ITS in Academics

ITS Community College Workshop #1
September 20-21, 2017 | ITS America Headquarters in Washington, D.C.

Day 1 Presentation | September 20, 2017

Industry Perspectives on Workforce Needs

Presenter: Jennifer Carter
Presenter’s Org: HERE

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The slides in this presentation include the HERE logo.

Slide 1: Industry Perspectives on Workforce Needs

Jennifer Carter, HERE Technologies
PCB Community College Workshop | September 20, 2017

[This slide contains an aerial photograph looking down upon some very tall city buildings.]

Slide 2: HERE in Numbers

200: Countries mapped
4 of 5: In-car navigation systems in Europe and North America use HERE maps
7,000+: Employees in 56 countries focused on delivering the world’s best map and location technologies
30+: Years of experience transforming location technology
700,000: 3D data points per second per car
100M and counting: vehicles with HERE maps on board
28 TB: map data collected per day
400: HERE cars collecting data for our maps

[This slide contains an infographic of HERE statistics. The data has been reproduced in the list above.]

Slide 3: A history of transforming maps into location technology

1985
- Navigation Technologies founded (NAVTEQ)
1994
- 1^st map for in-car nav
- 1^st map for web
2004
- 1^st map for ADAS
- 1^st map for phone
- 1^st map for Adaptive Cruise Control
2007
- Community mapping
- Offline maps for mobile
2009
- 1^st map for Predictive Cruise Control
- High-precision data collection and map-building technology
- Use of sensor data for map building
2011
- 1^st pure location cloud
2015
- 3 new investors: Audi, BMW, and Mercedes-Benz

[This slide contains a graph that shows an increase in the use of technology to produce maps. The timeline information is reproduced above.]

Slide 4: HD Mapping for Automated Driving

Enables automated driving through precise sub-lane level representation of the road network
Slope and curvature, lane marking types, and roadside objects
Helps with positioning, localization, and automated maneuvering

[This slide contains two images: (1) a graphic of a car with distance sensing sensors, and (2) a photo of a HERE car with a camera mounted on its roof which is used to collect map data.]

Slide 5: Closing the loop: vehicles, agencies, users

[This slide contains a diagram showing the relationship between different modes of transportation (cars, trains, buses) and traffic control equipment and locations (shown with a graphic of multi-story buildings). Arrows indicate that information travels from the cloud (at the center of the overall diagram), which contains the words “Sensor data ingestion, Real-time processing, and Enrichment with location intelligence”), to the transportation modes and locations, and then from the transportation modes and locations back to the cloud.]

Slide 6: HERE’s Open Location Platform solves these challenges:

by pooling anonymized, rich vehicle data
from competing car brands
to create a live depiction of the road network.

[This slide contains a graphic showing a HERE cloud above three rows of cars. There are two arrows that indicate bi-directional data flow between the two: crowd-sourced sensor data from the cars to the cloud and real-time services based on sensor data from the cloud to the cars.]

Slide 7: Safety

HERE Road Signs
HERE Hazard Warnings
HERE Safety Cameras

[This slide contains a two images: (1) a background photo of a car traveling on a curving two-lane road in a wooded setting, and (2) a graphic with a car with “S” tracks next to the words “Caution | Slippery road conditions ahead.”]

Slide 8: Partnering with leading transportation agencies to harness big data for improved safety and mobility

Michigan: Traffic Management
Colorado: Connected Vehicle Pilot Deployment
Iowa: Automated Vehicle & Freight Movement Technologies
Smart Cities: Toronto, Columbus
Finland: C-ITS Localized Safety Messages
Belgium: C-ITS Localized Safety Messages

[This slide contains a graphic showing a world map, covered with small dots, and with larger dots over Finland, Belgium, Michigan, Colorado, and Iowa.]

Slide 9: Example: Iowa DOT Connected and Automated Vehicle Project

Vehicle automation will improve safety
Access to driving environment information beyond on-board sensors will significantly improve the safe operation of AVs
State DOTs and other public sector infrastructure owner operators uniquely positioned—they already provide much of this data to the public today (e.g., 511)

[This slide contains a flowchart showing the information flow from cars, infrastructure, and devices, which is turned into Driving Environment Data, then goes to Data Processing, then to a Living Map, then to Info Streams. Each part of the flowchart is represented with a stylized graphic, and connected with arrows.]

Slide 10: Example: Iowa DOT Connected and Automated Vehicle Project (cont’d)

Working toward development of a “gold standard” guideline for infrastructure datafeeds to support connected and automated:
- The minimum data content (what we need to send)
- The data formats and sending protocols (how we need to send it)
- The data quality description and thresholds (how we will ensure that the data is “good enough”)

Involves a variety of technical skillsets - Product managers, system architects, test engineers, cloud developers, app developers, user experience designers, standards experts, survey designers, data analysts.

Slide 11: Some shifts we’re seeing

Shift from a need for theoretical experience to a need for practical experience
- Hands-on experience often more helpful than a master’s degree
Shift in programming needs
- Shifting from Java to Scala and Python - real need is for deep knowledge around object-oriented programming
Increased need for Data Science/Analytics/AI/Machine Learning
- Supply can’t keep up anymore - computer science and computer engineering degrees in particular
- Technical colleges can help fill the gap

Slide 12: Important skillsets we see a need for

Solid coding experience can support software architects - Scala certification program or similar
Solid understanding of how algorithms work can lead to a role on a support team that augments the AI/Machine Learning PhDs
Data analysts who can make sense of the data can support the data science/analytics team
Associates’ degree in mathematics or statistics is good solid foundation for these roles

[This slide contains a screenshot of an online article with the title “Facebook’s advice to students interested in artificial intelligence.” Overlaid on top of this screenshot are the words “Math. Math. Oh and perhaps some more math.”]

Slide 13: How students can meet these changing needs

Find their aptitude and passion and focus on that - and make that passion show on their resume
- If they’re just doing a degree program to get a job, that’s going to come across
- If they’re spending their free time in the area they’re studying, they’re going to be the most in demand
Get hands-on experience and work on getting both breadth and depth of knowledge
Give specifics to their resume to help it stand out
- Talk about a class they excelled in, about a class project where they used the Google API, or about some programming they did in their spare time for fun

Slide 14: Recruiting

We do a lot of partnerships with schools to recruit at the bachelor’s degree level
Partnered with DeVry University when doing a lot of hiring for our TrueCars
- Found this to be successful when we had a big need
Nanodegree programs - e.g., Udacity

[This slide contains a screenshot of a Udacity website page.]

Slide 15: Thank you

Contact
Jennifer Carter
HERE Technologies
Jennifer.carter@here.com

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