Queue Spillover Research Articles

Destination-Aware Coordinated Ramp Metering for Preventing Off-Ramp Queue Spillover and Mainstream Congestion

Destination-Aware Coordinated Ramp Metering for Preventing Off-Ramp Queue Spillover and Mainstream Congestion

Field‐tested signal controller to mitigate spillover using trajectory data

AbstractTrajectory data from connected vehicles (CVs) provide a continuous and reliable means of obtaining information that can be leveraged to optimize traffic signals. This paper proposes a real‐time traffic signal control method using CV trajectory data as the sole input. The primary goal of the proposed signal control method is to prevent queue spillover, which may significantly decrease the traffic efficiency on urban networks and induce high delays to the travelers. The proposed method formulates the signal control problem via a linear quadratic optimization model, considering the constraints related to the duration and variability of green lights in practical traffic signal control systems. Compared to conventional max‐pressure‐based methods, the optimization model offers enhanced efficiency in handling these constraints, making it highly suitable for real‐life implementation. The proposed method has undergone testing in both simulated environments and real‐world applications. In the simulation experiments, the proposed method has been demonstrated to effectively reduce spillover risks and outperform a conventional max‐pressure‐based approach even when the CV penetration rate is as low as 5%. In the real‐world experiment, the proposed method had been tested in a traffic network around the Beijing Capital International Airport for several months. The severity of spillovers, which was represented by two performance indicators, had been significantly reduced after implementing the proposed method.

Accounting for Traffic Dynamics in Pavement Maintenance Scheduling

Effective maintenance, rehabilitation, and reconstruction (MR&R) of road pavements is crucial for ensuring a safe and efficient transportation network. Existing research has proposed various models to aid decision-making in MR&R planning. However, these models often overlook the impact of traffic dynamics, such as shockwaves and queue spillovers caused by reduced capacity during maintenance activities. To bridge this gap, we present a novel methodology that incorporates traffic dynamics into the selection and sequencing of MR&R activities over a planning horizon. Our approach combines numerical evaluation of traffic flow theory using the link transmission model (LTM) with a deterioration model, considering travel time cost, fuel cost, and agency cost, to assess the optimal sequence of MR&R activities. To solve this multi-objective problem, we employ a genetic algorithm (GA) to minimize the objective function. Through a numerical example, we demonstrate the methodology’s effectiveness and sensitivity to pavement deterioration. The results clearly indicate the effectiveness of using the proposed methodology over the widely used Bureau of Public Roads (BPR)-function-based methods for pavement maintenance scheduling problems.

Adaptive Signal Control for Overflow Prevention at Isolated Intersections Based on Fuzzy Control

Nonrecurrent congestion on urban roads may cause overflow, possibly leading to gridlock at intersections. Signal control is one of the most important measures to prevent such phenomena. For nonrecurrent congestion with uncertain bottleneck capacity, however, existing signal control methods have mainly adopted the strategy of cutting off the green signal of the overflow movement while the release priority of green time has not been considered. Consequently, the green time allocated to overflow movements is too long, aggravating overflow and congestion. Therefore, a signal control method is proposed to prevent overflow caused by uncertain bottleneck capacity. The proposed method extends existing real-time adaptive signal control to explicitly consider the risk of queue spillover. When an overflow risk is detected, the green times of overflow movements will be reassigned using fuzzy control to determine the release priority depending on the queue length and red time. Numerical studies were conducted for two scenarios with different downstream bottleneck capacities. The results demonstrate that the proposed method not only outperforms existing methods in respect of intersection efficiency but also reduces the risk of overflow. The proposed method achieves a 27.7% to 33.8% reduction in the maximum queue length of overflow movements compared with a traditional adaptive signal control method and a 10.9% to 11.0% decrease compared with a modified signal control method with a cutting-off strategy. The sensitivity analysis indicates that the average delay resulting from the proposed method is 51.1% and 18.0% less than the delays resulting from the traditional and modified methods, respectively.

