What is Crowdsourcing for Advancing Operations?
Crowdsourcing is focused on employing the collective experience of a number of people to manage a process. Crowdsourced data can be obtained whenever and wherever people travel, allowing agencies to capture in real time what happens between sensors, in rural regions, along arterials, and beyond jurisdictional boundaries. Agencies at all levels can use crowdsourced data integrated from multiple streams to optimize roadway use for reduced congestion and increased safety and reliability.
State and local transportation systems management and operations (TSMO) programs strive to optimize the use of existing roadway facilities through traveler information, incident management, road weather management, arterial management, and other strategies targeting the causes of congestion. TSMO programs require real-time, high-quality, and wide-ranging roadway information. However, gaps in geographic coverage, lags in information timeliness, and life-cycle costs for field equipment can limit agencies' ability to operate the system proactively.
Benefits
Public agencies at all levels are increasing both their situational awareness and the quality and quantity of operations data using crowdsourcing, which enables staff to apply proactive strategies cost effectively and make better decisions that lead to safer and more reliable travel while protecting privacy and security of individual user data.
Learn more about this EDC-6 Innovation.
How NJ Incorporates Crowdsourcing for Advancing Operations
Stage of Innovation: ASSESSMENT (Pilot Study)
(December 2021)
The NJDOT is institutionalized in its use of vehicle probe data to support traffic incident/operations management and planning for operations. New Jersey has been a leader in using crowdsourcing data to advance operations since 2008. The following activities occurred in under previous EDC rounds:
Acquired Two Probe Data Sets. Crowdsourcing data from INRIX and HERE (via TRANSCOM partnership) is used for real-time performance management and traffic monitoring for roadway management and event after actions.
Incorporated Crowdsourcing Data Sets. TRANSCOM tools such as Data Fusion Engine (DFE) and Selected Priorities Applied to Evaluate Links (SPATEL) aggregate all available data sources for operations, analysis, and performance measures.
Piloted a Connected Vehicle Program. The pilot study funded through a STIC Incentive Grant seeks to protect safety service patrol staff by alerting drivers in real-time of their presence at an incident site through apps such as Waze and Google.
What's Next?
For the EDC-6 initiative, the NJDOT submitted and was awarded a STIC incentive funding grant to collaborate with a crowdsource information service provider (ISP). The goals of the pilot project include:
Utilize the data set provided by the crowdsource ISP to gain a better situational awareness of traffic incidents on the interstates/state highways.
Increase the availability of data to complement the 511 traveler information system for timelier traveler information.
Analyze the crowdsource data by comparing it to the State’s crash records to assist in determining the accuracy of the crowdsourced data.
Click for the Crowdsourcing for Operations Fact Sheet.
CROWDSOURCING FOR ADVANCING OPERATIONS: NEW & NOTEWORTHY
National Operations Center Webinar to Feature NJDOT’s Commercial Vehicle Alerts Initiative
Adventures in Crowdsourcing Webinar Series
Innovation Spotlight: Testing and Deploying ITS Solutions for Safer Mobility and Operations
STIC Incentive Grant Award: Crowdsourcing Traffic Data to Optimize Roadway Monitoring
DVRPC’s Sidewalk Inventory and Crowdsourcing Platform
Final Report Released for the Connected Vehicles Program Pilot Testing of Technology for Distributing Road Service Safety Messages from Safety Service Patrols
How SJTPO Refined Their Congestion Management Process with Crowdsourced Data
Tech Talk! Webinar: Crowdsourcing for Local Operations
Connected Vehicles Program Pilot Testing of Technology for Safety Service Patrol Workers Continues
Making Work Zones Smarter: Data-Driven Decision Making
