Larry Head
- Professor, Systems and Industrial Engineering
- Member of the Graduate Faculty
- Director, Craig M Berge Engineering Design Program
- (520) 621-2264
- Engineering, Rm. 251
- Tucson, AZ 85721
- klhead@arizona.edu
Biography
Larry Head is a Professor of Systems and Industrial Engineering at the University of Arizona. He has over 30 years of academic and industry experience related to systems engineering, engineering management, adaptive traffic signal control and signal priority, and connected and automated vehicle systems. He has served as Interim Dean of the College of Engineering, Interim Vice Provost for Online Learning, Director of the Transportation Research Institute, and Department Head of the Systems and Industrial Engineering Department at the University of Arizona. He currently serves on the Arizona Governor’s Task Force for Self -Driving Vehicles, is a member of the Transportation Research Board (TRB) Traffic Signal Systems Committee and the Intelligent Transportation Systems Committee, and a past member of the SAE DSRC Technical Committee. He is an Associate Editor of Transportation Research – Part C. He is a member of TRB, SAE, ASEE, INFORMS, IISE, and IEEE.
Degrees
- Ph.D. Systems and Industrial Engineering
- University of Arizona, Tucson, Arizona
- Modeling and Identification of Nonlinear Oscillations
- M.S. Systems Engineering
- University of Arizona, Tucson, Arizona
- Monitoring Patients in Anesthesia
- B.S. Systems Engineering
- University of Arizona, Tucson, Arizona
Work Experience
- College of Engineering (2018 - 2019)
- Systems and Industrial Engineering, University of Arizona (2015 - Ongoing)
- ATLAS Research Center, University of Arizona (2013 - 2018)
- Systems and Industrial Engineering, University of Arizona (2007 - 2015)
- Systems and Industrial Engineering, University of Arizona (2007 - 2014)
- Systems and Industrial Engineering, University of Arizona (2006 - 2007)
- Systems and Industrial Engineering, University of Arizona (2003 - 2006)
- Siemens Energy and Automation, Inc. (2000 - 2003)
- Gardner Transportation Systems, Inc. (1998 - 2000)
- Systems and Industrial Engineering, University of Arizona (1994 - 1997)
- Systems and Industrial Engineering, University of Arizona (1989 - 1993)
Awards
- Trevor O. Jones Outstanding Paper Award 2021
- Society of Automotive Engineers, Fall 2021
- Exceptional Paper Award, Committee on Traffic Signal Systems (AHB25) of the Transportation Research Board of the National Academies
- Transportation Research Board of the National Academies, Spring 2017
- 2016 Best ITS Implementation Project
- ITS Arizona, Fall 2016
- 2016 Member of the Year
- ITS Arizona, Fall 2016
- Best Dissertation Advisor Award
- Chinese Overseas Transportation Association (COTA), Spring 2016
- D. Grant Mickle Award for Outstanding Paper in the Field of Operation, Safety, and Maintenance of Transportation Facilities
- Transportation Research Board of the National Academies, Spring 2016
- da Vinci Fellow
- College of EngineeringUniversity of Arizona, Spring 2016
- COE Excellence at the Student Interface
- Spring 2014
Interests
Teaching
Systems Engineering, Engineering Management, Financial Modeling for Innovation, Object Oriented Modeling and Design, Simulation, Transportation Systems, Communications Theory
Research
Cyber-Physical Systems, Intelligent Systems, Connected and Autonomous Vehicles, Urban Traffic Operations, Transportation Modeling, Intelligent Transportation Systems
Courses
2024-25 Courses
-
Dissertation
SIE 920 (Spring 2025) -
Doctoral
SIE 695A (Spring 2025) -
Engineering Design Thinking
ENGR 195 (Spring 2025) -
Honors Thesis
HNRS 498H (Spring 2025) -
Honors Thesis
NROS 498H (Spring 2025) -
Interdisciplinary Capstone
ENGR 498A (Spring 2025) -
Interdisciplinary Capstone
ENGR 498B (Spring 2025) -
Master's Report
SIE 909 (Spring 2025) -
Topics in Engr Leadership
ENGR 495 (Spring 2025) -
DOD MISSIONS
DCTC 401 (Fall 2024) -
Dissertation
SIE 920 (Fall 2024) -
FUND OF CIVILIAN SERVICE
DCTC 301 (Fall 2024) -
Honors Thesis
HNRS 498H (Fall 2024) -
Honors Thesis
NROS 498H (Fall 2024) -
Interdisciplinary Capstone
ENGR 498A (Fall 2024) -
Interdisciplinary Capstone
ENGR 498B (Fall 2024) -
Master's Report
SIE 909 (Fall 2024) -
Research
SFWE 900 (Fall 2024) -
Research
SIE 900 (Fall 2024)
2023-24 Courses
-
Intro to Experiential Learning
ENGR 297 (Summer I 2024) -
Dissertation
SIE 920 (Spring 2024) -
Doctoral
SIE 695A (Spring 2024) -
Engineering Design Thinking