Optimization of dedicated bus lane location on a transportation network while accounting for traffic dynamics

A commonly used strategy to improve bus operations is to dedicate a lane for bus use only. However, this can reduce the available capacity for non-transit modes, in return increasing their delays and potentially creating queue spillovers. This paper proposes a bi-level optimization algorithm to determine dedicated bus lane locations on a network to reduce the total travel time of all network users while considering traffic dynamics. The proposed algorithm is applied to nine scenarios with different demand levels, demand patterns, bus routes, and base modal split values. The results show that, as expected, the implementation of bus lanes often increases car delay. However, the results also show that a net benefit in terms of total passenger travel time can be achieved by implementing bus lanes at strategic locations. The bus lane locations found as a result of the optimization process largely depend on the demand pattern, demand level, bus routes, and base modal split values. For an under-saturated demand scenario, the best performing solution finds that bus lanes should be implemented on almost all bus routes. For saturated and congested demand scenarios, links in the congested parts of the network are avoided in the best performing solution. However, the result of the sensitivity analysis shows that implementing bus lanes on links in the congested parts of the network can also be beneficial in certain scenarios.

Traffic scheduling and control in fully connected and automated networks

Taking advantages of connected and autonomous vehicle (CAV) technologies, this paper proposes to optimize the departure times, travel routes, and longitudinal trajectories of CAVs, as well as signal timings at intersections to achieve a stable traffic state, where no vehicles need to stop before entering any intersection and no queue spillover occurs at any intersection. The departure times, travel routes and signal timings are optimized in central controller, while the vehicle trajectories can be optimized by distributed roadside processors, which together form a hierarchical traffic management scheme. The conventional NEMA phasing structure is applied for signal control, so that no additional safety issue needs to be considered inside crowded intersections. Two mixed-integer nonlinear programs are proposed for achieving the stable traffic state on arterials and in grid networks. Numerical tests are performed to demonstrate the two programs.

Determining Optimum Transit Signal Priority Implementation Locations on a Network

Transit signal priority (TSP) can be used to improve bus operations at intersections. However, implementing TSP can often increase the delay of non-transit modes. Therefore, it is necessary to evaluate the effects of TSP both on car and bus operations to determine optimal locations to equip with TSP to improve network operations. To do so, the link transmission model is used to evaluate the travel times of both cars and buses on the network while accounting for dynamic queuing and queue spillover. This method is then used to evaluate different combinations of locations for TSP implementation and to determine the optimal configuration that can minimize the total travel time of network users, including bus and car passengers. The sensitivity of the proposed algorithm to demand level, changes in transit network, implementation strategy, and solution method are also evaluated. For all tested scenarios, the TSP configurations found to be optimum achieve a significant reduction of total bus passenger travel time while creating minimal effect on total car travel time. The results reveal that in general, not all intersections should be equipped with TSP, and intersections that carry high demand within a network are promising locations for TSP implementation to reduce the total travel time of network users. Additionally, it is found that the total travel time of network users can be further decreased by only activating TSP for buses with more than a certain number of on-board passengers.

Variable Speed Limits for Motorway Off-Ramp Queue Protection

Motorway off-ramp is a main source of traffic congestion and collisions. Heavy diverging traffic and associated lane changing to off-ramp slows down the mainline traffic speed. When the off-ramp queue spills onto the motorway mainline, it may cause a major breakdown of the motorway capacity and a significant threat to the traffic safety. This paper proposes using Variable Speed Limits (VSL) to protect the motorway off-ramp queue to improve safety in congested diverging areas through microsimulation tests. To support timely activation of VSL in advance of queue spill-over, a proactive strategy is proposed based on off-ramp queue estimation and new arrival prediction in the near term. This process determines the estimated queue size on the off-ramp in the near-term, on which the decision to change speed limits is made. VSL can effectively slow down traffic as it is mandated and enforceable in Queensland, Australia. As a possible scenario, reduced speed limits could make drivers more attentive to the surrounding condition, and prepared for a sudden braking of the leading car. This paper analyses and quantifies this possible effect of VSL on traffic safety and efficiency using the microsimulation approach.

