The optimal performance of transportation networks is increasingly reliant on the quick and accurate collection and dissemination of large amounts of data. Traditional traffic management relies on loop and video data to detect the presence and speed of vehicles at fixed locations, while traditional transit management relies on real-time vehicle location and passenger count information. These methods are expected to continue for the foreseeable future, but there is increasing interest among transportation professionals in the use of CV data to supplement data collected from traditional sources. Specifically, implementation of CV technology could result in the availability of high-quality, high-frequency operations data that would complement existing data streams.
Connected vehicles and certain emerging mobile device technologies broadcast location and motion information to support driver and pedestrian safety. Roadside CV infrastructure can also capture this information from vehicles over a range of around a half-mile or more (provided a clear line of sight) and forward it to management agencies. As the number of CVs and the scope of roadside CV infrastructure continue to grow, management agencies will have access to an unprecedented amount of data capable of significantly enhancing existing capabilities.
Captured data is aggregated and fused with other data (for example, data generated by intelligent transportation system devices) to generate system performance measures, to capture decisions made by travelers, or as input to a decision support system. This would allow a traffic management agency to more effectively pinpoint sources of congestion, apply a localized demand management strategy, or implement adaptive signal timing sequence. A transit management agency could also decide to increase the frequency of vehicles along a certain route, provide on-demand service, or request signal priority, based on the data that it receives.
The continued growth in the deployment of CV devices and roadside infrastructure will result in an expansion of high-quality, real-time, multimodal transportation data. Though currently limited, the opportunity to collect and use CV data for transportation management purposes will continue to grow as CV technology proliferates on vehicles, mobile devices and roadside infrastructure. However, it is important to acknowledge that benefits can be realized only if transportation agencies are prepared to manage and process the CV data that is generated as the technology continues to advance.
Christopher Toth is an associate consultant at WSP USA with experience in systems engineering, connected vehicles, automated vehicles and transportation systems operations. Chris is currently supporting the development of the Smart Columbus Connected Vehicle Environment project, the Smart Columbus Connected Electric Automated Vehicle project, and a U.S. Department of Transportation research project that focuses on Sharing and Using Connected Device Data to Improve Traveler Safety and Traffic Management.
WSP is at the forefront of the development and testing of transportation infrastructure for connected and automated vehicles, and is currently advising transportation agencies across the U.S. on the development and implementation of infrastructure and policies to proactively plan for these vehicles of the future. The firm’s comprehensive capabilities with respect to connected and automated vehicles are presented at www.advancingtransport.com. To find out what we can do for you, contact us at firstname.lastname@example.org.
[To subscribe to Insights, contact the editorial staff at email@example.com.]