ENGR 195 (Spring 2024) -
Independent Study
SIE 499 (Spring 2024) -
Interdisciplinary Capstone
ENGR 498A (Spring 2024) -
Interdisciplinary Capstone
ENGR 498B (Spring 2024) -
Topics in Engr Leadership
ENGR 495 (Spring 2024) -
Dissertation
SIE 920 (Fall 2023) -
Independent Study
SIE 399 (Fall 2023) -
Interdisciplinary Capstone
ENGR 498A (Fall 2023) -
SIE Sophomore Colloq
SIE 295S (Fall 2023) -
Topics in Engr Leadership
ENGR 495 (Fall 2023)
2022-23 Courses
-
Dissertation
SIE 920 (Spring 2023) -
Doctoral
SIE 695A (Spring 2023) -
Engineering Design Thinking
ENGR 195 (Spring 2023) -
Interdisciplinary Capstone
ENGR 498B (Spring 2023) -
Dissertation
SIE 920 (Fall 2022) -
Financ Mdl For Inovation
SIE 567 (Fall 2022) -
Independent Study
SIE 599 (Fall 2022) -
Interdisciplinary Capstone
ENGR 498A (Fall 2022) -
SIE Sophomore Colloq
SIE 295S (Fall 2022)
2021-22 Courses
-
Dissertation
SIE 920 (Spring 2022) -
Doctoral
SIE 695A (Spring 2022) -
Engineering Design Thinking
ENGR 195 (Spring 2022) -
Financ Mdl For Inovation
SIE 567 (Spring 2022) -
Independent Study
SIE 599 (Spring 2022) -
Interdisciplinary Capstone
ENGR 498B (Spring 2022) -
Intro to Experiential Learning
ENGR 297 (Spring 2022) -
Dissertation
SIE 920 (Fall 2021) -
Interdisciplinary Capstone
ENGR 498A (Fall 2021) -
Research
SIE 900 (Fall 2021) -
SIE Sophomore Colloq
SIE 295S (Fall 2021)
2020-21 Courses
-
Dissertation
SIE 920 (Spring 2021) -
Doctoral
SIE 695A (Spring 2021) -
Financ Mdl For Inovation
SIE 567 (Spring 2021) -
Dissertation
SIE 920 (Fall 2020) -
Research
SIE 900 (Fall 2020) -
SIE Sophomore Colloq
SIE 295S (Fall 2020)
2019-20 Courses
-
Dissertation
SIE 920 (Spring 2020) -
Engineering Design Thinking
ENGR 195 (Spring 2020) -
Financ Mdl For Inovation
SIE 567 (Spring 2020) -
Independent Study
SIE 599 (Spring 2020) -
Research
SIE 900 (Spring 2020) -
Dissertation
SIE 920 (Fall 2019) -
Independent Study
SIE 599 (Fall 2019)
2018-19 Courses
-
Grand Challenges: Engineering
ENGR 196C (Spring 2019) -
Dissertation
SIE 920 (Fall 2018)
2017-18 Courses
-
Independent Study
SIE 499 (Summer I 2018) -
Dissertation
SIE 920 (Spring 2018) -
Doctoral
SIE 695A (Spring 2018) -
Internship
SIE 493 (Spring 2018) -
Master's Report
SIE 909 (Spring 2018) -
Research
SIE 900 (Spring 2018) -
SIE Sophomore Colloq
SIE 295S (Spring 2018) -
Dissertation
SIE 920 (Fall 2017) -
Doctoral
SIE 695A (Fall 2017) -
Financ Mdl For Inovation
SIE 567 (Fall 2017) -
Honors Independent Study
SIE 299H (Fall 2017) -
Internship
SIE 493 (Fall 2017) -
Intro:Systems & Indust. Engr
SIE 250 (Fall 2017) -
Master's Report
SIE 909 (Fall 2017) -
Research
SIE 900 (Fall 2017)
2016-17 Courses
-
Directed Research
ECE 492 (Summer I 2017) -
Internship
SIE 493 (Summer I 2017) -
Dissertation
SIE 920 (Spring 2017) -
Doctoral
SIE 695A (Spring 2017) -
Master's Report
SIE 909 (Spring 2017) -
Research
SIE 900 (Spring 2017) -
SIE Sophomore Colloq
SIE 295S (Spring 2017) -
Senior Dsgn Projects II
SIE 498B (Spring 2017) -
Dissertation
SIE 920 (Fall 2016) -
Doctoral
SIE 695A (Fall 2016) -
Financ Mdl For Inovation
SIE 567 (Fall 2016) -
Master's Report
SIE 909 (Fall 2016) -
Research
SIE 900 (Fall 2016) -
Senior Design Projects I
SIE 498A (Fall 2016)
2015-16 Courses
-
Independent Study
SIE 499-SA (Summer I 2016) -
Dissertation
SIE 920 (Spring 2016) -
Doctoral
SIE 695A (Spring 2016) -
SIE Sophomore Colloq
SIE 295S (Spring 2016)
Scholarly Contributions
Journals/Publications
- Head, K. L., Altekar, N. V., & Das, D. (2022). Priority-Based Traffic Signal Coordination System With Multi-Modal Priority and Vehicle Actuation in a Connected Vehicle Environment. Transportation Research Record: Journal of the Transportation Research Board, 036119812211346. doi:10.1177/03611981221134627
- Altekar, N., Como, S., Lu, D., Wishart, J., Bruyere, D. P., Saleem, F., & Head, K. L. (2021). Infrastructure-based Sensor Data Capture Systems for Measurement of Operational Safety Assessment (OSA) Metrics. SAE Technical Paper, 2021-01-0175, 1-12. doi:10.4271/2021-01-0175
- Head, K. L., Altekar, N. V., Das, D., & Saleem, F. (2021). Traffic Signal Priority Control Strategy for Connected Emergency Vehicles with Dilemma Zone Protection for Freight Vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2676(1), 499-517. doi:10.1177/03611981211039157
- Duncan, G., Head, K. L., & Puvvala, R. K. (2014). Multi-Modal Intelligent Traffic Signal System-Safer and More Efficient Intersections Through a Connected Vehicle Environment. IMSA Journal, 52(5).