Integration of Model-Based Signal Control and Queue Spillover Control for Urban Oversaturated Signalized Intersection

An improved model-based predictive control approach integrating model-based signal control and queue spillover control is proposed in this paper, which includes three modules: model-based signal control, queue spillover identification, and spillover control to deal with the problem of traffic congestion for urban oversaturated signalized intersection. The main steps are as follows. First of all, according to the real-time traffic flow data, the green time splits for all intersections will be solved online by the model-based signal control controller whose optimization model is based on model-predictive control (MPC) strategy. Second, the queue spillover identification module will be used to detect the potential queue spillover. If potential queue spillover is detected, the spillover control module will be activated to prevent vehicles from the upstream link of the link with possible spillover from entering the downstream link to avoid traffic congestion. The experiment is performed on a simulated road network. The results verify that the proposed scheme can significantly decrease the delay which reflects the overall performance of the studied intersection.

Optimal Type-2 Fuzzy System For Arterial Traffic Signal Control

Arterial traffic is the artery of urban transport and loads huge traffic pressure. In order to alleviate its traffic pressure effectively, a coordinated arterial traffic type-2 fuzzy logic control (FLC) method is proposed. First, arterial traffic flow model and evaluation index model are set up, in which the turning vehicles and lane length are given full consideration. The traditional queue spillover phenomenon in the traffic models can be prevented here. Second, aiming at the coordination and dynamic uncertainty problem in arterial traffic, a coordinated arterial traffic type-2 fuzzy coordination control method is put forward. It consists of two-layer type-2 fuzzy controller, the basic control layer and the coordination layer. The former allocates green time according to the traffic situation of each intersection, while the latter adjusts each intersection’s green time on basis of the vehicles between the intersection and the downstream intersections for the purpose of enlarging green wave band. Finally, in order to configure the high-dimensional complex parameters of the coordinated two-layer type-2 FLC effectively, the parameters of membership function and the rules of the two controllers are optimized alternately by gravitational search algorithm. The simulation results verify the effectiveness of the proposed method from several aspects.

Queue Spillover Management in a Connected Vehicle Environment

To alleviate the queue spillovers at intersections of urban roads during rush hours, a solution to the cross-spill problem based on vehicle networking technologies is proposed. This involves using connected vehicle technology, to realize the interactive information on vehicle and intersection signal control. The maximum control distance between intersections is determined by how vehicles are controlled and would travel in that connected environment. A method of calculating overflow tendency towards intersection queuing is also proposed, based on the maximum phase control distance. By this method, the intersection overflow is identified, and then the signal phases are re-optimized according to the requirements of different phases. Finally, overflow prevention control was also performed in this study. The VISSIM simulation results show that the method can better prevent the overflow of queues at intersections.

Signal Cooperative Control With Traffic Supply and Demand on a Single Intersection

Traffic signal control is widely used at intersection to improve its operation efficiency. However, the existing signal control systems cannot satisfy the control requirements under unsaturated, saturated, and oversaturated conditions, which will induce queue spillover, even network deadlock. A signal Cooperative Control method with traffic Supply and Demand (CCSD) on a single intersection is put forward to maximize the efficiency and avoid queue spillover by the cooperation between traffic supply and demand. A general CCSD control framework is constructed by the control relationship description and discrete-time statespace equations. Furthermore, the uniform matrix description of CCSD is put forward under the framework to fast solve the problem by matrix calculation. An artificial intelligence planning model on CCSD is established by an objective function compromising between throughput and fairness to satisfy the control requirements under dynamic unknown traffic environment. CCSD is compared with the Webster method and capacity-aware back-pressure (CABP) control in the experiments by both the simulation data and investigation data under unsaturated, saturated, and oversaturated conditions. The results show that CCSD is superior to CABP control and the Webster method in the throughput, the number of stops, and stop time, and can avoid the queue spillover. Accordingly, CCSD can be used to improve the efficiency and avoid queue spillover at intersection under all traffic conditions.

