A Review of Traffic Signal Control.

The aim of this paper is to provide a starting point for the future research within the SERC sponsored project "Gating and Traffic Control: The Application of State Space Control Theory". It will provide an introduction to State Space Control Theory, State Space applications in transportation in general, an in-depth review of congestion control (specifically traffic signal control in congested situations), a review of theoretical works, a review of existing systems and will conclude with recommendations for the research to be undertaken within this project

Evaluation of Coordinated Ramp Metering (CRM) Implemented By Caltrans

Coordinated ramp metering (CRM) is a critical component of smart freeway corridors that rely on real-time traffic data from ramps and freeway mainline to improve decision-making by the motorists and Traffic Management Center (TMC) personnel. CRM uses an algorithm that considers real-time traffic volumes on freeway mainline and ramps and then adjusts the metering rates on the ramps accordingly for optimal flow along the entire corridor. Improving capacity through smart corridors is less costly and easier to deploy than freeway widening due to high costs associated with right-of-way acquisition and construction. Nevertheless, conversion to smart corridors still represents a sizable investment for public agencies. However, in the U.S. there have been limited evaluations of smart corridors in general, and CRM in particular, based on real operational data. This project examined the recent Smart Corridor implementation on Interstate 80 (I-80) in the Bay Area and State Route 99 (SR-99, SR99) in Sacramento based on travel time reliability measures, efficiency measures, and before-and-after safety evaluation using the Empirical Bayes (EB) approach. As such, this evaluation represents the most complete before-and-after evaluation of such systems. The reliability measures include buffer index, planning time, and measures from the literature that account for both the skew and width of the travel time distribution. For efficiency, the study estimates the ratio of vehicle miles traveled vs. vehicle hour traveled. The research contextualizes before-and-after comparisons for efficiency and reliability measures through similar measures from another corridor (i.e., the control corridor of I-280 in District 4 and I-5 in District 3) from the same region, which did not have CRM implemented. The results show there has been an improvement in freeway operation based on efficiency data. Post-CRM implementation, travel time reliability measures do not show a similar improvement. The report also provides a counterfactual estimate of expected crashes in the post-implementation period, which can be compared with the actual number of crashes in the “after” period to evaluate effectiveness

Ramp metering review

3200037E, Finnra Report

Application of ALINEA ramp control algorithm to freeway traffic flow on approaches to Bosphorus strait crossing bridges

AbstractBeginning from the 1960ies sustainability has been being pointed out as an important criterion in development which made many countries plan sustainability originated progressing policies. The decision makers, planning to construct a third roadway bridge to connect Asia and Europe continents on to the Bosphorus in Istanbul metropolitan area, first have to evaluate the exaggerated road traffic congestion phenomenon. Before making such a non-environmentally friend decision, advanced traffic managing strategies have to be incorporated to regularize the current pattern of traffic flows on the existing road network that prevails the road based urban transport.Ramp control is an efficient strategy that has been employed to prevent recurrent traffic congestion since 1970ies. With the employment of ramp control applications, several benefits of ramp management, including i.e., the increase on the level of traffic safety, the increase on travelling speeds and consequently decrease on travelling times, the increase on the level-of-service, increase on energy consumption efficiency, decrease on environmental impacts, and increase on user satisfaction, have been experienced. The present paper aims to impose advanced traffic management schemes, specifically the ramp control, on the non-efficient utilisation of freeway approaches to existing Bosphorus bridges as an alternative to a third bridge crossing

A self-learning motorway traffic control system for ramp metering

Self-learning systems have attracted increasing attention in the ramp metering domain in recent years. These systems are based on reinforcement learning (RL) and can learn to control motorway traffic adaptively. However, RL-based ramp metering systems are still in their early stages and have shown limitations regarding their design and evaluation. This research aims to develop a new RL-based system (known as RAS) for ramp metering to overcome these limitations. A general framework for designing a RL-based system is proposed in this research. It contains the definition of three RL elements in a ramp metering scenario and a system structure which brings together all modules to accomplish the reinforcement learning process. Under this framework, two control algorithms for both single- and multi-objective problems are developed. In addition, to evaluate the proposed system, a software platform combining the new system and a traffic flow model is developed in the research. Based on the platform developed, a systematic evaluation is carried out through a series of simulation-based experiments. By comparing with a widely used control strategy, ALINEA, the proposed system, RAS, has shown its effectiveness in learning the optimal control actions for different control objectives in both hypothetical and real motorway networks. It is found that RAS outperforms ALINEA on improving traffic efficiency in the situation with severe congestion and on maintaining user equity when multiple on-ramps are included in the motorway network. Moreover, this research has been extended to use indirect learning technology to deal with incident-induced congestion. Tests for this extension to the work are carried out based on the platform developed and a commercial software package, AIMSUN, which have shown the potential of the extended system in tackling incident-induced congestion

Early Empirical Evidence for the Effects of Adaptive Ramp Metering on Measures of Travel Time Reliability

