@article{mohebifard_hajbabaie_2021, title={Connected automated vehicle control in single lane roundabouts}, volume={131}, ISSN={0968-090X}, url={http://dx.doi.org/10.1016/j.trc.2021.103308}, DOI={10.1016/j.trc.2021.103308}, abstractNote={This paper introduces a methodology to optimize the trajectory of connected automated vehicles (CAVs) in roundabouts using a two-dimensional point-mass model. We formulate an optimization problem that includes vehicle dynamics and collision-avoidance constraints with explicit representation of vehicle paths. The objective function of the problem minimizes the distance of CAVs to their destinations and their acceleration magnitudes. The methodology also involves a customized solution technique that convexifies the collision-avoidance constraints and employs the alternating direction method of multipliers to decompose the convexified problem into two sub-problems. The first sub-problem only includes vehicle dynamics constraints while the second sub-problem projects the solutions of the first sub-problem onto a collision-free region. The first sub-problem is then transformed into a quadratic problem by redefining its decision variables along vehicle paths. The transformation allows solving this sub-problem with several vehicle-level problems in a distributed architecture. Moreover, we show that iterating between the two sub-problems leads to convergence to the optimal solutions of the convexified problem. The methodology is applied to a case study roundabout with different demand levels. The results show that the trajectory optimization reduced the total travel times and average delays respectively by 9.1% to 36.8% and 95.8% to 98.5% compared to a scenario with human-driven vehicles.}, journal={Transportation Research Part C: Emerging Technologies}, publisher={Elsevier BV}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2021}, month={Oct}, pages={103308} }
 @article{islam_tajalli_mohebifard_hajbabaie_2021, title={Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System}, volume={2675}, ISSN={0361-1981 2169-4052}, url={http://dx.doi.org/10.1177/03611981211013036}, DOI={10.1177/03611981211013036}, abstractNote={The effectiveness of adaptive signal control strategies depends on the level of traffic observability, which is defined as the ability of a signal controller to estimate traffic state from connected vehicle (CV), loop detector data, or both. This paper aims to quantify the effects of traffic observability on network-level performance, traffic progression, and travel time reliability, and to quantify those effects for vehicle classes and major and minor directions in an arterial corridor. Specifically, we incorporated loop detector and CV data into an adaptive signal controller and measured several mobility- and event-based performance metrics under different degrees of traffic observability (i.e., detector-only, CV-only, and CV and loop detector data) with various CV market penetration rates. A real-world arterial street of 10 intersections in Seattle, Washington was simulated in Vissim under peak hour traffic demand level with transit vehicles. The results showed that a 40% CV market share was required for the adaptive signal controller using only CV data to outperform signal control with only loop detector data. At the same market penetration rate, signal control with CV-only data resulted in the same traffic performance, progression quality, and travel time reliability as the signal control with CV and loop detector data. Therefore, the inclusion of loop detector data did not further improve traffic operations when the CV market share reached 40%. Integrating 10% of CV data with loop detector data in the adaptive signal control improved traffic performance and travel time reliability.}, number={10}, journal={Transportation Research Record: Journal of the Transportation Research Board}, publisher={SAGE Publications}, author={Islam, S M A Bin Al and Tajalli, Mehrdad and Mohebifard, Rasool and Hajbabaie, Ali}, year={2021}, month={May}, pages={800–814} }
 @article{mohebifard_hajbabaie_2021, title={Trajectory control in roundabouts with a mixed fleet of automated and human‐driven vehicles}, volume={37}, ISSN={1093-9687 1467-8667}, url={http://dx.doi.org/10.1111/mice.12711}, DOI={10.1111/mice.12711}, abstractNote={This paper presents a methodology to control the trajectory of cooperative connected automated vehicles (CAVs) at roundabouts with a mixed fleet of CAVs and human‐driven vehicles (HVs). We formulate an optimization program in a two‐dimensional space for this purpose. A model predictive control‐based solution technique is developed to optimize the trajectories of CAVs at discretized time steps based on the estimated driving behavior of HVs, while the actual behavior of HVs is controlled by a microscopic traffic simulator. At each time step, the location and speed of vehicles are collected, and a decomposition‐based methodology optimizes CAV trajectories for a few time steps ahead of the system time. The optimization methodology has convexification, alternating direction method of multipliers, and cutting plane decomposition components to tackle the complexities of the problem. We tested the solution technique in a case study roundabout with different traffic demand flow rates and CAV market penetration rates. The results showed that increasing the CAV market penetration rate from 20% to 100% reduced total travel times by 2.8% to 35.8%. The analyses indicate that the presence of cooperative CAVs in roundabouts can lead to considerable improvements.}, number={15}, journal={Computer-Aided Civil and Infrastructure Engineering}, publisher={Wiley}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2021}, month={Jun}, pages={1959–1977} }