Real-time route diversion control at congested freeway off-ramp areas

This paper develops, investigates and demonstrates real-time route diversion policies in cases where recurrent freeway traffic congestion is created due to a saturated off-ramp. In particular, the proposed route diversion policies attempt to avoid the off-ramp queue spill-over onto the freeway mainstream and the resulting freeway congestion by appropriately re-routing the freeway vehicles through nearby off-ramps towards the same destination. The proposed route diversion concepts are based on feedback control laws and are tested for a hypothetical, but quite typical, network infrastructure and three different traffic scenarios by use of macroscopic simulation. In the first traffic scenario, the user-optimal conditions may be achieved without off-ramp queue spill-over and creation of mainstream congestion; thus the route guidance system may propose an alternative route without any disbenefit for the compliant drivers. In the second case, the user-optimal conditions may be achieved only after the off-ramp queue spills back to the mainstream freeway; thus the route diversion system will have to assume sufficient compliance to the proposed route choice; or be based on mandatory actions, such as temporary off-ramp closures. Finally, in the third examined case, the user-optimal conditions cannot be achieved, due to the traffic conditions on the alternative route, thus the route diversion system should decide for the temporary off-ramp closure, when and to the extent needed, in order to prevent formation of mainstream congestion. The obtained simulation results are compared to the case where no route guidance is applied to the network and reveal interesting features and the potential for significant improvements.

Integration of adaptive signal control and freeway off-ramp priority control for commuting corridors

Congestion at the downstream of an off-ramp often propagates the traffic queue to the freeway mainline, and thus reduces the freeway capacity at the interchange area. To prevent such potential queue spillover and improve traffic control efficiency over the entire corridor, this study develops an integrated control system which includes three primary functions: off-ramp queue estimation, arterial adaptive signal operations, and freeway off-ramp priority control. Using detected flow data, the system firstly estimates the queue length on the target off-ramp. If no potential queue spillover is predicted, the adaptive signal control function will then adjust the intersection signal timings and provide dynamic signal progression to critical path-flows. Otherwise, the off-ramp priority control function will be activated to clear the queuing vehicles at the off-ramp. To evaluate the effectiveness of the proposed system, this study has conducted numerical studies on a freeway interchange using a well-calibrated simulation platform. The experimental results reveal that the overall network performance can indeed be improved under the proposed control system, compared with other operational strategies. Further analyses of freeway time-dependent travel time distribution also evidence the effectiveness of the proposed system in preventing off-ramp queue spillover.

Development of signal optimization models for asymmetric two-leg continuous flow intersections

Despite extensive studies have been reported to address the operational issues of full Continuous Flow Intersection (CFI) in the literature, the asymmetric two-leg CFI, which is more applicable in practice, has not received adequate attentions yet. To satisfy such need, this study develops two signal optimization models for asymmetric CFI based on its unique geometric features. The first proposed model, following a two-step procedure, determines the cycle length, phase design and sequence, and green split in the first step and optimizes intersection offset in the second step. To benefit both intersections’ capacity maximization and signal progression design by optimizing phase plan and sequence, the second proposed model takes the Mixed-Integer-Linear-Programming (MILP) technique to concurrently optimize all signal control variables. With extensive case studies on a field site in Maryland, the simulation results prove that the proposed models can effectively provide signal progression to critical path-flows and prevent the potential queue spillover on the short turning bays/links. Further comparisons between the two proposed models reveal that the second model is more flexible in designing phase plan but the first model performs better in reducing link queue length.

Four-phase or two-phase signal plan? A study on four-leg intersection by cellular automaton simulations

The proper setting of traffic signals at signalized intersections is one of the most important tasks in traffic control and management. This paper has evaluated the four-phase traffic signal plans at a four-leg intersection via cellular automaton simulations. Each leg consists of three lanes, an exclusive left-turn lane, a through lane, and a through/right-turn lane. For a comparison, we also evaluate the two-phase signal plan. The diagram of the intersection states in the space of inflow rate versus turning ratio has been presented, which exhibits four regions: In region I/II/III, congestion will propagate upstream and laterally and result in queue spillover with both signal plans/two-phase signal plan/four-phase signal plan, respectively. Therefore, neither signal plan works in region I, and only the four-phase signal plan/two-phase signal plan works in region II/III. In region IV, both signal plans work, but two-phase signal plan performs better in terms of average delays of vehicles. Finally, we study the diagram of the intersection states and average delays in the asymmetrical configurations.

