About

Ali Hajbabaie is an Associate Professor in the Department of Civil, Construction, and Environmental Engineering at NC State University, where he is associated with the 'Transportation Systems' and 'Computing and Systems' groups. His research focuses on traffic operations and control in the presence of connected human-driven and self-driving cars, utilizing multi-scale analysis, modeling, and optimization to improve traffic systems. Dr. Hajbabaie has contributed to advancing understanding of cooperative traffic control systems and the development of future mobility systems, including connected and automated vehicles. He has served as the Secretary of the Work Zone Traffic Control standing committee and as the Chair of the Asset Management Subcommittee of the Traffic Signal Systems Committee within the Transportation Research Board of the National Academies of Sciences, Engineering, and Medicine. His academic background includes a Ph.D. in Civil Engineering from the University of Illinois at Urbana-Champaign, along with master's degrees in Industrial Engineering and Civil Engineering from the same university, and a bachelor's degree in Civil Engineering from Sharif University of Technology.

Research topics

• Computer Science
• Artificial Intelligence
• Engineering
• Mathematical optimization
• Real-time computing
• Simulation
• Algorithm
• Mathematics
• Aerospace engineering
• Computer network
• Transport engineering
• Electrical engineering

Selected publications

• Performance Effects of the New Displaced Left Turn and Median U-Turn Combination Design

  Transportation Research Record Journal of the Transportation Research Board · 2025-07-30 · 1 citations

  article

  During the last two decades, transportation professionals have turned to alternative intersection designs with two critical signal phases, such as median U-turn (MUT) and reduced conflict intersections (RCIs), to improve safety and mobility. Intersections with two critical signal phases often have substantial safety and performance benefits. Nonetheless, two-critical-phase designs may lack public acceptance and may have noticeable impacts at some intersection sites owing to the substantial changes required to convert a four-phase traffic signal to a two-phase traffic signal. Conversely, three-critical-phase designs might mitigate some of these issues because only one of the signal phases will be removed (compared with a four-phase signal), but they may still present some of the benefits of two-phase designs. This study utilized microsimulation to analyze the performance effects of a new three-phase design, the partial displaced left turn and median U-turn combination (DLT/MUT combination), a partial DLT, and an existing (conventional) intersection at two intersection sites in North Carolina. The results showed that the partial DLT/MUT combination can outperform the conventional intersections in high-traffic volume scenarios. On average, this new design reduced vehicle travel time by 63% and 21% in comparison to the conventional intersection in case study sites #1 and #2, respectively. It also performed similarly with the partial DLT in operations, but it should be safer and more friendly to people walking and biking, and more cost-effective.

  PublisherDOI

• Safety Analysis of Emerging Alternative Intersection Designs with Three-Phase Traffic Signals

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Integrated column generation for volunteer-based delivery assignment and route optimization

  Computer-Aided Civil and Infrastructure Engineering · 2025-02-12 · 4 citations

  articleSenior author
  PublisherDOI

• Real‐time network‐level traffic signal and trajectory optimization with connected automated and human‐driven vehicles

  Computer-Aided Civil and Infrastructure Engineering · 2025-11-15 · 3 citations

  articleOpen accessSenior authorCorresponding

  This paper introduces a real-time framework designed to optimize intersection signal timing and vehicles’ trajectories across a network of intersections in a mixed environment of human-driven and automated fleets. The network-level optimization model is decomposed into intersection-level sub-models, whose decisions are coordinated through information exchange, aiming to push them toward the network model's optimal solutions. At each intersection, a bi-level framework addresses both the signal timing and trajectory optimization models. A specialized greedy heuristic algorithm is developed for the lower-level problem where optimal connected and automated vehicles (CAVs) trajectories are constructed for a given signal timing plan. At the upper level, all the feasible signal timing plans are created, and the system selects the most effective one to implement. The study integrates the entire solution process into a receding horizon framework to ensure efficient handling throughout the study period. A case study demonstrated the system's capability to adjust signals and trajectories effectively under various traffic demands and CAV market shares. Results showed a reduction in overall arterial delay correlating with higher proportions of CAVs. The proposed system delivered solutions in less than 70 ms, which is significantly faster than the half-second solving time steps, ensuring decisions were made quicker than in real-time.

