Connected Vehicle Eco GlidePath at Signalized Intersections

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Contact details

Marcia Pincus, ITS JPO AERIS Program Manager, Osman Altan, Project Manager. John Stark, Leidos, Matt Barth, University of California at Riverside,

Timing and duration of tests

May 2014 – December 2015

Location(s) of tests

Turner Fairbank Highway Research Center (TFHRC) McLean, Virginia, USAs

Tested automation

Tested functionalities

Develop a working prototype GlidePath application with automated longitudinal control for demonstration and future research, and evaluate the performance of the algorithm and automated prototype in terms of energy savings and environmental benefits.

Level of automation tested

SAE / NHTSA Level 1 (Partial automation)

Tested use cases

One driver on a controlled test track interacting (V2I) with one signalized traffic signal.

Tested transport system

Private passenger vehicle

Purposes of testing
  • Assessment of impacts on safety (short-term, long-term)
  • Technical assessment, proof of concept (incl. vehicle, background support systems such as communication)


Definition of baseline

Human driver with no V2I information; advisory speed display provided.

Test design

Controlled field test containing one automobile and one traffic signal.

Algorithm Input

  • Vehicle distance to intersection
  • Vehicle speed
  • SPaT and MAP messages
  • cenario inputs: max speed, acceleration, deceleration, jerk, etc.

Algorithm Output

  • Speed, position profile at 10 Hz
  • Target speed
  • Target acceleration/deceleration transitions
    • Minimize fuel consumption
    • Limit jerk for passenger discomfort

Field Experiment Stages Stage I – Manual-uninformed (novice) Driver Stage II – Manual-DVI Driver (2012 AERIS experiment) Stage III – Automated Driver

Method of testing

Controlled field tests

Test fleet, participants and environment

Number and make of vehicles

Ford Escape Hybrid developed by TORC with ByWire XGV System (one vehicle used in testing)

Description and number of participants/drivers

Multiple drivers and runs

Tested environment and facilities

Road type: Interrupted flow Lanes: 1 Grade: Level Curve: Slight curve Surface: Paved Intersection: Signalized (one traffic signal) Traffic conditions: No other traffic Travel speed: 20 – 40 MPH

Legal and ethical aspects


Duration of testing

Input parameters and assumptions of simulation tests



  • Communication data (V2V, V2I, V2U, etc.)
  • HMI

Key Performance Indicators (KPIs)

Fuel Consumption (g/mi) at various speeds

Situational data available

Timestamp Speed Acceleration Jerk Latitude Longitude Distance to Stop Bar Signal Phase MAP Message SPaT Message

Subjective data collected

Driver interaction with display


Issues that affected the impact assessment

Based on preliminary results:

  • Minimizing controller lag on the vehicle is important.
  • The Eco-Approach and Departure at Signalized Intersections algorithm and vehicle control perform well with 2-meter position accuracy; however, precise positioning is more important near the intersection stop bar
  • “Creep” towards the intersection can feel very un-natural (under scenario 4)

Preliminary Results: Four different drivers were part of the experimentation, each conducting Stage I, II, and II at two different speeds (20 mph and 25 mph)

  • DVI (Stage II) improved fuel economy over uninformed driving (Stage I) by only 5% on average, with a wide range of responses (18% standard deviation)
  • Some drivers with the DVI (Stage II) performed worse than uninformed driving (Stage I)
  • Automation (Stage III) improved fuel economy over uninformed driving (Stage I) by 20% on average, within a narrow range of responses (6% standard deviation)

GlidePath Project Report:

Connected Vehicle Eco GlidPath at Signalized Intersections, in

Eco-Approach and Departure at Signalized Intersections, in (this is a generic architecture for applications similar to GlidePath)

Other things to report

Potential Next Steps:

  • Multiple equipped vehicles (and unequipped vehicles) at single intersection
  • Integration of V2V cooperative adaptive cruise control (CACC) capabilities
  • Multiple intersections / corridor
  • Controlled environment
  • Real-world corridor with traffic
  • Actuated Traffic Signal Timing Plans
  • Consideration of queue lengths (and dissipation of queues) at the stop bar
  • The Federal Highway Administration (FHWA) has initiated a project with CAMP* under the V2I Program to further assess this application
  • CAMP: Crash Avoidance Metrics Partnership, a consortium of 10 automakers
Method of testingControlled field tests +
Purpose of testingAssessment of impacts on safety (short-term, long-term) + and Technical assessment, proof of concept (incl. vehicle, background support systems such as communication) +