Location: Arlington, VA (GMU/Arlington)
Date: November 30-December 1, 2010

[Day 1, Agenda Item 1-6] Applications and Data Environments Breakouts

1. Arterial Data Environment

This data environment consolidates and organizes data from vehicles (light, transit, freight, non-motorized, and emergency), mobile devices and roadside infrastructure along a signalized arterial facility up to 10 miles in length.  Although the facility is primarily bi-directional in nature, the data environment encompasses data from all approaches at intersections located along the length of the facility.  On-street parking is allowed along some portions of the facility itself during specific times of day/days of the week.  Bus-Only lanes can be found on the mainline arterial facility.  Travel demand on the facility is highly variable by time of day and day of week.  Travel demand also varies in terms of vehicle type.  There is significant truck and delivery vehicle traffic and some of these vehicles can block a lane of traffic while loading and unloading when parking is not available. Bike lanes may be present on either the facility itself or on crossing facilities, and crosswalks for pedestrians are present in each intersection.  Periods of high pedestrian demand are also prevalent, particular before and after events held at venues directly adjacent to the facility.  The facility is a designated snow emergency route and must be cleared of parked vehicles and passable during winter precipitation events.

11 Applications:

Facilitators:

Steve Mortensen (FTA)
Ben McKeever (FHWA Office of Operations R&D)
Meenakshy Vasudevan (Noblis)

2. Freeway Data Environment

This data environment consolidates and organizes data from vehicles (light, transit, freight and emergency), mobile devices and roadside infrastructure along an uninterrupted flow (freeway) facility up to 15 miles in length.  Although the facility is primarily bi-directional in nature, the data environment encompasses data drawn from all interchanges located along the length of the segment, including ramp facilities and arterial segments that provide access to these ramps.  Lanes on the mainline facility or ramps may have access restrictions (e.g., HOV or Truck Only) and tolls may be collected on some or all lanes along the length of the freeway segment.  Some sections of the freeway may experience partial or complete flooding during intense rain events.

8 Applications:

Facilitators:

Gene McHale (FHWA Office of Operations R&D)
Kate Hartman (ITS JPO)
Mike McGurrin (Noblis)

3. Corridor Data Environment

This data environment consolidates and organizes data from vehicles (light, transit, freight and emergency), mobile devices and roadside/wayside infrastructure in a sub-regional corridor up to 30 miles in length.  The sub-regional corridor carries primarily directional travel demand (inbound or outbound) depending on time of day and day of week.  Key features of the corridor include a collection of parallel arterial and freeway facilities, as well as a dedicated transit (BRT or light rail) facility.  All stations along this transit facility have bus feeder networks and some stations provide parking facilities. Although the facility is primarily bi-directional in nature, the data environment encompasses data drawn from all facilities in a connected network within the corridor boundaries, including crossing arterial, freeway or transit facilities.  Particular roadway facilities within the corridor may have access restrictions (e.g., HOV or Truck Only) and tolls may be collected on some or all lanes of these facilities.  A fleet of incident response vehicles are available to be dispatched within the corridor. Note that the Corridor Data Environment utilizes data from one or more federated Arterial or Freeway data environments.

12 Applications:

Facilitators:

Brian Cronin (DCM, ITS JPO)
Bob Rupert (DMA, FHWA Office of Operations)
Carolina Burnier (Noblis)

4. Regional Data Environment

This data environment consolidates and organizes data from vehicles, mobile devices and roadside infrastructure in a regional, state-wide, rural, multi-state, or national transportation system.  The Regional Data Environment spans a network of subsidiary sub-networks and may utilize data from one or more federated Corridor Data Environments or federated Arterial or Freeway data environments.  The Regional Data Environment includes roadway sub-networks (arterial, freeway, or rural), parking facilities, and an integrated transit sub-network (comprising rail, ferry, and bus sub-networks).  Particular roadway facilities within the network may have access restrictions (e.g., HOV or Truck Only) and tolls may be collected on some or all lanes of these facilities. Weather-related or incident-related closures are infrequent but significant events, potentially impacting operations on roadway sub-networks and/or transit sub-networks.  The regional transportation system carries both significant traveler demand and supports time-critical goods movements between intermodal facilities.  Directional passenger and freight demand patterns vary by time-of-day, day-of-week, and season.

11 Applications:

Facilitators:

Paul Pisano (DCM, FHWA Office of Operations)
Randy Butler (DMA, FHWA Office of Freight)
Karl Wunderlich (Noblis)

Data Environments – Supplementary Considerations for Workshop Exercises

(Note:  These notional considerations are for purposes of the workshop exercises ONLY.
They do not represent connected vehicle program targets or expected near-term or long-term states)

Foundational Assumptions

• All Dedicated Short-Range Communication (DSRC) data are anonymous.
• Here-I-Am (HIA) messages do not contain Personally-Identifiable Information (PII).
• For purposes of the workshop, non-DSRC data are considered anonymous;
• No data is made available for law enforcement purposes.

Travelers/Mobile Devices

Near-Term (0-3 Years)

• 50% of travelers carry GPS-enabled mobile devices
• 5% of travelers opt-in to configure mobile devices to contribute persistent anonymous ID GPS position data, every 5 minutes
• No Vehicle-Device integration -- data stream includes devices not carried in travel (e.g., on the night stand while the person is sleeping in bed).

