Connected and Automated Vehicles: Where Are We Going and What Happens When We Get There?

COLLABORATE. INNOVATE. EDUCATE.
Connected and Autonomous Vehicles:
Where Are We Going and What
Happens When We Get There?
Dr. Chandra Bhat & James Kuhr, Esq.
Acknowledgements: TxDOT, D-STOP NCTCOG, Humboldt
Award, Dr. Ram Pendyala, Dr. Kostas Goulias, all of Dr. Bhat’s
graduate/undergraduate students

CTR Research
• Overview
• Autonomous
Technology
• Connected
Technology
• CARSTOP
project
• Adoption
• Societal
Effects
• Planning

Definitions
• NHTSA – National Highway
Transportation Safety
Administration, they are
the federal regulating body
for autonomous vehicles
• Autonomous – A vehicle that can operate, in some
manner, without constant direction from the driver
• Connected – A vehicle that can communicate with
other vehicles and infrastructure
• Ridesourcing – the new name for Ridesharing

Levels of Autonomy
Level 1
Level 2
Level 3
Level 4
Adaptive
Cruise Control
Adaptive Cruise
Control + Lane Assist
Open Road Automated
Vehicle
Generally Hands
Off Driving
IncreaseinRoadwaySafety
IncreaseinNetwork
Effects
Level 5

Did you know?
• All New 2018 Vehicles Must Have A Back-Up Camera
• Roughly 200 people are killed each year and another 14,000
are injured in so-called backover accidents, when drivers
reverse over another person without noticing him or her.
• 20 Automakers (99% of the US market) have agreed to make
automatic braking standard by 2022
• IIHS estimates that automated braking at full penetration
would have prevented 700,000 crashes in 2013 (13% of all
crashes)
• “The data show that the Tesla vehicles crash rate dropped by
almost 40 percent after Autosteer installation.” – NHTSA Report
• Tesla expects a 90% drop with Autopilot 2
• Tesla is selling insurance in Australia and Hong Kong

AUTOMATED VEHICLE
TECHNOLOGY

LIDAR
Produces a 360 degree 3d model
of the surroundings
Video Camera
Monitors frontward, lane
departure and reads traffic
signals
Radar
Monitors surroundings
Odometry Sensors
Monitors vehicle distance
travel and speed
GPS
Tracks the car location
geospatially
Ultrasonic
Senses at low speeds
Internal
CPU
V2V, V2I
Communication
Connects with other cars and
supporting infrastructure
Autonomous Vehicle Technology

LIDAR

Cameras Radar

GPS
GPS position (white box) vs. Google Car
Ultrasonic and Odometry
CPU

LIDAR vs Camera

The car will identify the vehicle in front of it and match speeds to maintain
a safe following distance (set by the user) while not exceeding a certain
speed (also set by the user)
Adaptive Cruise Control
Automatically adjust speeds in a traffic jam, including braking to a full stop,
and handles the steering. Driver must stay alert, but does not have to
touch the wheel or pedals.
Traffic Jam Assist
Alerts the driver when the system detects that the vehicle is about to leave
its lane and can automatically correct the steering and keep the car on
course
Lane Keep Assist
The car will detect panicked breaking and apply more pressure to the
brakes to stop the car faster.
Emergency Brake Assist
Automatically parallel parks a car, as long as the gap is 1.2 times the size of
the car.
Parking Assist
Automatically applies the brakes for obstacle avoidance.
Auto Braking
Semi-autonomous features are safety based – and their incorporation in
current models will begin to reduce accidents in the next 5 to 10 years.
Conclusion
Semi Autonomous Features

US Market Share Level 2 Level 3 Level 4
20% 2016 2021
16% 2016 2021
13% 2016 2020
12%
9% 2016 2020
7% 2016 2018 2020
7% 2016 2020 2030
3% 2016 2020
2% 2016 2017 2021
Level 2 Level 3 Level 4
2016 2025
2016 2021
2016 2030
2016 2017 2018
2016 2016 2018
2020
Others:
Market Shares
2018 (ride sourcing)