  PublisherOA PDFDOI

• Traffic Operations Analysis of Seven New Alternative Intersections with Three-Phase Traffic Signals

  Transportation Research Record Journal of the Transportation Research Board · 2025-01-29 · 1 citations

  article

  This paper presents a traffic operational comparison of seven new alternative signalized intersection designs with three critical phases: 1) offset thru-cut, 2) thru-cut, 3) seven-phase, 4) redirect left and through from one minor road (redirect L&T), 5) reverse reduced conflict intersection (reverse RCI), and 6) and 7) two new versions of partial median U-turn (MUT) intersection. These designs will also be compared with the four-phase conventional intersection and two alternatives with two-phase traffic signals: full MUT and reduced conflict intersection (RCI) designs under various traffic conditions at near-capacity levels. Overall, 1,800 simulation runs were conducted to estimate traffic operations under different traffic conditions with varying traffic volumes, traffic distributions, and turning traffic ratios. Traffic signals were optimized for all the tests, and the optimized signal data was imported into microsimulation to evaluate the performance of the 10 intersections included. According to the results, four of the three-phase intersection designs (offset thru-cut, thru-cut, MUT #1, and reverse RCI) could result in significantly shorter travel times than the conventional intersection. The traffic operations of these four intersection designs were found to be similar to the two-phase designs and even better than the full MUT in scenarios with high turning traffic ratios. The other three intersection designs (seven-phase, redirect L&T, and MUT #2) also showed potential as possible substitutes for existing four-phase intersections under conditions with higher turning traffic demands.

  PublisherDOI

• Optimal Connected Automated Vehicle Control in Freeway Merge Segments through Distributed Coordination

  Transportation Research Record Journal of the Transportation Research Board · 2025-12-12

  articleSenior authorCorresponding

  Recent advancements in connected automated vehicle (CAV) technologies promise significant improvements in traffic management, particularly in complex roadways such as freeway merge segments. However, achieving these improvements requires the implementation of a systematic control framework to coordinate CAV operations effectively. This paper presents a distributed cooperative optimization algorithm specifically designed to refine the trajectory and lane-changing decisions of CAVs. A vehicle-level mixed-integer nonlinear program is introduced, optimizing discrete lane-changing decisions and continuous lateral and longitudinal acceleration of CAVs. The optimization approach uses a hybrid solution technique that combines linearization with a receding horizon framework. This reduces computational complexity while ensuring adaptability to the traffic system’s dynamics. The algorithm is evaluated using a case study, and it significantly improves traffic flow efficiency. The results showed reductions of up to 93.6% in average delay, 50.0% in speed variation, and 47.6% in fuel consumption. Sensitivity analysis revealed the algorithm’s robustness across varying speed limits, demand levels, and lane configurations. For instance, while higher demand rates severely degrade traffic performance in simulation runs, the optimization consistently maintains low delays and high speeds. This shows the algorithm’s ability to adapt to challenging traffic conditions. In addition, sensitivity tests indicate that design features, such as longer acceleration lanes, reduce speed variations and improve merging efficiency. These results highlight the algorithm’s capability to deliver reliable and efficient traffic management under diverse operational scenarios.

  PublisherDOI

• A closed-form avoidance control for safe maneuvering of multiple car-like vehicles

  Automatica · 2025-12-18

  article
  PublisherDOI

• Introducing Two New Versions of Continuous Flow and Median U-Turn Combination Intersection Designs

  Journal of Transportation Engineering Part A Systems · 2025-05-27 · 2 citations

  article

  In recent years, departments of transportation (DOTs) have shown an interest in implementing alternative intersections that combine features of two (or more) different designs. However, the current literature on the performance of these combination designs is limited. This paper reports on an assessment of the traffic operations and safety of two new combination intersection designs—continuous flow and median U-turn combination (CFI/MUT combo) and redirect two left-turn and one through (redirect 2L&T)—in comparison to four existing intersection designs: conventional, partial MUT, partial CFI, and reduced conflict intersection (RCI). Over 1,000 microsimulation runs were conducted in this study, considering different traffic demands, turning traffic ratios, and traffic demand distributions. For all simulation scenarios, traffic signals were optimized using Synchro, and the optimized signal data were imported into PTV VISSIM to obtain several performance measures such as vehicle travel time, queue length, and the number of stops for all designs considered. Safety analysis was also conducted using surrogate safety measures, including the US Federal Highway Administration’s Surrogate Safety Assessment Model (SSAM). Based on the results, both the CFI/MUT combo and redirect 2L&T showed potential in improving safety and operations at conventional intersections. The CFI/MUT combo exhibited statistically similar vehicle travel times to a partial CFI and outperformed all other designs. The redirect 2L&T demonstrated statistically similar travel times to the partial MUT but resulted in longer queue lengths. From a safety standpoint, the RCI is the safest intersection design among those considered.