- He, Q., Head, K. L., & Ding, J. (2014). Multi-modal traffic signal control with priority, signal actuation and coordination. Transportation Research Part C: Emerging Technologies, 46, 65--82.
- Beak, B., Zamanipour, M., Head, K. L., & Leonard, B. (2018). Peer-to-Peer Priority Signal Control Strategy in a Connected Vehicle Environment. Transportation Research Record, 0361198118773567.
- Head, K. L., Beak, B., & Khosravi, S. (2018). Quantitative Analysis of Smooth Progression in Traffic Signal Systems. Journal of Transportation Engineering, Part A: Systems, 144(3). doi:10.1061/jtepbs.0000123
- Khosravi, S., Beak, B., Head, K. L., & Saleem, F. (2018). Assistive System to Improve Pedestrians’ Safety and Mobility in a Connected Vehicle Technology Environment. Transportation Research Record, 0361198118783598.
- Miao, Z., Head, K. L., & Beak, B. (2018). Vehicle Reidentification in a Connected Vehicle Environment using Machine Learning Algorithms. Transportation Research Record, 0361198118774691.
- Zhao, J., Ma, W., Head, K. L., & Han, Y. (2018). Improving the operational performance of two-quadrant parclo interchanges with median U-turn concept. Transportmetrica B: transport dynamics, 6(3), 190--210.
- Beak, B., Head, K. L., & Feng, Y. (2017). Adaptive Coordination Based on Connected Vehicle Technology. Transportation Research Record: Journal of the Transportation Research Board, 1--12.
- Beak, B., Head, K. L., & Khosravi, S. (2017). Quantitative Analysis of Smooth Progression in Traffic Signal Systems. Journal of Transportation Engineering, Part A: Systems, 144(3), 04017082.
- Feng, Y., Zamanipour, M., Head, K. L., & Khoshmagham, S. (2016). Connected Vehicle--Based Adaptive Signal Control and Applications. Transportation Research Record: Journal of the Transportation Research Board, 11--19.
- Head, K. L., Zhao, J., Ma, W., & Han, Y. (2016). Improving the operational performance of two-quadrant parclo interchanges with median U-turn concept. Transportmetrica B: Transport Dynamics, 6(3), 190-210. doi:10.1080/21680566.2016.1249438
- Khoshmagham, S., Head, K. L., Feng, Y., & Zamanipour, M. (2016). Multimodal Data Analytics Comparative Visualization Tool: Case Study of Pedestrian Crossing Design. Transportation Research Record: Journal of the Transportation Research Board, 44--54.
- Zamanipour, M., Head, K. L., Feng, Y., & Khoshmagham, S. (2016). Efficient priority control model for multimodal traffic signals. Transportation Research Record: Journal of the Transportation Research Board, 86--99.
- Feng, Y., Head, K. L., Khoshmagham, S., & Zamanipour, M. (2015). A real-time adaptive signal control in a connected vehicle environment. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 55, 460-473.
- Zhao, J., Ma, W., Head, K. L., & Yang, X. (2015). Dynamic Turning Restriction Management for Signalized Road Network. TRANSPORTATION RESEARCH RECORD, 96-111.
- Zhao, J., Ma, W., Head, K. L., & Yang, X. (2015). Optimal operation of displaced left-turn intersections: A lane-based approach. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 61, 29-48.
- Head, K. L., Xie, X., Feng, Y., & Smith, S. F. (2014). Unified Route Choice Framework: Specification and Application to Urban Traffic Control. Transportation Research Record: Journal of the Transportation Research Board, 2466(1), 105-113. doi:10.3141/2466-12
- Wanjing, M. a., Head, K. L., & Feng, Y. (2014). Integrated optimization of transit priority operation at isolated intersections: A person-capacity-based approach. Transportation Research Part C: Emerging Technologies, 40, 49-62.More infoAbstract: In this paper, a person-capacity-based optimization method for the integrated design of lane markings, exclusive bus lanes, and passive bus priority signal settings for isolated intersections is developed. Two traffic modes, passenger cars and buses, have been considered in a unified framework. Person capacity maximization has been used as an objective for the integrated optimization method. This problem has been formulated as a Binary Mixed Integer Linear Program (BMILP) that can be solved by a standard branch-and-bound routine. Variables including, allocation of lanes for different passenger car movements (e.g., left turn lanes or right turn lanes), exclusive bus lanes, and passive bus priority signal timings can be optimized simultaneously by the proposed model. A set of constraints have been set up to ensure feasibility and safety of the resulting optimal lane markings and signal settings. Numerical examples and simulation results have been provided to demonstrate the effectiveness of the proposed person-capacity-based optimization method. The results of extensive sensitivity analyses of the bus ratio, bus occupancy, and maximum degree of saturation of exclusive bus lanes have been presented to show the performance and applicable domain of the proposed model under different composition of inputs. © 2014 Elsevier Ltd.
- Wanjing, M. a., Liu, Y., & Head, K. L. (2013). Optimization of pedestrian phase patterns at signalized intersections: A multi-objective approach. Journal of Advanced Transportation.More infoAbstract: SUMMARY: This paper presents a multi-objective optimization model and its solution algorithm for optimization of pedestrian phase patterns, including the exclusive pedestrian phase (EPP) and the conventional two-way crossing (TWC) at an intersection. The proposed model will determine the optimal pedestrian phase pattern and the corresponding signal timings at an intersection to best accommodate both vehicular traffic and pedestrian movements. The proposed model is unique with respect to the following three critical features: (1) proposing an unbiased performance index for comparison of EPP and TWC by explicitly modeling the pedestrian delay under the control of TWC and EPP; (2) developing a multi-objective model to maximize the utilization of the available green time by vehicular traffic and pedestrian under both EPP or TWC; and (3) designing a genetic algorithm based heuristic algorithm to solve the model. Case study and sensitivity analysis results have shown the promising property of the proposed model to assist traffic practitioners, researchers, and authorities in properly selecting pedestrian phase patterns at signalized intersections. © 2013 John Wiley & Sons, Ltd.
