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Airport operations count data are used for a variety of purposes ranging from allocation of Airport Improvement Program (AIP) funding to environmental assessments and budget justification. Operations counts are hard to obtain at small, non-towered airports, which constitute the majority of airports in the United States, and are frequently estimated unscientifically by airport managers. Current acoustic and video counting technology is limited, but with the FAA NextGen mandate for installation of ADS-B Out transponders by Jan. 1, 2020, transponder data is rapidly emerging as a viable data source beyond traditional NextGen applications. To date, the NextGen literature has focused on the use of this technology for navigation, safety, and airspace management. This paper introduces a method of applying ADS-B data to fleet management and airport operations. With a 1090 MHz receiver and appropriate signal processing hardware and software, Mode S and Mode S Extended data can be used to track runway operations and fleet usage in an accurate and cost-effective manner.

On August 7, 2015, a 37 mile stretch of I-65 N from MM 141 to 178 was closed due to a structural evaluation of a bridge. Traffic was detoured onto US-52, SR-26, and US-231 before returning to the highway. In order to monitor delay and congestion on the detour route, a real-time dashboard was implemented in the style of the interstate Traffic Ticker. Throughout the detour, this website was used to monitor congestion in real time and measure the impact of mitigation actions. The improvement in travel can be seen from the addition of temporary signals, retiming of the US-231 corridor, and conversion of US-231 and SR-18 to a two-way stop.

The students of the Field Infrastructure Assessment course evaluated the Mobile Advanced Road Weather Information Sensor by Lufft on behalf of the Indiana Department of Transportation. The device is mounted on a vehicle, takes roadway condition measurements 100 times per second, and aggregates the measurements into one-second intervals. The data is transmitted real-time to the cloud. The class specifically evaluated the following measurements: road condition, surface temperature, and friction. It was found that the MARWIS temperature reading was systematically 4˚F lower than the probe readings. Skid test empirical results were consistent with the MARWIS friction readings. It was also found, using two devices on the back of the test vehicle, that the friction in the wheel track was greater than the friction in the center of the lane, as expected. Lastly, the “chemically wet” road condition was not consistently observed by MARWIS where expected.

Purdue University initiated a bike-sharing program in August 2015 with 13 locations and 50 bikes. The first 14 weeks of the program saw 15,259 rentals for a total of 22,677 hours. The Purdue sustainable transportation staff partnered with Purdue traffic engineering students to monitor usage trends to identify future investment opportunities and changes to the bike sharing contract. In this session we will present the series of analytics performance measures, management dashboards, and changes initiated as a result of this partnership.

Real-time performance measurement of interstate congestion is critical for successful traffic operations management. Monitoring interstate speeds in real time provides the basis for operations engineers to assess interstate system performance at a high level. Crowdsourced probe vehicle data are real-time speeds on roadways collected from cell phones, GPS devices, and vehicle telematics that can be turned into useful performance measures. This project involved the development of a real-time dashboard to display graphs to characterize the congestion history of interstate roadways using the number of miles operating below 45 mph. The playback feature allows for review of conditions during an event such as a road closure or ice storm.

Performance measures are important for managing transportation systems and demonstrating accountability. This session presents a scalable methodology for analyzing arterial travel times, taking into account both the central tendency of the travel time and its reliability. Findings will be presented from a pilot analysis that was carried out for 28 arterials including a total of 341 signalized intersections from across the state of Indiana.