Long-Term (10+ years)

• 90% of travelers carry GPS-enabled mobile devices
• 15% of travelers opt-in to configure mobile devices to contribute persistent anonymous ID GPS position data, every 5 minutes1
• Vehicle-Device integration
• 5% of travelers opt-in to configure mobile devices to broadcast HIA via DSRC when in motion and not integrated with a vehicle
• 5% of travelers opt-in to contribute origin-planned destination and trip context data (just prior to trip start);  actual destination, decision and trip outcome data (just after trip finish)

Light Vehicles

Near-Term (0-3 Years)

• 5% of light vehicles opt-in to contribute persistent, anonymous ID GPS position data, every 5 minutes
• 1% of light vehicles act as advanced probe vehicles
• HIA message via DSRC every 0.1 second
• Vehicle status data (J2735) every 5 minutes
  (e.g., turn signal, exterior temperature, speed)

Long-Term (10+ years)

• 25% of light vehicles opt-in to contribute persistent, anonymous ID GPS position data, every 5 minutes
• 50% of light vehicles act as advanced probe vehicles
• Vehicle-Device data integration

Transit (Bus/Rail) Vehicles

Near-Term (0-3 Years)

• 10% of transit vehicles opt-in to broadcast HIA via DSRC and provide GPS vehicle location, every 30 seconds
• 5 % of transit vehicles opt-in to transmit internal video surveillance data and vehicle health data (as needed) and report passenger counts at departure from each stop/station.
• 1 % act as advanced probe vehicles, providing:
• Vehicle speed, acceleration, and weather data, every 30 seconds
• External video surveillance data, as needed

Long-Term (10+ years)

• 50 % of transit vehicles opt-in to broadcast HIA via DSRC and provide GPS vehicle location, every 30 seconds
• 25 % of transit vehicles opt-in to transmit internal video surveillance data and vehicle health data (as needed) and report passenger counts at departure from each stop/station.
• 15% conduct real-time open payment transactions at every bus stop served
• 15% act as advanced probe vehicles, providing:
• Vehicle speed, acceleration, and weather data, every 30 seconds
• External video surveillance data, as needed
• Vehicle-Device data integration

Freight Vehicles

Near-Term (0-3 Years)

• 50% of freight vehicles opt-in to contribute GPS position data, every 15 seconds
• 10% act as advanced probe vehicles
• HIA via DSRC
• Vehicle status and credentialing/weight data every 5 minutes

Long-Term (10+ years)

• 80% of freight vehicles opt-in to contribute GPS position data, every 15 seconds
• 50% act as advanced probe vehicles
• HIA via DSRC
• Vehicle status and credentialing/weight data every 5 minutes
• Vehicle-Device data integration

Emergency Vehicles

Near-Term (0-3 Years)

• 80% act as advanced probe vehicles
• HIA via DSRC
  (includes EV identifier)
• Vehicle status every 5 minutes

Long-Term (10+ years)

• 100% act as advanced probe vehicles
• HIA via DSRC
  (includes EV identifier)
• Vehicle status every 5 minutes
• Vehicle-Device data integration

Roadside/Wayside Infrastructure

Near-Term (0-3 Years)

• RWIS, loop detectors, other roadside sensors as currently deployed (Year 0)
• 10% of signalized intersections act as advanced intersections
• DSRC-capable RSE for 2-way communication with vehicles
• Broadcast Signal Phase and Timing data via DSRC
• 1% of transit parking facilities provide utilization data (spaces used/remaining), every minute

Long-Term (10+ years)

• RWIS, loop detectors, other roadside sensors as currently deployed (Year 0)
• 50% of signalized intersections act as advanced intersections
• 25% of transit parking facilities provide utilization data (spaces used/remaining), every minute

 [Day 2, Agenda Item 2-3] Applications and Impacts Breakouts

1. Environmental

This breakout group will identify promising applications to achieve goals related to transportation-related environmental impacts.  For the purposes of this breakout, this is defined as the capability to reliably deliver goods and passengers safely through the transportation system at current levels with transformative reductions in environmental impacts resulting from transportation-related emissions and fuel consumption.

9 Applications:

Facilitators:

Gene McHale (DCM, FHWA Research and Development)
Marcia Pincus (AERIS, ITS JPO)
Meenakshy Vasudevan (Noblis)

2. Productivity

This breakout group will identify promising applications to achieve goals related to overall system productivity.  For the purposes of this breakout, this is defined as a transformative capability to reliably deliver the largest aggregate net value of goods and passengers through the transportation system within the current system footprint and without increased environmental impact, fuel use, or safety risk.

9 Applications:

Facilitators:

Randy Butler (DCM, FHWA Office of Freight)
Ben McKeever (DMA, FHWA Research and Development)
Carolina Burnier (Noblis)

3. Mobility

This breakout group will identify promising applications to achieve goals related to enhancing individual mobility.  For the purposes of this breakout, this includes a transformative ability for travelers of all types to access the largest possible set of destinations reliably and predictably through the transportation system without increased environmental impact or safety risk.

10 Applications:

Facilitators:

Steve Mortensen (DCM, FTA)
Bob Rupert (DMA, FHWA Office of Operations)
Karl Wunderlich (Noblis)

4. Safety and Security

This breakout group will identify promising applications to achieve goals related to enhancing traveler safety and security.  For the purposes of this breakout, this is specifically defined as a transformative ability to reduce safety risks for travelers and pedestrians and enhance system security while maintaining current levels of traveler mobility, system productivity, and without increased environmental impact. Note that active safety applications (low-latency vehicle-to-vehicle applications) are out of scope in this breakout group.

9 Applications:

Facilitators:

Brian Cronin (DCM, ITS JPO)
Kate Hartman (DMA, ITS JPO)
Mike McGurrin (Noblis)