Crowdsourced data from multiple streams can be integrated and used in real time for improved operations.
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.
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.
Real-Time, Low-Cost, Valuable Data
Three common sources of crowdsourced data are social media platforms, third-party data providers, and specially developed mobile apps. These data can be passively or actively transmitted and may be quantitative or qualitative in nature. Included is information related to speed, travel time, incident type, travel behavior, public sentiment, vehicular operation, and more. Some data are free with little to no cost to process, while other data can be purchased at a more effective cost point than traditional traffic monitoring equipment (e.g., roadway sensors and cameras).
Because crowdsourced data are obtained whenever and wherever people travel, agencies can capture in real time what happens between sensors, in rural regions, along arterials, and beyond jurisdictional boundaries. Crowdsourced data can often be accessed by traffic management centers (TMC) with minimal or no time lags and is not subject to local sensor or system outages. Complementing crowdsourced data with data integration tools enables TMC operators to focus more quickly on proactively managing emerging events, rather than reacting to them after congestion forms.
Improved Operations. Better traveler information and more proactive and effective operations strategies can lead to reduced traffic congestion.
Increased Safety and Reliability. Crowdsourced data leads to faster and more accurate responses to traffic incidents and other congestion-causing events, reducing the likelihood of secondary crashes.
Cost Savings. Crowdsourcing allows agencies to use their existing intelligent transportation systems infrastructure more effectively and could reduce the need for installing and maintaining additional roadway sensors.
State of the Practice
Most States’ current crowdsourcing efforts are focused on obtaining data from a specific source and applying it to a single application area, such as traffic incident management or traveler information. This can be transformed into a system that gathers multiple streams of real-time data, integrates it, and uses it in multiple application areas for improved operations, as in the following examples:
- The Indiana Department of Transportation uses third-party probe data to actively manage traffic on major highways and corridors of interest. The agency worked with Purdue University to create Traffic Ticker and other dashboard tools that improve real-time operational decision-making and support training and after-action reviews.
- The Kentucky Transportation Cabinet integrates data from multiple sources, including third-party data providers, a mobile app, social media, and crowdsourced weather data, to improve operations and maintenance. Its Big Data System sends system-generated alerts to inform TMC operators of incidents and events earlier, allowing them to better plan their response.
- In Illinois, the Lake County Department of Transportation uses real-time tools and dashboards to integrate crowdsourced data with automated traffic signal performance measure (ATSPM) data to efficiently adapt traffic management systems to transportation system disruptions.