Fixed Signal Control Research Articles

Reservation-Based Cooperative Ecodriving Model for Mixed Autonomous and Manual Vehicles at Intersections

Oversaturation has become a serious issue for urban intersections worldwide due to the rapid increase in population and traffic demands. The emergence of connected and automated vehicle (CAV) technologies demonstrates the potential to improve oversaturated arterial traffic. Integrating vehicular control and intersection controller optimization into a single process based on CAV technologies can optimize the performance of mixed traffic flow scenarios with various levels of CAV market penetration. This paper proposes an efficient reservation-based cooperative ecodriving model (RCEM) for an isolated intersection under partial and complete CAV market penetration, which can simultaneously optimize the CAV trajectories and intersection controller. CAVs are utilized to precluster manual vehicles into a platoon to improve vehicle passage efficiency. Then, a heuristic-based algorithm is developed to effectively obtain an optimal solution. The proposed RCEM scheme is compared with fixed signal control and actuated signal control in a Simulation of Urban MObility (SUMO)-based platform. Experimental results prove that the RCEM scheme outperforms the fixed signal control and actuated signal control in terms of stop delay, fuel consumption, and emissions under the condition of low levels of CAV penetration. Sensitivity analysis indicates that the system performance further improves as the CAV penetration rate increases, and the stop delay is almost eliminated when the CAV market penetration reaches 100%. Furthermore, the vehicle delay fluctuation under left-turning rates ranging from 5%-75% is 4.4 sec, which is far better than the vehicle delay fluctuation of the fixed signal control (176 sec) and actuated control (65.6 sec).

Delay models for Signalised Intersections with Vehicle Actuated Controlled system in Heterogeneous Traffic Conditions

Delay is a critical parameter used to assess the performance of signalised intersections. Non-deterministic arrival and departure rates of vehicles at intersectionseffect the determination of delay. Furthermore, driver behaviour, vehicle characteristics, and type of signal control system at intersectionwere also influencing parameters. Previous literature has offered analytical and empirical models to estimate the average delay using hourly traffic flow data and a fixed cycle time. In India, major signalised intersections on urban arterial roads are controlled with vehicle actuated controlled system. In the present study, Simpson’sone third rule was applied to estimate the overall delay by using arrival rate and departure rate of vehicles in everycycle. In addition, the current studydevelopedregression-based delay model and modified the Indo-HCM model by changing incremental delay term in themodels. Thisensuredaccurateestimation of the delays at signalised intersections in both the VAC and fixed signal control systems. The proposed modelswere statistically significant, with R2values of 0.89 and 0.51, respectively.

Connected Vehicles Versus Conventional Traffic Congestion Mitigation Measures: An Operational Economic Analysis

This paper conducted an operational, economic analysis to assess alternative solutions to traffic congestion. They involved integrating adaptive traffic signal control (ATSC) with connected vehicle technology (ATSC-CV) and the application of various conventional and unconventional solutions. The studied conventional scenarios include signal timing optimization, signal actuation, and upgrading existing intersections to interchanges. There were unconventional scenarios involving converting two intersections to interchanges and the third to a continuous green-T intersection (CGTI). Different unconventional alternatives involved deploying ATSC-CV-based systems assuming varying market penetration rates (MPRs). The operational performance of each alternative was analyzed using VISSIM microsimulation software. To model the driving behavior of CVs, Python programming language was used through the COM interface in VISSIM. One-way analysis of variance (ANOVA) and post-hoc testing results indicate that implementing any suggested alternative would substantially decrease the mean vehicular travel time compared to the fixed signal control strategy currently implemented. Specifically, the ATSC-CVbased systems yielded notable travel time reductions ranging from 9.5% to 21.3%. Also, ANOVA results revealed that the highest benefit-to-cost ratio among all alternatives belonged to scenarios in which the MPRs of CVs were 100%. It was also found that ATSC-CV-based systems with MPRs of 25% and 50% would be as feasible as converting signalized intersections to underpass interchanges.