 @article{mirheli_tajalli_mohebifard_hajibabai_hajbabaie_2020, title={Utilization Management of Highway Operations Equipment}, volume={2674}, ISSN={["2169-4052"]}, url={http://dx.doi.org/10.1177/0361198120927400}, DOI={10.1177/0361198120927400}, abstractNote={This paper presents fleet utilization management processes for highway operations equipment based on actual tracked and reported usage data obtained from transportation agencies. The objective is to minimize total fleet utilization costs, including operational, purchase, and relocation expenses that yield the optimal utilization values and fleet composition of specific equipment types within each region in a year. The framework includes utilization prediction and optimization models, rather than relying on pre-determined utilization thresholds in existing strategies, to avoid under-utilization, over-utilization, or both. The prediction models are structured using equipment explanatory variables with their significant contributing factors, for example, annual equipment usage, annual fuel cost, downtime hours, age, and class code, to predict operational costs. The optimization model is formulated as a set of mathematical formulations, with embedded predictive models, that minimizes the total costs of (i) keeping an asset in-service using predictive annual operational cost functions, (ii) purchasing new assets in a region in the following year, and (iii) relocating assets by capturing the distance between regions. The costs include equipment purchase, operation, maintenance, and transportation expenses. The proposed framework captures the remedial actions to balance under-/over-utilized assets in the fleet in a cost-efficient manner. The proposed methodology is applied to utilization management of a set of operations equipment, and the findings of the dump trucks are presented. Several scenarios are designed to analyze the sensitivity of the costs to various decisions and parameters. The numerical experiments reveal that the proposed framework can facilitate the utilization prediction and management of highway operations equipment and save up to 16.6% in operational costs considering different demand scenarios.}, number={9}, journal={TRANSPORTATION RESEARCH RECORD}, author={Mirheli, Amir and Tajalli, Mehrdad and Mohebifard, Rasool and Hajibabai, Leila and Hajbabaie, Ali}, year={2020}, month={Sep}, pages={202–215} }
 @article{mohebifard_islam_hajbabaie_2019, title={Cooperative traffic signal and perimeter control in semi-connected urban-street networks}, volume={104}, url={http://dx.doi.org/10.1016/j.trc.2019.05.023}, DOI={10.1016/j.trc.2019.05.023}, abstractNote={This paper presents an integrated formulation and a distributed solution technique for cooperative signal control and perimeter traffic metering in urban street networks with various market penetration rates of connected vehicles. The problem is formulated as a mixed integer nonlinear program thus, does not scale well with the size of the network in a centralized optimization framework due to the presence of many mixed integer decision variables and nonlinear constraints. To address this limitation, we will develop a distributed model predictive control that distributes the network-level cooperative problem into several intersection-level sub-problems and coordinates their decisions. Our numerical analyses show that the proposed distributed methodology finds solutions to the problem in real-time with the optimality gap of at most 3.6% in our case studies. We have implemented the distributed methodology in Vissim and observed that cooperative signal timing and perimeter control yielded significant improvements in traffic operations. Our case study results show that the cooperative approach increases the number of completed trips by 6.0–12.8% and 10.9–11.0% and reduces the total travel times by 8.1–9.0% and 23.6–24.2% compared to independent signal control and independent perimeter control, respectively.}, journal={Transportation Research Part C: Emerging Technologies}, publisher={Elsevier BV}, author={Mohebifard, Rasool and Islam, S.M.A. Bin Al and Hajbabaie, Ali}, year={2019}, month={Jul}, pages={408–427} }
 @article{mohebifard_hajbabaie_2019, title={Distributed Optimization and Coordination Algorithms for Dynamic Traffic Metering in Urban Street Networks}, volume={20}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85050987048&partnerID=MN8TOARS}, DOI={10.1109/TITS.2018.2848246}, abstractNote={Previous research has shown that proper metering of entry traffic to urban street networks, similar to metering traffic on on-ramps in freeway facilities, reduces traffic congestion, especially in oversaturated flow conditions. Building on the previous research, this paper presents a real-time and scalable methodology for finding near-optimal metering rates dynamically in urban street networks. The problem is formulated into a mixed-integer linear program (MILP) based on the cell transmission model. We propose a distributed optimization scheme that decomposes the network level MILP into several link-level MILPs to reduce the complexity of the problem. We convert the link-level MILPs to linear programs to reduce the computational complexity further. Moreover, we create distributed coordination between the link-level linear programs to push the solutions toward optimality. The distributed optimization and coordination solution algorithm is incorporated into a rolling horizon technique to account for the time-varying demand and capacity and to reduce the computational complexity further. We applied the proposed solution technique to a number of case studies and observed that it was scalable and real time and found solutions that were at most 2.2% different from the optimal solution of the problem. Like the previous studies, we found significant improvements in network operations as a result of traffic metering.}, number={5}, journal={IEEE Transactions on Intelligent Transportation Systems}, author={Mohebifard, R. and Hajbabaie, A.}, year={2019}, pages={1930–1941} }
