Benefit

Volunteer drivers equipped with CV technologies saw immediate value in queue warning applications.

Experience implementing and evaluating connected vehicle (CV) technologies.


06/19/2015
I-5 Tukwila to Edmonds; Seattle; Washington; United States


Summary Information

This project demonstrated the Intelligent Network Flow Optimization (INFLO) system in Seattle, Washington. The system was designed to collect vehicle speed data from connected vehicles as well as infrastructure based speed detectors, and provide queue warning, speed harmonization, and weather responsive traffic management (WRTM) messages to connected vehicle drivers in a fully operational highway traffic environment.

Applications implemented
  • Speed Harmonization (SPD-HARM) This application was intended to fuse data from infrastructure based sensors with data from connected vehicles, identify sections of the roadway with deteriorated performance, and recommend appropriate speeds to vehicles in real-time to minimize traffic stream turbulence and improve throughput and safety.
  • Queue Warning (Q-WARN) This application was designed to fuse vehicle speed data collected from infrastructure and connected vehicles and generate queue warning messages disseminated through DMS signs and connected vehicles.
  • Weather Responsive Traffic Management (WRTM) This application was designed to recommend travel speeds based on the prevailing road weather conditions.
Hardware and software elements deployed
  • Connected Vehicle Equipment (In-Vehicle System) A dedicated short range communication (DSRC) radio was used to send and receive basic safety messages (BSMs) between vehicles, and share vehicle speed data with roadside infrastructure. A smartphone connected to DSRC radio (via Bluetooth) served an in-vehicle user interface. The smartphone was also connected to the internet using a cellular connection and configured to receive and process traveler information messages (TIMs).
  • Roadside Units (RSUs) A commercially available RSU was tested. The RSU was equipped with DSRC to connect in-vehicle systems with a virtual Traffic Management Entity (TME).
  • Virtual Traffic Management Entity (TME) The virtual TME included hardware and software components required to implement data collection, information management, and CV applications used during field testing
Evaluation Methodology

Researchers recruited 21 volunteer participants from the local area in Seattle. They agreed to have on-board INFO equipment installed in their private vehicles and perform a variety of driving scenarios during peak periods on I-5 during the week of 1/12/2015. The evaluation team collected vehicle speed data from both the WSDOT infrastructure based speed detector system and in-vehicle INFLO equipment. The data collected were processed by the evaluation team in real-time, and Q-WARN and SPD-HARM messages were sent to drivers to as needed to accommodate prevailing traffic conditions.

A smartphone graphical display mounted on the dashboard of each CV equipped vehicle provided drivers with the following types of information.
  • SPD-HARM Recommended Speed
  • Q-WARN Queue Ahead message with distance to the back of queue
  • Q-WARN In-Queue message with distance and estimated time to the end of queue
  • Vehicle weather and other data.
At the conclusion of testing, participants were requested to fill out a post demonstration questionnaire and receive agreed upon compensation for participation.

Findings

As a prototype, the INFLO project successfully demonstrated connected vehicle data capture and dissemination functionality using both cellular communications and DSRC communications. Although not rigorously tested, performance in terms of latency and processing speed was sufficient to support CV functionality in an operational traffic environment. In general, the process of capturing vehicle data, storing it in the database, processing it, and then delivering basic safety messages (BSMs) took less than 10 seconds. Drivers could expect to receive messages at least a mile in advance of the back of a queue. In one case, the INFLO prototype system detected a queue three minutes earlier using connected vehicle data than was achieved using infrastructure data only.
  • The assessment of survey data collected from driver participants (n=21) indicated that drivers saw immediate value in the Queue Ahead and In-Queue messages that informed them of the location and duration of congestion and queues. Participants were able to take action in advance of congestion, reducing the need to slow down or stop suddenly.
  • The value of Speed Harmonization messages, however, was not clear to participants.

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Source

Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and Queue Warning

Author: Stephens, Denny; Thomas Timcho; Theodore Smith (Battelle); Kevin Balke; Hassan Charara; Srinivasa Sunkari (TTI)

Published By: U.S. DOT Federal Highway Administration (FHWA)

Prepared by Battelle for the U.S. DOT FHWA

Source Date: 06/19/2015

Other Reference Number: Report No. FHWA-JPO-15-213

URL: https://rosap.ntl.bts.gov/view/dot/3551

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Benefit ID: 2016-01102