- Wanjing, M. a., Liu, Y., Head, L., & Yang, X. (2013). Integrated optimization of lane markings and timings for signalized roundabouts. Transportation Research Part C: Emerging Technologies, 36, 307-323.More infoAbstract: Installing signals has long been proved to be a cost-effective solution to increase capacity and treat unbalanced flows at modern roundabouts (Shawaly et al., 1991). However, signal optimization methods for conventional intersections do not directly apply to roundabouts due to the complexity of operating signals at circulatory lanes, designing special phase structure and lane marking settings, and treating left-turn movements, particularly when there are more than two lanes at approaches of a roundabout. This paper contributes to developing an integrated optimization model that is able to simultaneously determine lane markings and timings for a signalized roundabout. A precedence graph is uniquely designed to formulate a unified phase structure at both approaches and circulatory lanes. Left-turn movement queuing section at circulatory lanes is modeled as an intersection approach with short lanes and upstream signals, where queuing diagram is employed to model the capacity, queue length, and queue clearance for left turns at the second stop line. Capacity maximization, cycle length minimization, and delay minimization problems are formulated to optimize the operation of a roundabout. Real-world operational constraints are also taken into account in the optimization process to ensure feasibility and safety. Case study and sensitivity analyses results have demonstrated the effectiveness of the proposed model and provided guidelines for best application of the proposed control strategy. © 2013 Elsevier Ltd.
- Wanjing, M. a., Wei, N. i., Head, L., & Zhao, J. (2013). Effective coordinated optimization model for transit priority control under arterial progression. Transportation Research Record, 71-83.More infoAbstract: With the goal of providing effective priority control for transit while minimizing adverse impacts on general traffic movements along the arterial, this paper presents a coordinated transit priority control optimization model with the following features: (a) the control unit is defined as the coordinated intersection group between two successive bus stops; (b) buses are detected after leaving the upstream stop before their arrival at the first intersection of a control unit; (c) the dynamic interactions of priority strategies between adjacent intersections within a control unit are modeled by using a bus delay model and an ineffective priority time model; and (d) a linear program model is developed to generate the optimal priority strategies to reduce bus travel time when priority is necessary and to ensure that every priority treatment implemented at each intersection is effective. Extensive experimental analyses, including time-space diagram-based deterministic analysis and simulation-based analysis, were performed, and results were compared with conventional transit signal priority strategy and no-priority scenarios. The proposed model presents promising outcomes in the design of transit priority signal control in terms of decreasing bus delay, improving bus schedule adherence, and minimizing the negative impacts on general traffic under different traffic demand patterns.
- Wanjing, M. a., Xie, H., Liu, Y., Head, L., & Luo, Z. (2013). Coordinated optimization of signal timings for intersection approach with presignals. Transportation Research Record, 93-104.More infoAbstract: Many congested intersections have heavy traffic volume on movements for which there is insufficient capacity because of geometric limitations. Installing presignals at midblock locations and reorganizing traffic upstream of the approach of an intersection combine to be a promising and cost-effective method for addressing these capacity limitations. A coordinated optimization model was developed for an isolated intersection approach with presignals to increase the protected left-turn phase capacity. The presignal model was based on two principles: (a) explicitly capture the interaction between the presignal and the main signal by modeling the queuing process and capacity constraints of temporal and spatial limitations of the intersection and (b) optimize the signal timings of both the presignal and the main signal as well as the offset between them to produce the best operational strategy for the approach. The minimum green time required and the delay-minimization problems are considered. Extensive experimental analysis has shown that the presignal model out-performs the conventional control method (without presignal). Sensitivity analysis of the signal timing method that will assist traffic engineers with selecting the appropriate length of the sorting area, phase sequence, and early starting time of presignals was conducted. The results from the study offer a basis for traffic practitioners, researchers, and authorities on which to design and utilize presignals in locations where there is a need to increase intersection capacity for congested movements.
- Qing, H. e., Head, K. L., & Ding, J. (2012). PAMSCOD: Platoon-based arterial multi-modal signal control with online data. Transportation Research Part C: Emerging Technologies, 20(1), 164-184.More infoAbstract: A unified platoon-based mathematical formulation called PAMSCOD is presented to perform arterial (network) traffic signal control while considering multiple travel modes in a vehicle-to-infrastructure communications environment. First, a headway-based platoon recognition algorithm is developed to identify pseudo-platoons given probe vehicles' online information. It is assumed that passenger vehicles constitute a significant majority of the vehicles in the network. This algorithm identifies existing queues and significant platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine future optimal signal plans based on the current traffic controller status, online platoon data and priority requests from special vehicles, such as transit buses. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the probe information. Microscopic simulation using VISSIM shows that PAMSCOD can easily handle two common traffic modes, transit buses and automobiles, and significantly reduce delays for both modes under both non-saturated and oversaturated traffic conditions as compared to traditional state-of-practice coordinated-actuated signal control with timings optimized by SYNCHRO. © 2011 Elsevier Ltd.
