Research
Affiliated AZTrans faculty and student researchers contribute to an array of externally funded research projects in the focus areas of traffic and transportation operations, traffic safety, transportation planning, and bridge design and construction.
Traffic and Transportation Operations
Bridge Design and Construction
Traffic Safety
Transportation Planning
Projects
Analysis of the Operational Impacts of Left-In Left-Out Intersection/Driveway Treatments
Sponsor: City of Scottsdale PI: Dr. Brendan Russo Co-PI: Dr. Edward Smaglik Dates: 10/01/2023-10/31/2024 The City of Scottsdale, Arizona contains numerous examples (approximately 60) of left-in left-out (LILO) treatments at intersections or driveways. An aerial view of a typical LILO treatment in the City of Scottsdale is shown in Figure 1. These treatments are typically applied on arterial roadways with medians and consist of a channelizing island in the median which helps direct vehicles turning left both on to and…
Evaluation of Transportation Safety and Security Barriers in Bicyclist Accessibility
Sponsor: U.S. Department of Transportation, Pacific Southwest Region 9 UTC PI: Steven R. Gehrke Co-PIs: Brendan J. Russo and Edward J. Smaglik A continuation of automobile dependence over the past half-century within American cities has resulted in significant public health, environmental, and economic challenges. The further motivation of bicycling as a utilitarian and sustainable travel alternative has been identified as a viable solution to address societal concerns regarding physical inactivity, climate change, and transportation-related inequities. However, to date, a profound…
Development of Instrumented Bikes: Toward Smart Cycling Infrastructure and Maintenance
Sponsor: U.S. Department of Transportation, Pacific Southwest Region 9 UTC PI: Chun-Hsing Ho Co-PIs: Brendan J. Russo and Steven R. Gehrke Project Report: https://www.metrans.org/assets/research/psr%20final%20report%20nau%20instrumented%20bike%20revised%2011252022.docx.pdf This research project developed an instrumented bike with a sensor logger, a video device (e.g., GoPro), a mobile app, and a cloud server/website to detect real-time quality of cycling infrastructure systems (bike trails, sidewalks, pedestrian pathways, etc.). The instrumented bike is capable of immediately sharing the information with cyclists (road users) and governments/authorities (road managers) such…
Evaluation of Sidewalk Autonomous Delivery Robot Interactions with Pedestrians and Bicyclists
Sponsor: U.S. Department of Transportation, Pacific Southwest Region 9 UTC PI: Steven R. Gehrke Co-PIs: Edward J. Smaglik and Brendan J. Russo Project Report: https://www.metrans.org/assets/research/psr_finalreport_21-16.pdf Information and communication technology advancements and an increased demand for contactless deliveries after the Covid-19 pandemic outbreak resulted in the growing adoption of automated delivery services. Across university campuses, the deployment of sidewalk autonomous delivery robots (SADRs) has provided students, staff, and faculty a convenient last-mile delivery option. However, SADRs traverse campuses on pathways designed…
Analysis of the Safety Impacts of the Left-In Left-Out Median Opening Treatment at Intersections/Driveways
Sponsor: City of Scottsdale PI: Dr. Brendan Russo Dates: 01/01/2021-11/30/2021 Project Report: https://www.scottsdaleaz.gov/Assets/ScottsdaleAZ/Transportation/Analysis+Left+In+Left+Out+-+2021.pdf Over the past few decades the City of Scottsdale, Arizona has installed left-in/left-out (LILO) median opening treatments at approximately sixty intersections/driveways; typically at three-leg intersections or driveways on arterials with medians where the minor leg is stop-controlled. The treatment is relatively unique and consists of a channelizing island with an acceleration length provided for vehicles turning left out of the minor road (these left-turning vehicles then merge…
Journal Articles
A.E. Martinez, C.D. Phair, B.J. Russo, & S.R. Gehrke. (2023) Exploring neighborhood differences in bicycling accessibility to physical and virtual workplaces. Transportation Research Record: Journal of the Transportation Research Board.
Razi, A., Chen, X., Li, H., Wang, H., Russo, B., Chen, Y., & Yu, H. (2023). Deep learning serves traffic safety analysis: A forward‐looking review. IET Intelligent Transport Systems, 17(1), 22-71.
Russo, B. J., Yu, F., & Smaglik, E. J. (2023). Examination of factors associated with fault status and injury severity in intersection-related rear-end crashes: application of binary and bivariate ordered probit models. Safety science, 164, 106187.
Sponsors and Partners
