Ethics; Excellence in Engineering Education, Research, and Practice; Professionalism; and the Growth of the IEEE Intelligent Transportation Systems Society: Incoming President’s Message [President’s Message]

IEEE Intelligent Transportation Systems Magazine · 2026-01-01

Rejection of Sinusoidal Disturbances with Unknown Slowly Time-Varying Parameters For MIMO Linear Time-Varying Systems

IEEE Transactions on Automatic Control · 2026-01-01

Optimal coordinated platoon lane change in highways with mixed traffic

Vehicular Communications · 2025-04-18

Central Coordination of Connected Autonomous Vehicles At A Signal Free Intersection For Movement Free Lanes

2025-04-18

The cost of equipping and maintaining traffic signals at intersections is high enough to motivate approaches where physical equipment is replaced with a virtual one by taking advantage of connectivity and fast computations. In this paper, we propose a centralized intersection controller for real-time coordination of dynamic traffic demands of Connected and Autonomous Vehicles (CAVs) at a signal-free intersection. The proposed method comprises of two main components: (i) a centralized intersection controller which assigns a safe reference trajectory based on CAV's location, speed, origin before the intersection and desired destination after the intersection; (ii) vehicle controllers on-board of each CAV, which communicate with the centralized intersection controller its location, speed, origin before the intersection and desired destination after the intersection, and dynamical characteristics. These controllers are also capable of following the assigned collision free trajectory. We assess the performance of our method through multiagent simulations in CARLA's open source environment, benchmarking it against a traffic light controlled intersection that uses an optimal cycle length and phase plan derived from Webster's method. Our simulation results indicate that the proposed intersection controller reduces average delays and increases average flow rate per lane compared to a traffic lights. As expected the quantity of improvement depends on the demand.

Integrated Freeway Traffic Control Using <i>Q</i>-Learning With Adjacent Arterial Traffic Considerations

IEEE Transactions on Intelligent Transportation Systems · 2025-04-22 · 4 citations

Numerous studies have shown the effectiveness of intelligent transportation system techniques such as variable speed limit (VSL), lane change (LC) control, and ramp metering (RM) in freeway traffic flow control. The integration of these techniques has the potential to further enhance the traffic operation efficiency of both freeway and adjacent arterial networks. In this regard, we propose a freeway traffic control (FTC) strategy that coordinates VSL, LC, RM actions using a Q-learning (QL) framework which takes into account arterial traffic characteristics. The signal timing and demands of adjacent arterial intersections are incorporated as state variables of the FTC agent. The FTC agent is initially trained offline using a single-section road network, and subsequently deployed online in a connected freeway and arterial simulation network for continuous learning. The arterial network is assumed to be regulated by a traffic-responsive signal control strategy based on a cycle length model. Microscopic simulations demonstrate that the fully-trained FTC agent provides significant reductions in freeway travel time and the number of stops in scenarios with traffic congestion. It clearly outperforms an uncoordinated FTC and a decentralized feedback control strategy. Even though the FTC agent does not control the arterial traffic signals, it leads to shorter average queue lengths at arterial intersections by taking into account the arterial traffic conditions in controlling freeway traffic. These results motivate a future research where the QL framework will also include the control of arterial traffic signals.

Observer-Based Decentralized Adaptive Control of Interconnected Nonlinear Systems With Output/Input Triggering

IEEE Transactions on Cybernetics · 2025-03-11 · 6 citations

In this article, a double-channel event-triggered control method is developed for nonlinear uncertain interconnected systems using backstepping techniques, which introduces event-triggering mechanisms at both the sensor and controller sides. Using event-triggering mechanism at the sensor side presents a challenge to the backstepping control design as the discontinuous state/output signals received at the controller side result in nondifferentiable virtual control signals. This challenge becomes more pronounced when considering more general types of event-triggering mechanisms. Compared with existing methods, this article proposes a different idea with three innovative features: 1) the proposed event-triggering mechanism does not require the calculation of virtual control signals at the sensor side before transmitting them to the controller side; 2) the output triggering is considered directly, and there is no need to design separate controllers for the two communication scenarios without and with event-triggering, thereby avoiding the effect of errors caused by processing substitutions; and 3) it necessitates the online update of only one parameter estimator, avoiding the issue of over-parameterization. Finally, we validate the effectiveness and advantages of the proposed decentralized event-triggered control approach through a numerical case study.