- Ruiz, E. E., & Head, K. L. (2012). Use of an automatic under-vehicle inspection system as a tool to streamline vehicle screening at ports of entry and security checkpoints. Proceedings - 2012 European Intelligence and Security Informatics Conference, EISIC 2012, 329-333.More infoAbstract: Vehicle inspection at ports of entry is a critical component of border security. One part of the vehicle screening process involves customs and border protection (CBP) personnel performing a preliminary inspection of the underside of random vehicles by looking under the vehicle through a mirror mounted on a stick, searching for anomalies or foreign objects present on the undercarriage structure and components of a vehicle. If any deviances are detected, the vehicle is directed to a secondary and more thorough inspection. This paper presents a project that aims at automating this preliminary undercarriage inspection by using an automatic under-vehicle inspection system (AUVIS) and image processing algorithms to assist personnel in identifying vehicles for secondary inspection. The inspection system will image the undercarriage of every car in a lane as they approach the CBP agent and use a novel change detection algorithm to compare the captured image to a corresponding reference image of the vehicle's make and model. The software will detect and highlight any differences between the two images to provide a rapid and objective recommendation for secondary inspection. © 2012 IEEE.
- Qing, H. e., Head, K. L., & Ding, J. (2011). Heuristic algorithm for priority traffic signal control. Transportation Research Record, 1-7.More infoAbstract: A heuristic algorithm is presented for traffic signal control with simultaneous multiple priority requests at isolated intersections in the context of vehicle-to-infrastructure communications being available on priority vehicles, such as emergency vehicles and transit buses. This heuristic algorithm can achieve near-optimal signal timing when all simultaneous requests are considered and can be visualized in a phase-time diagram. First, the problem with the control of multiple priority traffic signals is transformed into a network cut problem that is polynomial solvable under some reasonable assumptions. Second, a phase-time diagram is presented to visualize and evaluate priority delay given a signal plan and a collection of priority request arrival times. Microscopic traffic simulation is used to compare the heuristic with the state-of-the-practice algorithms for transit signal priority. The proposed heuristic algorithm could reduce average bus delay in congested conditions by about 50%, especially with a high frequency of conflicting priority requests.
- Qing, H. e., Head, K. L., & Ding, J. (2011). PAMSCOD: Platoon-based arterial multi-modal signal control with online data. Procedia - Social and Behavioral Sciences, 17, 462-489.More infoAbstract: A unified platoon-based mathematical formulation called PAMSCOD is presented to perform arterial (network) traffic signal control while considering multiple travel modes in a vehicle-to-infrastructure communications environment. First, a headwaybased platoon recognition algorithm is developed to identify pseudo-platoons given probe vehicles' online information. It is assumed that passenger vehicles constitute a significant majority of the vehicles in the network. This algorithm identifies existing queues and significant platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine future optimal signal plans based on the current traffic controller status, online platoon data and priority requests from special vehicles, such as transit buses. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the probe information. Microscopic simulation using VISSIM shows that PAMSCOD can easily handle two common traffic modes, transit buses and automobiles, and significantly reduce delays for both modes under both non-saturated and oversaturated traffic conditions as compared to traditional state-of-practice coordinated-actuated signal control with timings optimized by SYNCHRO. © 2010 Published by Elsevier Ltd.
- Pengfei, L. i., Abbas, M. M., Pasupathy, R., & Head, L. (2010). Simulation-based optimization of maximum green setting under retrospective approximation framework. Transportation Research Record, 1-10.More infoAbstract: Most traffic signal systems work under highly dynamic traffic conditions, and they can be studied adequately only through simulation. As a result, how to optimize traffic signal system parameters in a stochastic framework has become increasingly important. Retrospective approximation (RA) represents the latest theoretical development in stochastic simulation. Under the RA framework, the solution to a simulation-based optimization problem can be approached with a sequence of approximate optimization problems. Each of these problems has a specific sample size and is solved to a specific error tolerance. This research applied the RA concept to the optimal design of the maximum green setting of the multidetector green extension system. It also designed a variant of the Markov monotonic search algorithm that can accommodate the requirements of the RA framework, namely, the inheritable Markov monotonic search algorithm, and implemented the RA-based optimization engine within VISSIM. The results show that the optimized maximum green can considerably increase composite performance (reducing delay and increasing safety) compared with traditional designs. The optimization methodology presented in this paper can easily be expanded to other signal parameters.
- Denney Jr., R. W., Curtis, E., & Head, L. (2009). Long green times and cycles at congested traffic signals. Transportation Research Record, 1-10.More infoAbstract: Field data were collected and simulation experiments based on traffic at an intersection in Virginia were conducted to test the hypothesis that headways increase with long green times and to test the common assumption that throughput increases with longer cycles. The results showed that headways increased with long green times as a result of departing turning vehicles and that this effect could cause a significant increase in overall average approach headways. The results also showed that maximum throughput, defined as the point where additional offered load could not be served, did not increase with longer cycles. With values derived from the field data, increasing the cycle did not increase throughput. In simulation, increasing the cycle caused a reduction in throughput as a result of increasing the effect of departing turning traffic on the average headway.
- Cohen, D., Head, L., & Shelby, S. G. (2007). Performance analysis of coordinated traffic signals during transition. Transportation Research Record, 19-31.More infoAbstract: Coordinated traffic signals can improve progression and delay times by switching timing plans as traffic conditions change. As cycle and split changes shift capacity where needed, signals shift offsets to maintain or to reestablish progressive flow. Signal offsets dictate, for each main-street green phase, where that green starts in each cycle with the intention of promoting nonstop green waves. To start it earlier or later at a given signal, the options are to shorten one or more intermediate phases or to lengthen one or more intermediate phases (or the main-street phase itself or both phases). Such phase time changes may create a temporary lack of capacity or impose extra delay time. Controllers from all vendors offer transition options to choose from that are differentiated by the amount of offset correction possible per cycle, whether they use a short or a long cycle, and by the distribution of time added to or subtracted from the set of phases. Common transition methods include dwell, maximum dwell, add, subtract, and shortway - all of which were recently incorporated into the CorSim actuated-controller logic. A transient profile analysis method is introduced and demonstrated with a model of a major arterial in Tucson, Arizona, and an additional hypothetical network model. The resulting transient profiles highlight the performance transition behavior that occurs during traffic signal plan transition and that contrasts with assertions previously reported in the literature.