Adaptive ramp metering (ARM) is a critical component of smart freeway corridors under an active traffic management portfolio. While improving capacity through smart corridors and application of proactive traffic management solutions is less costly and easier to deploy than freeway widening, conversion to smart corridors still represents a sizable investment for a state department of transportation. Early evidence of improvements following these projects can be valuable to agencies. However, in the U.S. there have been limited evaluations, of smart corridors in general and ARM in particular, based on real operational data. This thesis explores travel time reliability measures for the eastbound (EB) Interstate 80 (I-80) corridor in the San Francisco Bay Area before and after implementation of ARM using INRIX data. These measures include buffer index, planning time, and measures from the literature that account for both skew and width of the travel time distribution. The measures are estimated for the entire corridor as well as corridor segments upstream of a bottleneck that historically have the worst measures of reliability. A new metric for measuring unreliability that may be derived from readily available INRIX data is also proposed in the thesis using data from the study corridor. While the ARM system is relatively new, the results indicate positive trends in measures of reliability even as the number of incidents on the corridor has increased in line with the national crash trends. The spatio-temporal trend evaluation framework used here may be used in the future to obtain more robust conclusions. However, since multiple smart corridor components were installed simultaneously, it may not be possible to fully isolate the effects of the ARM, or any of the other systems, individually

Dynamic multi-ramp metering control with simultaneous perturbation stochastic approximation (SPSA)

Ramp metering was proven to be a viable form of freeway traffic control strategy, which could eliminate, or at least reduce, freeway congestion. In this study, the development of ramp metering control strategies, models, and constraints (e.g., meter locations, ramp storage capacities, lower and upper bounds of ramp metering rates) are discussed in detail. The pre-timed and demand/capacity metering control strategies were first evaluated, while the potential metered ramps were determined. A Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is proposed to dynamically optimize multiple-ramp metering control by maximizing the total throughput subject to a number of constraints. The ramp metering rates subject to dynamic traffic conditions and capacity constraints are considered as decision variables in the SPSA algorithm. Based on the collected geometric and traffic data, a CORSIM model was developed to simulate traffic operation for the study site. The potential benefit of the dynamic multi-ramp metering control model under time varying traffic condition was simulated and evaluated. The increased total throughput and reduced total delay were observed, while the traffic conditions suitable for implementing ramp metering control were suggested. The developed dynamic multi-ramp metering control with SPSA algorithm has demonstrated its effectiveness to improve freeway operation

A Microscopic Simulation Approach for Developing Ramp Metering Activation Guidelines For Weekends

Traffic congestion is one of the major concerns in urban motorways. Agencies are implementing various Transportation Systems Management and Operations (TSM&O) strategies to reduce traffic congestion on roadway networks. Ramp metering is a TSM&O strategy that utilizes signals installed at freeways’ on-ramps to dynamically manage traffic entering the freeway. RMSs have been effective at alleviating recurring congestion. Recurring congestion, however, constitutes less than half of all congestion. More than half of all congestion is due to non-recurring events such as incidents, work zones, adverse weather conditions, special events, etc., that adversely affect the performance of a highway. Non-recurring congestion on freeways, especially during the weekend, could be alleviated by activating RMSs based on prevailing traffic conditions along the freeway corridor. This study focused on establishing a set of guidelines for activating RMSs during weekend non-recurring congestion. A microscopic simulation model was used to establish the guideline considering non-recurring congestion due to traffic incidents. It also took account of several incident attributes, including incident location, clearance duration, and the number of lanes blocked. Sensitivity analysis and statistical tests were performed to develop the guidelines. The results showed that, for a two-lane blockage incident, activation of RMSs upstream of the incident location was necessary when ramp volume was above 800 vphpl and freeway mainline volume was above 950 vphpl, whereas for a three-lane blockage incident, activation was needed when ramp volume was higher than 750 vphpl and freeway mainline volume exceeded 850 vphpl. For both incident scenarios, RMSs needed to be activated when speeds were less than 50 mph. Furthermore, activation of RMSs on the weekend improved the average speed of the study roadway network by at least 7 % and reduced the delay by at least 15%

Analysis of the Effects of Adaptive Ramp Metering on Measures of Efficiency with a Proposed Framework for Safety Evaluation

Adaptive ramp metering (ARM) is a widely popular intelligent transportation system (ITS) tool that boasts the ability to reduce congestion and streamline traffic flow during peak hour periods while maintaining a lower implementation cost than traditional methods such as freeway widening. This thesis explores the effectiveness of ARM implementation on an 18 mile segment of the Interstate 80 (I-80) corridor in the Bay Area residing in northern California. Smaller segments of this particular segment were analyzed to determine the effective length of ARM on efficiency at various lengths originating from a known bottleneck location. Efficiency values were also compared against a control segment of the Interstate 280 (I-280) in San Jose to provide a test site experiencing similar traffic congestion but without any ARM implementation. An Empirical Bayes analysis was conducted to provide the foundation of a safety evaluation of the ramp metering implementation and determine a counterfactual estimate of expected collisions had ARM implementation not occurred. It was found that the installation of the ramp meters did allow for some marginal increases in efficiency but may not be entirely associated with ARM implementation due to a variety of external factors as well as showing inconsistent behavior between analyzed segments. Regarding safety, the predictive model estimates 32.8 collisions to occur along a 0.5 mile segment within a three-year timeframe if ARM were not installed, which implies substantial improvements in safety conditions. However additional efficiency and safety data within the “after” period may be necessary to provide a more robust and conclusive evaluation as the ARM system is still relatively new