /Inci ncident dent/W /Wea eathe ther Volume/A ume/ADT/ T/AAD ADT Modal al Data

Delay y Impa mpacts cts

“Cut Through” Data Layers

Trip Purp urpose se Toll Fea easi sibi bility lity Study udy

slide-21
SLIDE 21

The Power of Multiple Data Sets

Speed Data Land-Use Data Origin- Destination Data Socio- Economic Data Volume Data Mode Split Data Freight Data CV/AV Data

Future Source Future Source

Future Source

Future Source Future Source Future Source Future Source Future Source

slide-22
SLIDE 22

Impact of the Digital Economy: NYC Freight Data Sample - Selection Area

  • Selected all trips the start, end or pass

through the box

  • Only selected fleet data and only freight

profiles (i.e., no taxis)

  • Selected all weight classes
slide-23
SLIDE 23

OSM Map Layer Only

slide-24
SLIDE 24

One Day of Freight Data in New York City

slide-25
SLIDE 25

One Week of Freight Data in New York City

slide-26
SLIDE 26

One Week of Freight Data in New York City – Zoomed Detail

slide-27
SLIDE 27

One month of Freight Data in New York City

slide-28
SLIDE 28

San Francisco Water Authority

  • Problem

blem: Water Main Breaks Throughout the City

  • Ap

Approa

  • ach

ch: Assess Impacts

  • f Heavy Trucks on Water

Main Breaks

  • Data Used:

ed: Combine Freight O-D Data with Water Main Locations and Break Locations Water Mains -----

  • Freight Waypoints
slide-29
SLIDE 29

Return to Normal Analyses for Incident Management Programs

  • Important for TSM&O/ICM Applications
  • New Performance Measurement
  • Important for Toll Road Operators
  • Possible Insurance Claim for Insured Toll Authorities for

Revenue Loss

Image Source: Press Democrat

slide-30
SLIDE 30

SH 183 Accident Near MOPAC – Saturday, November 11, 2017

  • November 11, 2017
  • On NB SH 183 near MOPAC
  • 3:30 pm Jeep jumps center median into SB lanes
  • Two dead at scene
slide-31
SLIDE 31

SH 183 Accident Near MOPAC – November 11, 2017

Accident occurs 3:30 pm Return to normal ~10:30 pm

slide-32
SLIDE 32

Georgia Dome Origin-Destination Assessment

  • Looked at December 2017 due to Atlanta

Falcons Home Schedule

  • Three Home Games
  • December 3, 7 and 31
  • Vikings, Saints, Panthers
slide-33
SLIDE 33

Georgia Dome December 2017 Waypoint Data

33

slide-34
SLIDE 34

Georgia Dome December 2017 Waypoint Data

slide-35
SLIDE 35

Oroville Dam Mandatory Evacuation

35

  • Approximately 70 miles north of Sacramento
  • Approximately 180,000 people evacuated
  • Impacted three counties Butte, Sutter and Yuba
  • Mandatory evacuation lasted three days
slide-36
SLIDE 36

NB CA 99/149 and SB CA 70 Exiting Oroville – Sunday, February 12, 2017

36

Manda dator

  • ry

y evacu cuati tion

  • n order

der given en at 4:58 8 pm 2/12/1 2/17

slide-37
SLIDE 37

Questions?

37

Gary Carlin, PE, PMP, PTP gary.carlin@inrix.com 425-495-5476