Conventional Signal Control Research Articles

Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic

Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NOx) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NOx emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NOx emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NOx emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic.

Junction Management for Connected and Automated Vehicles: Intersection or Roundabout?

The concept of signal-free management at road junctions is tailored for Connected and Automated Vehicles (CAVs), in which the conventional signal control is replaced by various right-of-way assignment policies. First-Come-First-Served (FCFS) is the most commonly used policy. In most proposed strategies, although the traffic signals are replaced, the organization of vehicle trajectory remains the same as that of traffic lights. As a naturally signal-free strategy, roundabout has not received enough attention. A key motivation of this study is to theoretically compare the performance of signalized intersection (I-Signal), intersection using FCFS policy (I-FCFS), roundabout using the typical major-minor priority pattern (R-MM), and roundabout adopting FCFS policy (R-FCFS) under pure CAVs environment. Queueing theory is applied to derive the theoretical formulas of the capacity and average delay of each strategy. M/G/1 model is used to model the three signal-free strategies, while M/M/1/setup model is used to capture the red-and-green light switch nature of signal control. The critical safety time gaps are the main variables and are assumed to be generally distributed in the theoretical derivation. Analytically, I-Signal has the largest capacity benefiting from the ability to separate conflict points in groups, but in some cases it will have higher delay. Among the other three signal-free strategies, R-FCFS has the highest capacity and the least average control delay, indicating that the optimization of signal-free management of CAVs based on roundabout setting is worthy of further study.

Conditions for Setting Exclusive Pedestrian Phases at Two-Phase Signalized Intersections considering Pedestrian-Vehicle Interaction

In order to analyze the effectiveness of setting exclusive pedestrian phase (EPP) under different vehicle yielding rates, the effect of EPPs on traffic efficiency is studied and a setting condition of EPP considering pedestrian-vehicle interaction is proposed in this paper. First, the main factors influencing the behavior of vehicles and pedestrians during pedestrian-vehicle interaction are analyzed, and a pedestrian-vehicle interaction (PVI) model at the crosswalk of urban road is established. Second, assuming that vehicle arrival obeys the Poisson distribution, the delay models of vehicle passengers and pedestrians crossing the street at the intersection are established, and taking the total delay of traffic participants as the main index, the setting condition of EPP are proposed. Third, based on the video of pedestrian-vehicle interaction at crosswalks, the parameters of the proposed model are calibrated. Through sensitivity analysis, the change of the total delay of traffic participants is analyzed under different conditions of pedestrian and vehicle arrival rates. Finally, by introducing pedestrian-vehicle interaction rules, a cellular automata (CA) simulation platform of pedestrian-vehicle interaction in crosswalk is established; based on the field data of Shanghai, a simulation model of intersection is established, and the total delay, queue length, and vehicle throughput under conventional signal control plan and EPP plan are compared. The results show that the pedestrian-vehicle interaction process has a great influence on the total delay of traffic participants at intersections, and pedestrian-vehicle interaction should be considered in the setting conditions of EPP. Under the same condition of vehicular flow, the more the pedestrian flow is, the smaller the delay increment will be. The higher the vehicle yielding rate is, the smaller the delay increment will be after setting EPP.

Temporal-spatial dimension extension-based intersection control formulation for connected and autonomous vehicle systems

Traffic congestion has become a serious issue worldwide due to the rapid increase in population and traffic demands. Advances in connected automated vehicle (CAV) technology demonstrate the potential to improve traffic mobility and safety performance at intersections. An advanced intersection control system is proposed in this study to coordinate vehicle trajectories and ensure safety and operation efficiency at intersections. A temporal-spatial dimension extension-based trajectory coordination model is developed by formulating all possible trajectories of vehicles at the intersection. Correspondingly, according to the trajectory coordination model, two signal-free control algorithms, including the priority-based algorithm and the Discrete Forward-Rolling Optimal Control (DFROC) algorithm are proposed in this study to manage vehicles at the intersection. These two algorithms, together with the FCFS policy, are compared with the conventional signal control method in a SUMO-based simulation platform. Experimental results indicate that the proposed algorithms outperform the signal control method in terms of reducing total traffic delays at intersections and increasing intersection capacity and operation efficiency.

Multi-Agent-Based Data-Driven Distributed Adaptive Cooperative Control in Urban Traffic Signal Timing

Data-driven intelligent transportation systems (D2ITSs) have drawn significant attention lately. This work investigates a novel multi-agent-based data-driven distributed adaptive cooperative control (MA-DD-DACC) method for multi-direction queuing strength balance with changeable cycle in urban traffic signal timing. Compared with the conventional signal control strategies, the proposed MA-DD-DACC method combined with an online parameter learning law can be applied for traffic signal control in a distributed manner by merely utilizing the collected I/O traffic queueing length data and network topology of multi-direction signal controllers at a single intersection. A Lyapunov-based stability analysis shows that the proposed approach guarantees uniform ultimate boundedness of the distributed consensus coordinated errors of queuing strength. The numerical and experimental comparison simulations are performed on a VISSIM-VB-MATLAB joint simulation platform to verify the effectiveness of the proposed approach.