CONNECTED VEHICLE
TECHNOLOGY

Dedicated Short Range
Communications (DSRC)

Why Worry About Communication?
• The best autonomous vehicles are connected
vehicles!
• Commercially scorned by the Private Sector
• Value is found in a saturated market, first
mover gains no competitive edge
• Pieces are available off the shelf, now
• Retrofit possibilities are much larger than
autonomy
• Infrastructure is a necessary piece

• Through use of just V2V BSM to warn
drivers, with a mature system, NHTSA
studies indicate that up to 79% of
unimpaired crashes could be avoided.
• Using just a V2I communication system,
NHTSA estimates that 26% of unimpaired
crashes could be avoided.
Benefits
V2X Safety
• By 2029, seven years after the projected phase-in of the light vehicle V2V rule, 60% of all vehicles, or a cumulative
146 million cars, will have DSRC/V2X equipment.
• Adoption of aftermarket/consumer electronics DSRC devices will outpace factory installed DSRC within five to six
years after a NHTSA Light Vehicle V2V rule requiring 100% of all new vehicles to be equipped with V2V.
FHWA ITS JPO Prediction
https://ntl.bts.gov/lib/60000/60500/60535/FHWA-JPO-17-487_Final_.pdf
• Through use of just V2V BSM to warn
drivers, with a mature system, NHTSA
studies indicate that up to 79% of
unimpaired crashes could be avoided.
• Using just a V2I communication system,
NHTSA estimates that 26% of unimpaired
crashes could be avoided.
Benefits
• Together, NHTSA studies indicate that
81% of all unimpaired crashes could be
avoided with a fully mature V2V and V2I
system.

• MLK Speed Limit: 50mph
The Case of Bundyhill
• 19 recorded crashes since 2010
• 41 Units, 77 Persons

• Safety
• Shorter headways/spacing between
vehicles
• Platooning
• Smaller startup lost times at signalized
intersection
• A smoother stop-and-go movement
through intersections without traffic
signals
• String stability in Mixed Traffic
• Data support optimized traffic
management operations
V2X System Performance

Connected Vehicle Adoption Curve
it is worth noting that in case of no regulations, even at 10% annual drop in
technology prices and no-zero, but constant [Willingness To Pay]…83.5% [of
vehicles] would have connectivity in 2045 – Bansal & Kockleman
0
20
40
60
80
100
120
2021 2025 2030 2035 2040 2045 2050 2055 2060
% Veh w/ DSRC % w/ Safety Apps

CAR STOP
COMMUNICATIONS AND RADAR-SUPPORTED
TRANSPORTATION OPERATIONS AND PLANNING

Car Stop – Come see us during the break!
Develop prototypes of Crash Warning & Crash Avoidance (CW/CA) systems that use
joint sensing and communication technologies
22
So that:
• We can determine the sensor and communication equipment and
configuration needed in-vehicle and road-side to maximize roadway safety.
• We can test next generation level communication technology (mmWave)
that may enable an even wider range of safety based communications.

Automated Vehicles and
Transportation
Technology
Infrastructure
Traveler
Behavior

Self-Driving Vehicle (e.g., Google) Connected Vehicle
AI located within the vehicle
AI wirelessly connected to an external
communications network
“Outward-facing” in that sensors blast
outward from the vehicle to collect
information without receiving data inward
from other sources
“Inward-facing” with the vehicle receiving
external environment information
through wireless connectivity, and
operational commands from an external
entity
AI used to make autonomous decisions
on what is best for the individual driver
Used in cooperation with other pieces of
information to make decisions on what is
“best” from a system optimal standpoint
AI not shared with other entities beyond
the vehicle
AI shared across multiple vehicles
A more “Capitalistic” set-up A more “Socialistic” set-up
Two Types of Technology