Developing a decentralized signal control strategy considering link storage capacity

This paper proposes a double pressure (DP) signal control strategy that takes into account finite link storage capacity. Two types of pressure measures, including an endogenous and an exogenous pressure, are defined. The endogenous pressure is associated with the estimated exit-flow during a signal phase in the next time period, while the exogenous pressure is a virtual pressure associated with the downstream links. The properties of the proposed signal control strategy, including localized waiting time minimization and queue length stabilization at each isolated intersection were discussed. The performance of the proposed signal control strategy was evaluated with two testing networks via simulation, including a network with an isolated signalized intersection and a network with multiple signalized intersections. We compared the performance of the proposed DP control strategy with three existing strategies, including the fixed signal control, adaptive signal control and a back-pressure algorithm based control strategy proposed by previous studies. The test results show promise of the proposed DP control strategy in improving network travel time and queue stability when compared with several state-of-art decentralized control strategies, even though we acknowledge that future efforts in extending the decentralized strategy towards a better system-wide coordination are warranted.

Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment

This study aims to develop an optimal signal control algorithm for signalized intersections using individual vehicle’s trajectory data under the vehicle-to-infrastructure (V2I) communication environment. The optimal signal control algorithm developed in this study consists of three modules, namely, a phase group length computation module, a split distribution module, and a phase sequence assignment module. A set of analyses using a microscopic simulation model, VISSIM, was conducted for evaluating the effectiveness of the V2I-based optimal signal control algorithm proposed in this study. The analysis results show that the performance of the V2I-based optimal signal control algorithm is superior to the actuated as well as the fixed signal control methods in an isolated intersection and a 2X3 signalized intersection network. In addition, this study investigated the minimum market penetration rate of V2I equipped vehicles for which the V2I-based optimal signal control algorithm is applicable.

Performance evaluation of integrated strategy of vehicle route guidance and traffic signal control using traffic simulation

This study evaluated the integrated strategy performance of vehicle route guidance and traffic signal control methods using traffic simulation. Based on the proposed optimal framework, three typical traffic signal control methods, including fixed signal control, actuated signal control, and regional coordinative signal control, were investigated via plugin applications, integrated with vehicle route guidance. The characteristics of vehicle route guidance approaches were captured using different guidance information updating frequencies and different user compliance rates. The average link occupancy was used as a representation of the network traffic states, and the network performance was measured by the total travel time. A total of 12,480 simulation runs were conducted. Based on the regression results, six integrated strategies were selected into a recommended integration strategy set. The transferability test shows that the performance of the integration strategy set is quite consistent.

Tri-level programming model for combined urban traffic signal control and traffic flow guidance

In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm (HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages (MSA), the middle level model is solved by non-dominated sorting genetic algorithm II (NSGA II), and the upper level model is solved by genetic algorithm (GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.

A BUS PRIORITY SIGNAL STRATEGY FOR REGULATING HEADWAYS OF BUSES

Since congestion on roads has deteriorated quality of bus service, attractiveness of bus has been weakened. Bus priority signal is a method to shorten control delay of bus at signalized intersections and to improve its service quality, such as reliability, in-vehicle time and waiting time. It may, however, cause congestion in general traffic. For this reason, this study attempts to develop a signal priority strategy to improve bus service quality while little inducing additional delay in general traffic by restricting target buses for priority. The effectiveness of this strategy is evaluated using microscopic simulation model, PARAMICS. The results show that this selected signal priority strategy reduces bus travel time and improves regularity of bus headway, compared with fixed signal control. Furthermore, it may regulate bus headway more powerfully and induce less delay to general traffic than non- selected signal priority.

Advanced demand signals scheme

This paper proposes the advanced demand signals (ADS) scheme using seamless, real-time road-to-vehicle communications. First, a microscopic traffic flow simulator is constructed. Detailed discussions of various parameters affecting the performance of the ADS scheme are proposed. Based on the findings, its performance is compared with that in the conventional fixed signal control scheme and the usefulness of the ADS scheme is demonstrated. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 89(1): 21–30, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20179