Traffic design and signal timing of staggered intersections based on a sorting strategy

A staggered intersection is a special type of intersection in a road network. Its geographical characteristics consist of two T-legged intersections that cause the lost time per cycle to become longer than at cross intersections under conventional signal control, thus leading to low intersection efficiency. This article shows that the problem can be eliminated at the left–right type of staggered intersection by channelization and signal phasing, based on a sorting strategy and pre-signal, which reduce the amount of lost time during the signal cycle using the split distance as the sorting area. VISSIM was used to model and analyze the proposed method as well as the conventional method for comparison purposes. The simulation revealed that the proposed method reduced the average delays and maximum queue lengths in each movement and for the entire intersection, both in the peak hours and in the off-peak hour.

Development of a Distributed Cooperative Vehicles Control Algorithm Based on V2V Communication

This paper presents a new distributed Cooperative Vehicles Control (CVC) algorithm without any infrastructure. The algorithm is developed to manipulate individual vehicles’ travelling maneuvers based on V2V communication, so that vehicles can cross the intersection safely and rapidly. Assuming that all vehicles are fully automated, by eliminating the collision probability of vehicles at intersections, the CVC algorithm seeks a safe maneuver for vehicles approaching the intersection and manipulates them. To evaluate the performance of algorithm, we develop an integrated simulation framework. The results show that the CVC algorithm can significantly improve the efficiency of intersection compared with conventional signal control system under varying congestion conditions, moreover, the impact of communication performance on algorithm is also considered.

A Learning-based Adaptive Group-based Signal Control System under Oversaturated Conditions

The operation of traffic signal control is of significant importance in traffic management and operation practice, especially under oversaturated condition during the morning and afternoon peak hours. However, the conventional signal control systems showed the limitations in signal timing and phasing under oversaturated situations. This paper proposes a multi-agent adaptive signal control system in the context of group-based phasing techniques. The adaptive signal control system is able to acquire knowledge on-line based on the perceived traffic states and the feedback from the traffic environment. Reinforcement learning with eligibility trace is applied as the learning algorithm in the multi-agent system. As a result, the signal controller makes an intelligent timing decision. Feature-based function approximation method is incorporated into reinforcement learning framework to improve the learning efficiency as well as the quality of signal timing decisions. The learning process of the learning-based signal control is carried out with the aid of a microscopic traffic simulation model. A benchmarking system, an optimized group-based vehicle actuated signal control system, is compared with the proposed adaptive signal control systems. The simulation results show that the proposed adaptive group-based signal control system has the potential to improve the mobility efficiency under different congested situations.

Applying a Network Programming Algorithm to a Networkwide Traffic Control Scheme: Simulation-Based Performance Studies

A complete optimal formulation of a network traffic control scheme in the form of arc flows in a time-expanded network is presented. The platoon dispersion model used in the proposed optimal control formulation forms linear constraints. The integer-linear network programming formulation is solved by using a modified network simplex and branch-and-bound scheme. The formulation does not assume fixed cycle lengths or phase sequences. It assumes full information on external inputs, but it can be incorporated into a sensor-based environment, as well as into a feedback control framework. The integer-linear program formulation may not be efficiently solved by standard simplex and branch-and-bound techniques. Network programming formulations that can be used to handle the linear equations and the integer constraints at the intersections are discussed. A special-purpose network simplex algorithm for fast solution is also mentioned. The optimization model takes the form of mixed integer-linear programming. The control strategies generated by these optimization models were compared with those derived from conventional signal timing models by using the TRAF-NETSIM microscopic simulation model. The proposed optimization models consistently outperformed the conventional signal control methods with respect to the system delay objective. It was found that the optimization models successfully produced optimal signal timing plans for the various signalized intersections, including simulated and real-world networks.

Adaptive Signal Control System with Online Performance Measure for a Single Intersection

An adaptive signal control system with an online signal performance measure is introduced. Unlike conventional signal control systems, the proposed method uses real-time delay estimation and an online signal timing update algorithm. As a signal performance measure, intersection delay for each phase is measured in real-time via an advanced surveillance system that reidentifies individual vehicles at upstream and downstream stations by using vehicle waveforms obtained from advanced inductive loop detectors. In each cycle, the signal timing plan is optimized based on the delay estimated from the vehicle reidentification technology. The main thrust of the algorithm is the online control capability utilizing direct intersection delay measures. A description of the overall control system architecture and the optimization algorithm is addressed. Performance of the proposed system is evaluated with a high-performance microscopic traffic simulation program, Paramics, and the preliminary results prove the promising properties of the proposed system.