An Adaptive Signal Control Scheme to Prevent Intersection Traffic Blockage

In this paper, we present an adaptive signal control scheme to prevent intersection traffic blockage resulted from vehicle queue spillover. A method to identify vehicle queue spillover condition through simplified shockwave analysis is developed. Instead of measuring the vehicle queue length or locating the end of queue directly, this method relies on the vehicle speed which is more feasible to measure in practice. The adaptive traffic signal control scheme is designed to prevent potential intersection traffic blockage, and adaptively allocates green time to appropriate signal phases. At the end, a simulation study is carried out to evaluate the proposed adaptive control scheme. The results show that the scheme can effectively prevent intersection traffic blockage and significantly improve the performance of the intersection in terms of vehicle delay.

Operational Analysis and Signal Design for Asymmetric Two-Leg Continuous-Flow Intersection

Despite the increasing implementation of the continuous-flow intersection (CFI) in practice, the development of reliable guidelines for its operational analysis and signal design remains in its infancy, especially for the popular two-leg asymmetric CFI design, because of the relatively low cost and desirable efficiency. For best use of the capacity of such a CFI design, a signal optimization model is presented; it can serve as an effective tool for engineers to design the cycle length, phase duration and sequences, and offsets for both its primary and subintersections. By accounting for the commonly encountered constraints of short bay length for turning movements and the interrelations between critical flow movements, the proposed model can prevent queue spillover on left-turn bays and offers concurrent progression for both the through and left-turn flows. To ensure the applicability and effectiveness of the proposed model, this study further uses the data from a proposed asymmetric CFI in Maryland for performance evaluation. The results of extensive simulation with field data confirm that the proposed signal optimization with its capability to account for all physical constraints and flow conflicts can indeed perform as expected; that is, it offers concurrent progression to both through and left-turning flows and prevents any queue from spilling over its designated bay.

Real-Time Merging Traffic Control at Congested Freeway Off-Ramp Areas

This study presents a real-time merging traffic control algorithm to mitigate the problem of freeway congestion resulting from an overspilling off-ramp. The proposed control algorithm aims at maximizing the merge area outflow of the surface street and at the same time preventing the off-ramp queue spillover into the freeway mainstream and the resulting freeway congestion. The potential benefits obtained by applying the proposed control concept are demonstrated by the use of microscopic simulation applied to a real freeway network where recurrent freeway traffic congestion is created as a result of an overspilling off-ramp. The simulation results demonstrated that the proposed control algorithm may improve the prevailing traffic conditions, preventing the formation of freeway congestion and benefiting freeway drivers and surface street users.

A Program for Simultaneous Network Signal Timing Optimization and Traffic Assignment

This study formulates a program for simultaneous traffic signal optimization and system optimal traffic assignment for urban transportation networks with added degree of realism. The formulation presents a new objective function, i.e., weighted trip maximization, and explicit constraints that are specifically designed to address oversaturated conditions. This formulation improves system-wise performance while locally prevents queue spillovers, de-facto reds, and gridlocks. A meta-heuristic algorithm is developed that incorporates microscopic traffic flow models and system optimal traffic assignment in genetic algorithms. This solution technique efficiently optimizes signal timing parameters, at the same time solves system optimal traffic assignment, and accounts for oversaturated conditions and different driver's behaviors. This study also proposes a framework to calculate an upper bound on the value of the objective function by solving the problem while several constraints (i.e., network loading and traffic assignment) are relaxed. An empirical case study for a portion of downtown Springfield, Illinois has been conducted under four demand patterns. Findings indicate that our solution approach can solve the problem effectively. Several managerial insights have also been drawn.