Throughput Maximizing Takeoff Scheduling for eVTOL Vehicles in On-Demand Urban Air Mobility Systems

IEEE Transactions on Intelligent Transportation Systems · 2025-12-11

Urban Air Mobility (UAM) offers a solution to current traffic congestion by using electric Vertical Takeoff and Landing (eVTOL) vehicles to provide on-demand air mobility in urban areas. Effective traffic management is crucial for efficient operation of UAM systems, especially for high-demand scenarios. In this paper, we present a centralized framework for conflict-free takeoff scheduling of eVTOLs in on-demand UAM systems. Specifically, we provide a scheduling policy, called VertiSync, which jointly schedules UAM vehicles for servicing trip requests and rebalancing, subject to safety margins and energy requirements. We characterize the system-level throughput of VertiSync, which determines the demand threshold at which the average waiting time transitions from being stable to being increasing over time. We show that the proposed policy maximizes throughput for sufficiently large fleet size and if the UAM network has a certain symmetry property. We demonstrate the performance of VertiSync through a case study for the city of Los Angeles, and show that it significantly reduces average passenger waiting time compared to a first-come first-serve scheduling policy.

Central Coordination of Connected Autonomous Vehicles at a Signal Free Intersection

IEEE Transactions on Intelligent Transportation Systems · 2025-12-11

Intersections are major sources of traffic delays and accidents. Unlike traffic light controlled intersections, signal free intersections coordinate safe vehicle crossings individually, offering greater flexibility and the potential to eliminate unnecessary stops. Moreover, the high cost of installing and maintaining physical traffic signals motivates the adoption of virtual infrastructure enabled by connectivity and fast computation. This paper proposes a centralized intersection controller for real-time coordination of the dynamic traffic demands of Connected and Autonomous Vehicles (CAVs) at a signal free intersection. The proposed method consists of a centralized intersection controller that, in real time, assigns each CAV a safe reference path and desired speed based on its location, current speed, onboard vehicle controller transient response, and origin–destination pair, rather than transmitting direct acceleration commands to individual vehicles. Due to errors in measuring acceleration and susceptibility to delays, tracking a reference speed is a more robust and practical approach as it takes into account the ability of onboard vehicle controllers to track speeds in a more accurate way than accelerations. Moreover, the proposed approach allows vehicles to be in any lane when making left and right turns, which has been shown to improve efficiency. The proposed method was evaluated via multi-agent simulations in the open-source CARLA environment. It was compared against four benchmark methods: fixed- and variable cycle time traffic light controlled intersections (with variable cycle and phase plan optimized using Webster’s method) and two state-of-the-art signal free coordination methods. Results show that the proposed approach reduces average delays and increases the average lane flow rate compared to these benchmarks. As expected, the magnitude of improvement depends on the demand.

Decentralized prescribed-time input-to-state stabilization for interconnected normal form nonlinear systems

Automatica · 2025-07-15 · 9 citations

Decentralized Prescribed-Time Control of Robotic Arm-Finger Systems for Grasping and Moving Tasks

IEEE Transactions on Cybernetics · 2025-07-30 · 6 citations

The control of a humanoid robot equipped with one arm and multiple fingers, designed primarily for grasping and manipulating various objects, is investigated. Synchronizing the movements of the fingers is a challenging task, as each joint must reach the desired angle simultaneously to ensure a firm grasp. The success of this task hinges on the synchronization of convergence times for each finger joint; otherwise, the object may slip or escape. This challenge is further intensified by uncertainties in the dynamics of the hand or the object. We present decentralized prescribed-time tracking control strategies for the dynamical system comprising the arm-finger combination. In this system, the fingers are primarily used for grasping the object while the arm is responsible for moving, tilting, or flipping it. To streamline the controller structure and simplify the stability analysis, we design a linear controller based on the maximum eigenvalue of a parameter matrix and establish a new technical lemma, which paves the way for the stability analysis of the prescribed-time tracking and the reduction of the input efforts of the actuator. We develop robust and decentralized adaptive control schemes separately for the arm and fingers, achieving better transient performance with less prior knowledge and lower computation costs. Finally, we validate the proposed controller's performance through kinematic simulations of grasping and moving tasks in 3-D, alongside numerical simulations that demonstrate the tracking performance of our algorithm in the joint space.