 @article{mohebifard_hajbabaie_2019, title={Optimal network-level traffic signal control: A benders decomposition-based solution algorithm}, volume={121}, url={http://www.sciencedirect.com/science/article/pii/S0191261518307616}, DOI={https://doi.org/10.1016/j.trb.2019.01.012}, abstractNote={This paper formulates the network-level traffic signal timing optimization problem as a Mixed-Integer Non-Linear Program (MINLP) and presents a customized methodology to solve it with a tight optimality gap. The MINLP is based on the Cell Transmission Model (CTM) network loading concept and captures the fundamental flow-density diagram of the CTM explicitly by considering closed-form constraints in the model and thus, eliminates the flow holding-back problem. The proposed solution algorithm is based on the Benders decomposition technique and decomposes the original MINLP to an equivalent Integer Program (IP) (Master problem), and a new MINLP (Primal problem). We will show that the new MINLP has only one optimal non-holding-back solution that can be found by a CTM simulation run. We will prove that the proposed solution technique guarantees convergence to optimal solutions with a finite number of iterations. Furthermore, we propose a dual estimation algorithm for the new MINLP (the Primal problem), which utilizes a simulation-based approach to generate Benders cuts instead of solving a complex optimization program. We applied the proposed solution technique to a simulated network of 20 intersections under various demand patterns and observed an optimality gap of at most 2% under all tested conditions. We compared the solutions of the proposed algorithm with two benchmark algorithms and found reductions in total travel time ranging from 7.0% to 35.7%.}, journal={Transportation Research Part B: Methodological}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2019}, pages={252–274} }
 @article{mohebifard_hajbabaie_2019, title={Optimal network-level traffic signal control: A benders decomposition-based solution algorithm}, volume={121}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85061027902&partnerID=MN8TOARS}, DOI={10.1016/j.trb.2019.01.012}, abstractNote={This paper formulates the network-level traffic signal timing optimization problem as a Mixed-Integer Non-Linear Program (MINLP) and presents a customized methodology to solve it with a tight optimality gap. The MINLP is based on the Cell Transmission Model (CTM) network loading concept and captures the fundamental flow-density diagram of the CTM explicitly by considering closed-form constraints in the model and thus, eliminates the flow holding-back problem. The proposed solution algorithm is based on the Benders decomposition technique and decomposes the original MINLP to an equivalent Integer Program (IP) (Master problem), and a new MINLP (Primal problem). We will show that the new MINLP has only one optimal non-holding-back solution that can be found by a CTM simulation run. We will prove that the proposed solution technique guarantees convergence to optimal solutions with a finite number of iterations. Furthermore, we propose a dual estimation algorithm for the new MINLP (the Primal problem), which utilizes a simulation-based approach to generate Benders cuts instead of solving a complex optimization program. We applied the proposed solution technique to a simulated network of 20 intersections under various demand patterns and observed an optimality gap of at most 2% under all tested conditions. We compared the solutions of the proposed algorithm with two benchmark algorithms and found reductions in total travel time ranging from 7.0% to 35.7%.}, journal={Transportation Research Part B: Methodological}, publisher={Elsevier}, author={Mohebifard, R. and Hajbabaie, A.}, year={2019}, pages={252–274} }
 @article{mohebifard_hajbabaie_2018, title={Dynamic traffic metering in urban street networks: Formulation and solution algorithm}, volume={93}, url={http://www.sciencedirect.com/science/article/pii/S0968090X18305795}, DOI={https://doi.org/10.1016/j.trc.2018.04.027}, abstractNote={Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.}, journal={Transportation Research Part C: Emerging Technologies}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2018}, pages={161–178} }
 @article{mohebifard_hajbabaie_2018, title={Dynamic traffic metering in urban street networks: Formulation and solution algorithm}, volume={93}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85048206051&partnerID=MN8TOARS}, DOI={10.1016/j.trc.2018.04.027}, abstractNote={Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.}, journal={Transportation Research Part C: Emerging Technologies}, publisher={Elsevier}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2018}, pages={161–178} }
 @inproceedings{mohebifard_hajbabaie_2018, title={Real-Time Adaptive Traffic Metering in a Connected Urban Street Network}, url={https://trid.trb.org/view/1497102}, booktitle={Transportation Research Board 97th Annual Meeting}, author={Mohebifard, Rasool and Hajbabaie, Ali}, year={2018} }