Regular Traffic Conditions
PRESENT DAY

Icy Patch
PRESENT DAY

Incident
PRESENT DAY

Lane blocking, traffic slow down
PRESENT DAY

Congestion buildup, late lane changes
PRESENT DAY

Congestion propagation to frontage, ramp backed up
PRESENT DAY

V2V

Icy Patch
V2V

Incident: Information propagation
V2V

Preemptive lane changing, freeway exit
V2V

Re-optimization of signal timing, upstream detours
INCIDENT
AHEAD TAKE
DETOUR
V2I

AUTONOMOUS

Icy Patch
AUTONOMOUS

Avoidance of icy patch, no incident
AUTONOMOUS

Traffic slowdown, late lane changing, congestion
AUTONOMOUS

Icy Patch
AUTONOMOUS + V2X

Avoidance of icy patch, no incident
AUTONOMOUS + V2X

Information propagation, preemptive lane changing,
freeway exit
AUTONOMOUS + V2V

Re-optimization of signal timing, upstream detours
INCIDENT
AHEAD TAKE
DETOUR
AUTONOMOUS + V2I

Infrastructure Needs/Planning
Driven By…
 Complex activity-travel patterns
 Growth in long distance travel demand
 Limited availability of land to dedicate to infrastructure
 Budget/fiscal constraints
 Energy and environmental concerns
 Information/ communication technologies (ICT) and mobile platform
advances
Autonomous vehicles leverage technology to increase flow without the
need to expand capacity

Technology and Infrastructure
Combination Leads To…
 Safety enhancement
 Virtual elimination of driver error – factor in 80% of crashes
 Enhanced vehicle control, positioning, spacing, speed,
harmonization
 No drowsy, impaired, stressed, or aggressive drivers
 Reduced incidents and network disruptions
 Offsetting behavior on part of driver

 Capacity enhancement
 Platooning reduces headways and improves flow at transitions
 Vehicle positioning (lateral control) allows reduced lane widths and
utilization of shoulders; accurate mapping critical
 Optimized route choice
 Energy and environmental benefits
 Increased fuel efficiency and reduced pollutant emissions
 Clean fuel vehicles
 Car-sharing

• NHTSA Crash Report: 40% reduction in Tesla
crashes attributable to autopilot
Already Happening: Safety
• IIHS: 2010-14 study on
FCW systems on the
road:
– For 383,868 cars, there
were only 1277 actual
rear end crashes vs
1872 projected
– Extrapolating: that
would be ~390,000 less
crashes with full fleet
penetration

• Tesla surpassed Ford and
GM as most valuable
auto-maker
• Ridesourcing entities are
changing mobility
• Parking Revenue is being
affected at airports and
parking meters
• Transit is taking
advantage of
Ridesourcing
opportunities
Already Happening

BUT LET’S NOT FORGET
TRAVELER BEHAVIOR
ISSUES!

Adoption

0%
20%
40%
60%
80%
100%
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
% of Vehicles Replaced Globally
In 2015, just over 90 million light passenger and commercial vehicles were
produced in the world. Currently, there are over 1.2 billion vehicles in use in
the world. On the roughest possible level: at current production rates, if
every vehicle going forward was autonomous, it would still be 13 years
before all the existing vehicles on the road could be replaced.
Assumption: Current Production capabilities provide a most-aggressive bound
Consider

Concerns about Autonomous Cars
Survey with 1800 individuals in the Puget sound Region:
Type of concern Not concerned
Somewhat
unconcerned
Neutral/doesn’t
know
Somewhat
concerned
Very concerned
Equipment and system
safety
6.9% 4.4% 22.2% 26.9% 39.6%
System and vehicle
security
8.4% 5.0% 26.2% 26.8% 33.7%
Capability to react to
the environment
6.2% 3.2% 18.9% 22.8% 48.9%
Performance in poor
weather or other
unexpected conditions
6.3% 4.3% 21.5% 26.5% 41.4%
Legal liability for drivers
or owners
6.4% 4.2% 24.3% 27.4% 37.7%

Adoption Timelines based
on:
• Previous Adoption of
New Technology
• Consultant Reports
• Behavior studies
…all indicate an extended
period of mixed traffic
Victoria Transport Policy Institute (VTPI)