- Gettman, D., Shelby, S. G., Head, L., Bullock, D. M., & Soyke, N. (2007). Data-driven algorithms for real-time adaptive tuning of offsets in coordinated traffic signal systems. Transportation Research Record, 1-9.More infoAbstract: A real-time adaptive control algorithm for tuning traffic signal offsets in a coordinated traffic signal system is presented. The algorithm described here is used in the Adaptive Control Software-Lite (ACS-Lite) adaptive control system. The algorithm uses a statistical average flow profile of traffic on the coordinated approaches to an intersection to assess when vehicles are arriving during the signal cycle. Alternative offset adjustments are evaluated by calculating how much of this flow profile is being captured by the green phase serving each coordinated approach. The algorithm considers the impact of the offset adjustment on traffic at the local intersection as well as on traffic at adjacent intersections that are also under ACS-Lite control. Simulation tests have quantitatively shown that this tuning approach can improve arterial progression performance relative to the quality of the initial baseline fixed offsets used in a traffic pattern. Several issues and areas for improvement of the algorithm are also identified and discussed.
- Head, L., Gettman, D., Bullock, D. M., & II, T. U. (2007). Modeling traffic signal operations with precedence graphs. Transportation Research Record, 10-18.More infoAbstract: A series of examples of traffic signal operations with the precedence graph model is presented to illustrate the interactions among phases, intervals, and overlaps. The examples are built up from the simple operation of a T-intersection by adding more complex behaviors, including advance "Walk," delayed overlap termination indications, and advance flashing warning signals. In each of these extensions the required signal timing behavior is illustrated through the appropriate precedence graph model. The precedence graph approach provides a structured conceptual representation to support the analysis of operational behaviors of controller timing features such as added lost time and required fixed timing intervals that are induced when certain overlap features are enabled. It is believed that the precedence graph modeling approach may provide a mechanism to formalize the often ad hoc interaction between traffic signal controller software development, logic design, and field operations. This improved understanding may ultimately result in a better understood and more robust deployment of innovative signal control logic by utilizing a structure-modeling approach similar to that found in project management techniques such as the critical path method and the program evaluation and review technique.
- Head, L., Gettman, D., & Zhiping, W. (2006). Decision model for priority control of traffic signals. Transportation Research Record, 169-177.More infoAbstract: This paper presents a model of the core logic of a traffic signal controller. The model is formulated on the basis of the traditional North American ring, phase, and barrier construct and includes phase intervals such as minimum and maximum times, pedestrian service, alternative minimum times, and a priority service extension. The mathematical model is based on precedence graphs that are familiar to engineers involved with project management techniques such as Gantt charts, the critical path method, and the program evaluation and review technique. The model presents an analytical framework for the analysis of complex controller behaviors and is demonstrated for the case of multiple priority requests. An example shows that a first-come, first-served policy for serving priority requests can result in more delay than will a multiple-priority-request policy generated by the model developed in this paper. Additional controller behaviors, such as preemption, coordination, and offset transition, can be analyzed with this model.
- Gettman, D., & Head, L. (2003). Surrogate Safety Measures from Traffic Simulation Models. Transportation Research Record, 104-115.More infoAbstract: Safety is emerging as an area of increased attention and awareness within transportation engineering. Historically, the safety of new and innovative traffic treatments has been difficult to assess, primarily because of a lack of good predictive models of crash potential and a lack of consensus on what constitutes a safe or unsafe facility. An FHWA-sponsored research project investigated the potential to derive surrogate measures of safety from existing traffic simulation models. These surrogate measures could then be used to support evaluations of various traffic engineering alternatives, including facilities that have not yet been built and strategies that have not yet been used. Each surrogate measure is collected on the basis of the occurrence of a conflict event, which is an interaction between two vehicles in which one vehicle must take evasive action to avoid a collision. The surrogate measures that are proposed as the best are time to collision, postencroachment time, deceleration rate, maximum speed, and speed differential. Time to collision, postencroachment time, and deceleration rate can be used to measure the severity of the conflict. Maximum speed and the speed differential can be used to measure the severity of the potential collision (by use of additional information about the mass of the vehicles involved to assess momentum). After the simulation model is executed for a number of iterations, a postprocessing tool would be used to compute the statistics for the various measures and perform comparisons between design alternatives.
- Luyanda, F., Gettman, D., Head, L., Shelby, S., Bullock, D., & Mirchandani, P. (2003). ACS-Lite Algorithmic Architecture: Applying Adaptive Control System Technology to Closed-Loop Traffic Signal Control Systems. Transportation Research Record, 175-184.More infoAbstract: ACS-Lite is being developed by FHWA to be a cost-effective solution for applying adaptive control system (ACS) technology to current, state-of-the-practice closed-loop traffic signal control systems. This effort is intended to make ACS technology accessible to many jurisdictions without the upgrade and maintenance costs required to implement ACS systems that provide optimized signal timings on a second-by-second basis. The ACS-Lite system includes three major algorithmic components: a time-of-day (TOD) tuner, a run-time refiner, and a transition manager. The TOD tuner maintains plan parameters (cycle, splits, and offsets) as the long-term traffic conditions change. The run-time refiner modifies the cycle, splits, and offsets of the plan that is currently running based on observation of traffic conditions that are outside the normal bounds of conditions this plan is designed to handle. The run-time refiner also determines the best time to transition from the current plan to the next plan in the schedule, or, like a traffic-responsive system, it might transition to a plan that is not scheduled next in the sequence. The transition manager selects from the transition methods built in to the local controllers to balance the time spent out of coordination with the delay and congestion that is potentially caused by getting back into step as quickly as possible. These components of the ACS-Lite algorithm architecture are described and the similarities and differences of ACS-Lite with state-of-the-art and state-of-the-practice adaptive control algorithms are discussed. Closed-loop control system characteristics are summarized to give the context in which ACS-Lite is intended to operate.