  PublisherDOI

• Advancing the white phase mobile traffic control paradigm to consider pedestrians

  Computer-Aided Civil and Infrastructure Engineering · 2024-03-11 · 7 citations

  articleOpen accessSenior authorCorresponding

  Current literature on joint optimization of intersection signal timing and connected automated vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention to pedestrians. This paper presents a methodology to safely incorporate pedestrians into signalized intersections with CAVs and connected human-driven vehicles (CHVs). The movements of vehicles are controlled using both traffic lights and mobile CAV controllers during our newly introduced “white phase.” CAVs navigate platoons of CHVs through the intersection when the white phases are active. In addition to optimizing CAV trajectories, the model optimally selects the status of the traffic light signal among white and green indications for vehicular and walk and do-not-walk intervals for pedestrian movements. A receding horizon-based methodology is used to capture the stochastic nature of the problem and to reduce computational complexity. The case study results show the successful operation of fleets consisting of pedestrians, CAVs, and CHVs with various demand levels through isolated intersections. The results also show that increasing the CAV market penetration rate (MPR) can decrease average intersection delay by up to 27%. Moreover, the average pedestrian, CHV, and CAV delays decrease as the CAV MPR increases and reach their minimum values with a fully CAV fleet. In addition, the presence of the white phase can decrease the intersection average delay by up to 14.7%.

  PublisherOA PDFDOI

• Joint Signal Timing and Trajectory Control With Uncertainty in Connected Automated Vehicle Dynamics

  IEEE Transactions on Intelligent Transportation Systems · 2024-05-31 · 12 citations

  articleSenior author

  Optimizing the trajectory of connected automated vehicles (CAVs) through cooperation with signal controllers can smoothen the traffic flow and reduce energy consumption. However, most existing research efforts in this domain do not consider the effect of stochastic disturbances generated by exogenous systems. Ignoring these stochasticities may cause a mismatch between the estimated and real vehicle dynamics, which may result in a deviation among implemented and optimized trajectories, inefficient operational performance, and even collisions in the worst-case condition. This paper introduces a two-stage optimization model for CAVs trajectory and signal timing control that considers and responds to uncertainty in vehicle dynamics. The signal controller receives the speed, acceleration, and position of incoming CAVs within the communication range and identifies incoming platoons based on vehicle headways. At the upper stage, a mixed-integer linear program within the signal controller optimizes the trajectories of the platoon leaders and signal timing parameters. At the lower stage, platoon leaders optimize the trajectories of all other vehicles within the platoon based on a chance-constrained concept to consider uncertainties involved in implementing optimized trajectories. We utilize a sample-based approximation of the collision probabilities to formulate constraints to control vehicle trajectory. The resulting formulation ensures that the probability of satisfying inter-vehicle safety distance is above a certain threshold and reduces the probability of longitudinal crashes between vehicles. The proposed framework shows a 48%-67% reduction in travel delays in comparison with optimized fixed-time signal timing plans in a simulated signalized intersection under different levels of uncertainty in vehicle dynamics.

  PublisherDOI

Recent grants

• RAPID: Collection and Archiving of Vital Data on COVID-19 Vaccine Distribution

  NSF · $100k · 2021–2023

Frequent coauthors

• Rahim F. Benekohal

  University of Illinois Urbana-Champaign

  29 shared

• Leila Hajibabai

  North Carolina State University

  23 shared

• Mehrdad Tajalli

  North Carolina State University

  21 shared

• Rasool Mohebifard

  North Carolina State University

  18 shared

• Juan C. Medina

  University of Utah

  17 shared

• Nagui M. Rouphail

  17 shared

• Bastian J. Schroeder

  14 shared

• S M A Bin Al Islam

  Amazon (United States)

  11 shared

Education

• Ph.D., Civil Engineering

  University of California, Berkeley

  2003

• M.S., Civil Engineering

  University of California, Berkeley

  1999

• B.S., Civil Engineering

  University of Tehran

  1996

Awards & honors

• Secretary of the Work Zone Traffic Control standing committe…
• Chair of the Asset Management Subcommittee of the Traffic Si…