Planning for the Future

Going to Happen?
Land Use Patterns
• Live and work farther away
– Use travel time productively
– Access more desirable and higher
paying jobs
– Attend better school/college
• Visit destinations farther away
– Access more desirable destinations
for various activities
– Reduced impact of distances and
time on activity participation
• Influence on developers
– Sprawled cities?
– Impacts on community/regional
planning and urban design
Impacts on Household Vehicle Fleet
• Potential to redefine vehicle
ownership
– No longer own personal vehicles;
move toward car sourcing
enterprise where rental vehicles
come to traveler
• More efficient vehicle ownership
and sharing scheme may reduce the
need for additional infrastructure
– Reduced demand for parking
• Desire to work and be productive in
vehicle
– More use of personal vehicle for
long distance travel
– Purchase large multi-purpose
vehicle with amenities to work and
play in vehicle

Impacts on Mode Choice
Automated vehicles combine the advantages of public
transportation with that of traditional private vehicles
What will happen to public transportation?
Also automated vehicles may result in lesser walking and bicycling
shares
• Driving personal vehicle more convenient and safe
• Traditional transit captive market segments now able to use auto (e.g., elderly,
disabled)
• Reduced reliance/usage of public transit?
• However, autonomous vehicles may present an opportunity for public transit and car
sharing
– Lower cost of operation (driverless) and can cut out low volume routes
– More personalized and reliable service - smaller vehicles providing demand-responsive
transit service
– No parking needed – kiss-and-ride; no vehicles “sitting” around
– 20-80% of urban land area can be reclaimed
– Chaining may not discourage transit use

More Impacts: Long Term Facilities
Long Distance Travel
• Less incentive to use public
transportation?
– Should we even be investing in high
capital high-speed rail systems?
– Individuals may travel mostly in the
night
– Speed difference?
Infrastructure Investment in Tolled
Facilities
• How does this affect Traffic and
Revenue?
Parking
• Do we need it?
Highway Design
• Smaller lanes or bigger?

Can We Guide the Future?
• Results show:
 Individuals with green lifestyle preferences and who are tech-savvy are more likely to
adopt car-sharing services, use ride-sourcing services, and embrace autonomous
vehicle-sharing in the future.
 Younger and more educated urban residents are more likely to be early adopters of
autonomous vehicle technologies, favoring a sharing-based service model.
 Individuals who currently eschew vehicle ownership, and have already experienced
car-sharing or ride-sourcing services, are especially likely to be early adopters of AV
sharing services.
 Most effective way to move AV adoption toward a sharing model (rather than an
ownership model) is to enhance neighborhood densification.
 Will new mobility options reduce bicycling, walking, and the use of public
transportation (PT) services?

Mixed Vehicle Operations
Uncertainty in penetration rates of driverless cars
Considerable amount of time of both driverless and
traditional car operation
When will we see full adoption of autonomous?
Depends on regulatory policies
Need infrastructure planning to support both, with
intelligent/dedicated infrastructure for driverless

TEXAS AUTOMATED VEHICLE
PROVING GROUNDS
PARTNERSHIP
Chandra Bhat, Ph.D., P.E.
Director, Center for Transportation Research
1

USDOT AV Proving Grounds
• USDOT seeking to:
– Create national network of proving grounds
– Encourage new levels of public safety
– Establish Community of Practice on testing and
demonstration of best practices
– Accelerate the pace of safe deployment
• January 2017, USDOT designated 10 sites
62

Texas AV Testing Needs
• Automated vehicles are here – and more are
coming!
• How do the public agencies plan for:
– AVs to help with safety and mobility needs
– What is needed to safely accommodate AVs
– Safe introduction of AVs into mixed traffic

National AV Proving Grounds
USDOT selected 10 sites out of 60+ proposals
1. City of Pittsburgh and the Thomas D. Larson Pennsylvania
Transportation Institute
2. Texas AV Proving Grounds Partnership
3. U.S. Army Aberdeen Test Center
4. American Center for Mobility (ACM) at Willow Run
5. Contra Costa Transportation Authority (CCTA) & GoMentum
Station
6. San Diego Association of Governments
7. Iowa City Area Development Group
8. University of Wisconsin-Madison
9. Central Florida Automated Vehicle Partners
10. North Carolina Turnpike Authority
64

