Dr. Gayah’s research interests lie in the design, operation, and management of resilient transportation systems to improve the efficiency, safety, and sustainability of travel. His research contributions are divided among two main thrusts.
Thrust 1: Traffic operations
Dr. Gayah’s research in traffic operations seeks to develop and apply novel methods to describe the aggregate outcome of vehicle and infrastructure interactions across large urban transportation systems. This work involves the application of Network or Macroscopic Fundamental Diagrams (NFDs/MFDs), which allow congestion within urban traffic networks to be modeled at the regional level. Dr. Gayah’s theoretical contributions in this area include:
- Identification of instabilities that arise in congested networks and their impacts on MFDs and methods to mitigate these instabilities (Daganzo et al, 2011; Gayah and Daganzo, 2011a; Gayah and Daganzo, 2011b; Jin et al, 2013; Gayah et al, 2014; Gan et al, 2017; Keyvan-Ekbatani et al, 2019);
- Modeling framework to account for uncertainty in aggregate network behavior (Gao and Gayah, 2018);
- Development of methods to estimate MFDs using probe vehicle data (Gayah and Dixit, 2013; Nagle and Gayah, 2014; Tsubota et al, 2015; Du et al, 2015) and traffic flow theory (Xu and Gayah, 2020);
- Assessment of how various network features may impact an MFD, including signal coordination (Girault et al, 2016), street layout (Muhlich et al, 2015), and hierarchical network structures (ongoing);
- Relationship between MFDs and network-wide safety performance (Alsalhi et al, 2018); and,
- Development of regional traffic control strategies using MFD-based frameworks (Yocum and Gayah, 2021; Zhou and Gayah, 2021).
Of note, Dr. Gayah has applied MFD theory to obtain practical recommendations on street network design. This research provides insights into the debate between one-way vs. two-way street layouts in urban areas and has identified hybrid strategies to improve network efficiency via the restriction of left-turns at signalized intersections on two-way street networks (Gayah and Daganzo, 2012; Ortigosa et al, 2015; DePrator et al, 2017; Ortigosa et al, 2019; Yu and Gayah, 2020; Bayrak and Gayah, 2021; Yu and Gayah, 2022). This work has been featured in CityLab, The Conversation, NPR, various podcasts, and several newspapers for cities planning local street network conversions.
Dr. Gayah’s traffic operations research also focuses on vehicle behavior at isolated signalized intersections and signalized corridors. Notable examples of this works include:
- Application of analytical methods to describe aggregated outcomes of vehicle interactions at signalized intersections (Han et al, 2014; Han and Gayah, 2015);
- Development of optimization frameworks to improve signal phasing and timing plans using traditional sensing technologies (Liu et al, 2015; Han et al, 2016; Yu et al, 2017; Yu et al, 2022) and in a Connected and Autonomous Vehicle (CAV) environment (Liang et al, 2018, 2019, 2020a, b, c);
- Extension of existing analytical methods to examine the disruptions caused by bus stops or other temporary obstructions located near signalized intersections (Gu et al, 2013; Gu et al, 2014; Gayah et al, 2015; Wu et al, 2017);
- Development of strategies to mitigate multimodal vehicle interactions to improve intersection efficiency (Xuan et al, 2012; Guler et al, 2016);
- Multi-objective optimization methods at signalized intersections (Hitchcock et al, 2018);
- Development of signal timing performance measures using high-resolution signal data (Guadamuz et al, 2021); and,
- Implementation of deep reinforcement learning for traffic signal control (Wei et al, 2019a, b; Zheng et al, 2019; Zheng et al, 2020).
Research Thrust 2: Transportation safety
Dr. Gayah has participated in numerous projects to quantify safety performance of roadway segments and intersections, as well as to assess the impacts of specific safety countermeasures. Notable examples include:
- Development of regionalized safety performance functions (SPFs) for:
- Various roadway segment and intersection types in Pennsylvania (Donnell et al, 2015; Donnell et al, 2016; Li et al, 2017; Donnell et al, 2018);
- Pedestrian and bicyclists via NCHRP 17-84 (ongoing);
- Freeway facilities with part-time shoulder use via NCHRP 17-89 (Jenior et al, 2021); and,
- Freeway facilities with managed lanes via NCHRP 17-89A (Himes et al, 2021);
- Demonstration of the need for curve-specific SPFs (Gooch et al, 2018) and SPFs that account for bus traffic/presence of bus routes (Guadamuz et al, 2020);
- Estimation of Crash Modification Factors (CMFs) for:
- Horizontal curves on two-lane rural roads (Gooch et al, 2016);
- Setting speed limits lower than engineering recommendations (Gayah et al, 2018);
- Adaptive traffic signal control (Tang et al, 2020); and,
- ITS treatments such as ramp metering, variable message signs, and road weather information systems via NCHRP 17-95 (ongoing);
- Development of macroscopic safety prediction models at the:
- Census tract level via NCHRP 17-81 (Porter et al, 2022); and,
- County-level within Pennsylvania (Yocum and Gayah, 2022);
- Integration of emerging data sources for pedestrian safety analysis (Hamilton et al, 2022);
- Quantification of pedestrian risk factors for systemic safety analysis in North Carolina (ongoing); and,
- Application of surrogate safety measures in transportation safety analyses via NCHRP 17-86 (ongoing).
The results of this research have or are scheduled to be implemented into Pennsylvania’s Publication 638A (which serves as the PA version of the Highway Safety Manual), the safety management processes of other state transportation agencies (including Montana, Virginia, and North Carolina), numerous national guidance documents, the FHWA CMF Clearinghouse, and the second edition of the Highway Safety Manual.