- Ghaman, R., Gettman, D., Head, L., & Mirchandani, P. B. (2002). Adaptive control software for distributed systems. IECON Proceedings (Industrial Electronics Conference), 4, 3103-3106.More infoAbstract: Traffic control systems in United States evolved from electro-mechanical time-clock based to computer-based in late 1970's. The research and development sponsored by the Federal Highway Administration resulted in mainframe computer based centralized systems called Urban Traffic Control Software (UTCS). The key aspects of these systems were second by second command and control by the central computer of electro-mechanical controllers at each intersection. The communication technologies at the time were twisted pair time division multiplexing with a maximum of 12 intersections per pair of communication cable. A majority of the urbanized cities in the U.S. implemented such systems. In the 1990's, the Federal Highway Administration (FHWA) started research called Adaptive Control Software (ACS). This research generated four adaptive traffic control software prototypes called RHODES, OPAC, RTACL and ATCS. The key aspect of the RHODES, OPAC, and RTACL is that the control software is decentralized with link by link short time prediction of traffic demand. ATCS extended the UTCS approach to include adaptive capabilities. This research constitutes a major advancement in traffic signal control since the deployment of UTCS.
- Abbas, M., Bullock, D., & Head, L. (2001). Real-time offset transitioning algorithm for coordinating traffic signals. Transportation Research Record, 26-39.More infoAbstract: A traffic signal offset transitioning algorithm is introduced that can be viewed as an integrated optimization approach designed to work with traditional coordinated-actuated systems. The proposed approach assumes a fixed cycle length (selected by either time of day or some traffic-responsive technique). The splits are determined by each local controller subject to maximum and minimum constants traditionally imposed by coordinated-actuated signal systems. End-of-green offsets at each intersection are continually adjusted by the proposed algorithm with the objective of providing smooth progression of a platoon through an intersection using the volume and occupancy profile of advance detectors. The algorithm was implemented in a hardware-in-the-loop simulation and evaluated with a set of National Transportation Communications for Intelligent Transportation Systems Protocol (NTCIP) National Electrical Manufacturers Association controllers. The offsets were manipulated with NTCIP messages. The unique aspect of this algorithm is the cycle-based procedure used to tabulate volume and occupancy profiles, which can then be used to adjust the offsets in a traditional coordinated-actuated signal system. This automatic tuning process is analogous to an engineer or technician standing beside the cabinet and tuning the offset so that the coordinated phase turns green at the appropriate time to facilitate smooth progression of the upstream platoon. Because only the offsets are tuned, it is unlikely that this algorithm will be able to achieve the global optimum parameters or rapid adaptation possible with model-based approaches; nevertheless, this algorithm has the advantage of working within the framework of traditional coordinated-actuated signal systems that are familiar to system operators.
- Mirchandani, P., & Head, L. (2001). A real-time traffic signal control system: Architecture, algorithms, and analysis. Transportation Research Part C: Emerging Technologies, 9(6), 415-432.More infoAbstract: The paper discusses a real-time traffic-adaptive signal control system referred to as RHODES. The system takes as input detector data for real-time measurement of traffic flow, and "optimally" controls the flow through the network. The system utilizes a control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in an hierarchical fashion, (2) predicts traffic flows at appropriate resolution levels (individual vehicles and platoons) to enable pro-active control, (3) allows various optimization modules for solving the hierarchical subproblems, and (4) utilizes a data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be downloaded in the field appropriately within the given rolling time horizon of the corresponding subproblem. The RHODES architecture, algorithms, and its analysis are presented. Laboratory test results, based on implementation of RHODES on simulation models of actual scenarios, illustrate the effectiveness of the system. © 2001 Elsevier Science Ltd. All rights reserved.
- Lucas, D. E., Mirchandani, P. B., & Head, K. L. (2000). Remote simulation to evaluate real-time traffic control strategies. Transportation Research Record, 95-100.More infoAbstract: Simulation is a valuable tool for evaluating the effects of various changes in a transportation system. This is especially true in the case of real-time traffic-adaptive control systems, which must undergo extensive testing in a laboratory setting before being implemented in a field environment. Various types of simulation environments are available, from software-only to hardware-in-the-loop simulations, each of which has a role to play in the implementation of a traffic control system. The RHODES (real-time hierarchical optimized distributed effective system) real-time traffic-adaptive control system was followed as it progressed from a laboratory project toward actual field implementation. The traditional software-only simulation environment and extensions to a hardware-in-the-loop simulation are presented in describing the migration of RHODES onto the traffic controller hardware itself. In addition, a new enhancement to the standard software-only simulation that allows remote access is described. The enhancement removes the requirement that both the simulation and the traffic control scheme reside locally. This architecture is capable of supporting any traffic simulation package that satisfies specific input-output data requirements. This remote simulation environment was tested with several different types of networks and was found to perform in the same manner as its local counterpart. Remote simulation has all of the advantages of its local counterpart, such as control and flexibility, with the added benefit of distribution. This remote environment could be used in many different ways and by different groups or individuals, including state or local transportation agencies interested in performing their own evaluations of alternative traffic control systems.