Texas Proving Ground Partnership
65

Proving Ground Partners
• Texas A&M, University of Texas, and
Southwest Research Institute
• All are conducting AV research
• All have controlled proving grounds on their
campuses
66

Areas of Research
Connected &
Autonomous
Vehicles
Emerging
Technologies
Policy Impact
Analysis
Pavements &
Infrastructure

Connected & Autonomous Vehicles
Data-Supported Transportation Operations & Planning
Consumer Preferences and
Willingness to Pay for Advanced
Vehicle Technology Options and Fuel
Types
 Objective
– Analyze consumer preferences for
advanced vehicular technologies
 Outcomes
– Heterogeneity in preferences for
wireless internet, vehicle
connectivity, voice command
features
– Less heterogeneity in preferences
for real-time traveler information
Other Projects
 Transit Demand and Routing after
Autonomous Vehicle Availability
 Semi-Autonomous Parking for
Enhanced Safety and Efficiency
 Learning Approach to Beam
Alignment for mmWave Vehicular
Communications

Connected & Autonomous Vehicles
Ensuring Benefits of CAV in Texas
 Objective
– Smart transport technologies
and practices
 Outcomes
– Benefit cost assessment,
e.g. AV managed lanes
– Proactive policy making
• Vehicle licensing
• Liability
• Privacy standards
Other Projects
 Assessing Impact on Traffic and
Infrastructure Needs
 Implications of AVs on Safety,
Design, and Operation of Texas
Highways
 Semi Autonomous Operations, such
as parking and/or transit facilities

Emerging Technologies
Active Traffic Management Strategies
 Objective
– Analyze effectiveness: Varying
congestion levels and data
availability
 Outcomes
– Tools for evaluating where each
strategy works best
– Network level Impacts using
DTA
– Corridor level impacts using
microsimulation
Other Projects
 Integrating Activity Based Modeling
with Dynamic Traffic Assignment
 Smart Cities
 High Precision GPS Tracking for
safer Operations

Policy Impact Analysis
Texas Technology Task Force
 Objective
– Develop a vision for the future
of the Texas transportation
system
 Outcomes
– Network of thought leaders
– Emerging Technology Portfolio
– Strategic Technology Business
Plan
Interconnected
Applications
Next Generation
Vehicles &
Energy
Information &
Communications
Service-Based
Platforms
Other
Technologies
Materials &
Additive
Manufacturing
Infrastructure &
Construction

Policy Impact Analysis
Network Impacts post WMD Attacks
 Objective
– Modeling outages in critical
infrastructure
 Outcomes
– Propagation of degradation
due to contaminants
– Insight on vulnerability of
interdependent networks
Panama Canal Expansion Effects
 Objective
– Predict its impacts on Texas
freight infrastructure
 Outcomes
– Project traffic growth
– Suggest Improvements to freight
infrastructure- roads and rails

Pavements & Infrastructure
Designing Quieter Pavements
 Objective
– Optimal pore size in asphalt
mixes to reduce noise
 Outcomes
– Developing new asphalt mix
and test against noises
– Benefit cost analysis for real
field implementation
Other Projects
 Continuum Approaches to Quantify
Healing in Asphalt Composites
 Asphalt Genome Investigation:
Impact of Different Chemical
Fractions
 Evaluation of Pavement Surface
Micro and Macro-Texture
 Optimal Resource Allocations for
Highway Infrastructure
Maintenance under Budget
Fluctuations

Summary
Broad Areas of Research
 Enhancing safety
 Relieving congestion
 Multi-modal transportation
 Strategic planning
 Improving current
infrastructure management
practices

Our Sincerest Thanks!
We love what we do, and we can do it because of the
generosity of TxDOT among others. Thank you!

Connected and Automated Vehicles: Where Are We Going and What Happens When We Get There?

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