Pavement embedded sensors such as loops and piezos, along with roadside-based radar/light devices and other fix point installed detection systems offer the most reliable traffic volume and classification data. However, it is also known that such point based traditional detection systems are expensive to install and operate. Over the last two decades, new technologies and new data seeming unrelated to vehicle travel have been explored successfully to characterize vehicle travel. It has been proven that such new passively collected data are successful in characterizing traffic patterns. One of the most successful initiatives is the National Performance Management Research Data Set (NPMRDS). The NPMRDS data, which is based on a wide range of non-traditional data, offers vehicle travel time on all the national highway systems in a timely manner and with great reliability, accuracy and precision. Recent researches have also shown the potential and success of using passive data to decipher traffic volumes and other movement data such as origin destination data and modal share data. To promote further development and deployment of such advancements, the Federal Highway Administration is organizing a pooled fund effort with the objective of developing and deploying methods to collect vehicle volume data and classification data through the usage of passively collected data. The term of “passively collected data” means data are not collected through traditional roadway point based sensor detections. The passive data-based non-traditional method, if validated, could reduce costs and improve efficiency for State Departments of Transportation (DOTs), Metropolitan Planning Organizations (MPOs), and local agencies to collect AADT including vehicle class data. It could also reduce risks to employees and contractors who go out to place sensor devices in and on the roadways.

The objective of this pooled fund project is to develop and deploy methods and approaches to obtain vehicle volume and classification data with passively collected data. Volume data refers to the annual average daily traffic (AADT) for all vehicles (both passenger and trucks) covering all roadway functional classes by traffic link or finer levels of segmentation with emphasis on functional classes of minor arterials, collectors, and local roads. Volume data on high volume urban interstates is also highly desired as there is a greater risk for collecting this data in these environments because maintenance of traffic is more expensive and these activities can disrupt normal traffic patterns.

To achieve the objectives, this project will: 1) Develop non-traditional methods and approaches to collect and estimate AADT by vehicle type – all vehicles, trucks, passenger vehicles – based on passively collected data. Passenger vehicles include FHWA vehicle classes 1-3, and trucks include classes 4-13. If possible, trucks could be further categorized into buses and single-unit trucks (classes 4-7) and combination trucks (classes 8-13). Other attributes such as hourly profiles, day of week and month of year factors along with k-Factors will also be produced. The methods and approaches shall be transparent to a degree that public trust can be established and both independent checking and validations can be performed. The methods and approaches shall facilitate governmental agencies in decision makings about calibrating, adopting or rejecting such methods and data with sufficient technical details. 2) Validate the AADT from the newly developed non-traditional methods with FHWA’s Travel Monitoring Analysis System (TMAS) data, Highway Performance Monitoring System (HPMS) data, and other ground truth sources to determine data accuracy and precision. The non-traditional AADT methods will be compared to both the FHWA and AASHTO AADT methods for computing AADT from short-term counts as well as participating State agency current approaches. The validation effort should include different vehicle classes and roadway functional class categories. 3) Provide levels of data accuracy and output formats from micro (e.g., a specific site) to macro (e.g., a specific functional class or a group of roads). Provide insights to improve data accuracy in future efforts. 4) The contractor is encouraged to offer incentives (e.g., reduced fee, additional data) for pooled fund members for future related services when such methods and approaches that are deemed statistically and scientifically sound. Pilot demonstration(s) of methods studied in earlier tasks for pooled fund members as funds are available.

Minimum contribution for any agency joining the pooled fund would be $50,000. Any agency (DOT, MPO or other local agency) is welcome to participate. A 100% SP&R waiver letter is expected.