Operational Strategies toward Greener Highways

1
Operational Strategies toward Greener Highways

• Alixandra Demers
• North Carolina State University
• November 8, 2005
• Green Highways Forum, College Park, MD

2
Outline

• Greening Methods
• Environmental results of other Advanced Traveler
  Information System (ATIS) projects
• Capital District ATIS project
• Experiment background
• Changes in network use
• User perceptions
• Future opportunities

3
Greening Methods

• Roadway design
• Vehicle technology
• Operational Strategies
• changes in control
• more effective capacity assignment
• better route guidance My Focus Today

4
Environmental Results of ATIS

• Improvements in the way vehicles traverse the
  network can produce significant reductions in
  fuel consumption and green house gas emissions.

5
ATIS Benefits
Ref Peng Beimborn (2000)
6
Capital District ATIS Project

• Experiment background
• Changes in network use
• User perceptions

7
Research Team

• Academic partners
• Rensselaer Polytechnic Institute
• Cornell University
• Polytechnic University
• CUBRC (CALSPAN / University of Buffalo Research
  Center)
• Public partners
• FHWA
• NYS DOT
• CDTC
• CDTA
• Corporate partners
• ALK Technologies, Inc.
• Annese and Associates
• Consensus Systems Technologies
• Sprint

• Rensselaer County Economic and Community
  Development
• Hudson Valley Community College

8
Project Overview

• Precedent 1st time in the world for real time
  data collection from vehicles and dissemination
  to vehicles of congestion avoidance information
• Focus operations, users, observability, transfer
  of information to travelers
• Target locations small to medium-sized urban
  areas

9
Setting

• 3-month field experiment in Upstate NY
• 200 participants
• 80 Tech Park employees
• 120 HVCC staff students
• Techy travelers
• Journey-to-work
• Congested links
• Freeways signalized arterials
• Path choices exist

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The In-Vehicle Tools
CoPilot GPS device Talks to satellites,
determines where you are
Sprint PCS Vision connection card and battery
pack Sends your routing question to server for
an answer
Pocket PC with 256 MB SD card Navigates you by
voice map
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Information Exchange Decision-making

• GPS unit locates drivers initial position
• Driver provides destination. Device queries
  server.
• Server sends current travel times table
• Vehicle sends location, notifies server of
  passing monuments (virtual toll gates)
• Processed link travel times.
• Updates returned to vehicle Re-route or not

5
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6
3
1
4
Destination
12
Changes in Travel Times Distances

• Anecdotal perceptions
• Pre- post-experiment estimates from surveys
• During experiment actual travel times distances
  from weekday morning commute

13
What Weve Heard So Far
I'm very impressed with the CoPilot program thus
far. The directions are accurate and it adapts
quickly to route changes.
I find it interesting how willing I am to listen
to a machine tell me which route to take
I like using it for when I have no idea on how to
get somewhere, and it is good for my normal route
because it keeps me out of traffic on route 4.
This thing is awesome. I was a little skeptical
at first but once i got the hang of it I dont
know how I went along without it. I think any
student commuting to school will benefit from
this.
Feel more secure in making changes and using
alternate routes, since I'm confident that
CoPilot will get me to work!
It is great, it took a while to trust it telling
me where to go, but i like it because i cant get
lost! Thanks.
14
Driver Perceptions of Time
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Actual Travel Times Raw Data Issues

• This was a real-time data collection
  dissemination experiment.
• We are culling through the data now.
• It appears there are pieces of the software that
  created unintended extra data entries
• A program edit later removed these duplicates.
• Presented here are select cases to see what
  happened to their trip behavior over the 90-day
  study.
• Look at about 30 users beg/end of study.
• Also look at one day (say a Tuesday), m2m data
  and create picture of what happened and again
  look at all Tuesdays. Think of animating in
  ArcGIS for trip length vs. trip time scatter plot

Hi Distance Lo
Hi Lo

• 90

Day of Experiment
Travel Time
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Actual Travel Times Driver 1

• Early Same route time
• Later Shorter travel times observed

17
Actual Travel Times Driver 2

• Early Scatter of travel times
• Later More consistent travel times

18
Actual Travel Times Driver 3

• Early Scatter of travel times
• Later Similar to Driver 2 with more consistent
  travel times. New upper bound lowered

19
Actual Travel Times Driver 4

• Early Scatter of travel times distances
• Later Clustering of more consistent travel times
  distances

20
Future Opportunities

• Moving beyond the prototype
• Real-time travel times shared between vehicles
  through multiple softwares
• Sharing time-based road restrictions (e.g. school
  zone speed limits)
• Create Green Regions by implementing ATIS and
  other Intelligent Transportation Systems in key
  environmentally-challenged areas

21
Defining a Green Region

• In area with densest travel, increase intensity
  of ITS services

22

• Contact information
• Alixandra Demers
• North Carolina State University
• Dept. of Civil, Construction, Environmental
  Engineering
• 208 Mann Hall/ 2501 Stinson Road
• Raleigh, NC 27616-7908
• ademers_at_unity.ncsu.edu