Dr. Jorge A. Laval is a Professor at Georgia Tech in the School of Civil and Environmental Engineering. He obtained his PhD in Civil Engineering from the University of California, Berkeley under the supervision of Carlos Daganzo. Dr. Laval's work focuses on understanding urban traffic congestion by merging traffic flow theory, complex systems theory, and machine learning. He has made significant contributions to identifying the limitations of machine learning in urban network control and has developed autonomous vehicle control models that enhance traffic stability.
Dr. Laval’s research primarily involves understanding urban traffic congestion to develop superior control methods. His work integrates traffic flow theory, complex systems theory, and machine learning to address challenges in urban network control and autonomous vehicle stability. He also specializes in estimating macroscopic fundamental diagrams for urban networks and creating stochastic car-following models for statistical parameter inference.
| Ph.D., Civil Engineering | University of California at Berkeley | 2004 |
| MS, Transportation Engineering | University of California at Berkeley | 2001 |
| Ingeniero Civil Industrial, Mención Transporte | Universidad Católica de Chile | 1995 |
Dr. Laval focuses on integrating the latest advances in traffic flow and simulation into the curriculum. He has redefined courses such as Traffic Flow Theory and Simulation in Transportation and developed new offerings like Queuing Theory and Quantitative Methods in Transportation. His recent course, Complex Systems and AI Control, teaches students to use AI and machine learning tools to optimize large-scale engineering systems that exhibit unpredictable behavior.
- “Thank a Teacher” certificate from Fall 25’ students in CEE3770 Statistics and Applications class.
- Excellent Paper Award from the Korean Transportation Association in America (KOTAA).
- Preprints.org 2023 Most Popular Preprints Award Finalist.
- 2022 Best Paper Award: Gartner Prize awarded by the Traffic Flow Theory and Characteristics Committee of the Transportation Research Board.
- 2022 Best Paper Award: Greenshields Prize awarded by the Traffic Flow Theory and Characteristics Committee of the Transportation Research Board.
- 2019 Best Paper Award, awarded by the Traffic Flow Theory and Characteristics Committee of the Transportation Research Board.
- Faculty Early Career Development (CAREER) program award, 2011.
- Aryaman Jha, Kurt Wiesenfeld, Garyoung Lee, and Jorge Laval. Evidence of non-equilibrium critical phenomena in a simple model of traffic. Accepted in Physical Review E, 2025.
- He Z, Laval J, Han Y, Hegyi A, Nishi R, Wu C. A Review of Stop-and-Go Traffic Wave Suppression Strategies: Variable Speed Limit vs. Jam-Absorption Driving. Accepted in IEEE Transactions on Intelligent Transportation Systems, 2025.
- Zhou, Anye; Peeta, Srinivas; Zhou, Hao; Laval, Jorge. String instability mitigation of adaptive cruise control without modifying control laws: trajectory shaper and parameter estimation. Transportmetrica B: Transport Dynamics 13 (1), 2473885, 2025.
- Michail A. Makridis, M; El-Baklish, S; Kouvelas, A; Laval, J. The Fundamental Diagram of Autonomous Vehicles: Traffic State Estimation and Evidence from Vehicle Trajectories. Accepted in Communications in Transportation Research, 2025.
- Maiti, Nandan; Laval, Jorge; Chilukuri, Bhargava Rama; Universality of Area Occupancy-Based Fundamental Diagrams in Mixed Traffic. Physica A: Statistical Mechanics and its Applications 640, 2024.
- Zhou, Anye; Peeta, Srinivas; Zhou, Hao; Laval, Jorge; Wang, Zejiang; Cook, Adian; Implications of stop-and-go traffic on training learning-based car-following control. Transportation Research Part C: Emerging Technologies, 104578, 2024.
- Laval, Jorge. "Traffic Flow as a Simple Fluid: Towards a Scaling Theory of Urban Congestion." Transportation Research Record 2678 3, 376-386, 2024.
- Lee, Garyoung; Ding, Zijian; Laval, Jorge; Effects of loop detector position on the macroscopic fundamental diagram. Transportation Research Part C: Emerging Technologies 154, 104239, 2023.
- Laval, Jorge. Self-organized criticality of traffic flow: Implications for congestion management technologies. Transportation Research Part C: Emerging Technologies, Volume 149, pp 1040-56, 2023.
- Laval, Jorge. "Effect of the Trip-Length Distribution on Network-Level Traffic Dynamics: Exact and Statistical Results." Transportation Research Part C: Emerging Technologies, volume 148, pages 104036, 2023.