- Mirchandani, P. B., Head, K. L., & Boyce, D. (2000). Model-based transportation policy analysis. International Journal of Technology Management, 19(3), 507-531.More infoAbstract: The role of 'models' has been well accepted in the analyses of problems dealing with transportation 'operations' and 'planning' decisions. The paper argues that even policy issues could use a model-based focused thinking in their analyses, even though in policy issues (1) more entities are affected and have to be considered, (2) decision variables and constraints are not clearly defined, and (3) multiple objectives need to be satisfied. The paper introduces a recursive systems engineering process for policy analyses, with a significant role for models. Two case studies on policies to reduce traffic congestion are discussed. The first study relates to preferential treatment for high-occupancy vehicles for using the transportation facilities. The second study relates to altering travel demand by congestion pricing policies. Several types of models are utilized in these studies. The models provide insights, which otherwise might be difficult, on issues and sensitivities of potential decisions and assumed parameters.
- Sen, S., & Head, K. L. (1997). Controlled optimization of phases at an intersection. Transportation Science, 31(1), 5-17.More infoAbstract: This paper presents a general purpose algorithm for real-time traffic control at an intersection. Our methodology, based on dynamic programming, allows optimization of a variety of perfor-mance indices such as delay, stops and queue lengths. Furthermore, optimal phase sequencing is a direct by-product of this new approach. These features make the new methodology a powerful tool for intersection control. We demonstrate the usefulness of the approach by a simulation experiment in which our intersection control algorithm is interfaced with a well established simulation package called TRAF-NETSIM. Our study compares the controlled optimization of phases methodology with fully-actuated as well as semi-actuated control. We show that consistent reductions in delay may be possible by adopting the new algorithm.
- Sen, S., Higle, J., Ferrell, R., Head, L., & Goldberg, J. (1997). ELITE - Engineering with Liberal and Technical Education project status report - evaluation, seminars, and advising. Proceedings - Frontiers in Education Conference, 2, 807-.More infoAbstract: Through the ELITE (Engineering with Liberal and Technical Education) program, the University of Arizona aims to help its students, through evaluations, seminars and advising, plan a course of study that reflects their interests in the arts, humanities, business or social sciences, and applications of engineering methods to these disciplines. The program provides a well rounded education that combines the quantitative analytical approach of engineering with the societal and cultural dimensions of the liberal arts. The project has been ongoing for approximately 15 months and the degree program approval process has been completed. A status report for this project is presented.
- Sheppard, D. E., Head, K. L., Joshua, S., & Mirchandani, P. B. (1997). Simulation-based methodology for evaluation of high-occupancy-vehicle facilities. Transportation Research Record, 90-98.More infoAbstract: There has been an increasing interest in improving the use of transportation facilities as environmental and social concerns have grown and as financial resources for infrastructure expansion have become increasingly scarce. Numerous programs for increasing carpooling, vanpooling, and transit usage have been undertaken to decrease reliance on single-occupant vehicles and increase the use of multioccupant vehicles. One program has been to develop facilities that give preferential treatment to high-occupancy vehicles (HOVs). Although HOV facilities have been implemented, they often have been found to be unsuccessful in attaining their stated or implied goals. Because interest in the use of HOV facilities is growing, there is a need to improve the ability to evaluate and compare design alternatives in the context of realistic (stochastic) environments. Simulation modeling has long been recognized as a powerful tool for such purposes. A structured simulation-based methodology for the evaluation of HOV design alternatives is presented. An example case study for a corridor in the Phoenix, Arizona, metropolitan area is used to demonstrate the methodology.
- Head, K. L., Sheppard, D. E., Joshua, S., & Mirchandani, P. B. (1996). Simulation-Based Methodology for Evaluation of High-Occupancy-Vehicle Facilities. Transportation Research Record: Journal of the Transportation Research Board, 1554(1), 90-98. doi:10.1177/0361198196155400112
- Sheppard, D. E., Head, K., Joshua, S., & Mirchandani, P. B. (1996). Simulation-based methodology for evaluation of high-occupancy-vehicle facilities. Transportation Research Record, 90-98.More infoAbstract: There has been an increasing interest in improving the use of transportation facilities as environmental and social concerns have grown and as financial resources for infrastructure expansion have become increasingly scarce. Numerous programs for increasing carpooling, vanpooling, and transit usage have been undertaken to decrease reliance on single-occupant vehicles and increase the use of multioccupant vehicles. One program has been to develop facilities that give preferential treatment to high-occupancy vehicles (HOVs). Although HOV facilities have been implemented, they often have been found to be unsuccessful in attaining their stated or implied goals. Because interest in the use of HOV facilities is growing, there is a need to improve the ability to evaluate and compare design alternatives in the context of realistic (stochastic) environments. Simulation modeling has long been recognized as a powerful tool for such purposes. A structured simulation-based methodology for the evaluation of HOV design alternatives is presented. An example case study for a corridor in the Phoenix, Arizona, metropolitan area is used to demonstrate the methodology.
- Head, K. (1995). Event-based short-term traffic flow prediction model. Transportation Research Record, 45-52.More infoAbstract: The problem of predicting traffic flow for the purpose of real-time traffic-adaptive signal control in an urban street network is explored. A prediction model is described that combines data from traditional vehicle loop detectors and known relationships from traffic flow theory. The model is demonstrated using a microscopic traffic simulation model. Results of the simulation demonstrate that the model can provide the information required to develop truly proactive real-time traffic-adaptive signal control.