A hierarchical control system for freeway traffic

A hierarchical control system consisting of three control layers is developed for the freeway traffic control problem. A simplified optimization problem for the overall freeway system is solved on-line in an optimization layer. Optimization results are used as reference values for an inferior decentralized direct control layer. Prediction of slowly varying variables like on-ramp demands and origin-destination rates as well as of particular model parameters are provided by a supremal adaption layer. The overall control structure is shown to be robust even in the case of strong unexpected disturbances like incidents.     

Simulation studies of information propagation in a self-organizing distributed traffic information system

This paper investigates the feasibility of a self-organizing, completely distributed traffic information system based upon vehicle-to-vehicle communication technologies. Unlike centralized traffic information systems, the proposed system does not need public infrastructure investment as a prerequisite for implementation. Due to the complexity of the proposed system, simulation is selected as the primary approach in the feasibility studies. A simulation framework is built based on an existing microscopic traffic simulation model for the simulation studies. The critical questions for building the proposed market-driven system are examined both from communication requirements and traffic engineering points of view. Traffic information propagation both in freeway and arterial networks via information exchange among IVC-equipped vehicles is tested within the simulation framework. Results on the probability of successful IVC and traffic information propagation distance obtained from the simulation studies are generated and analyzed under incident-free and incident conditions for various roadway formats and parameter combinations. Comparisons between the speed of the incident information wave and the speed of the corresponding traffic shock wave due to the incident are analyzed for different scenarios as the most crucial aspect of the information propagation as a potential foundation for application in such a decentralized traffic information system.     

Cooperative traffic control of a mixed network with two urban regions and a freeway

Currently most optimization methods for urban transport networks (i) are suited for networks with simplified dynamics that are far from real-sized networks or (ii) apply decentralized control, which is not appropriate for heterogeneously loaded networks or (iii) investigate good-quality solutions through micro-simulation models and scenario analysis, which make the problem intractable in real time. In principle, traffic management decisions for different sub-systems of a transport network (urban, freeway) are controlled by operational rules that are network specific and independent from one traffic authority to another. In this paper, the macroscopic traffic modeling and control of a large-scale mixed transportation network consisting of a freeway and an urban network is tackled. The urban network is partitioned into two regions, each one with a well-defined Macroscopic Fundamental Diagram (MFD), i.e. a unimodal and low-scatter relationship between region density and outflow. The freeway is regarded as one alternative commuting route which has one on-ramp and one off-ramp within each urban region. The urban and freeway flow dynamics are formulated with the tool of MFD and asymmetric cell transmission model, respectively. Perimeter controllers on the border of the urban regions operating to manipulate the perimeter interflow between the two regions, and controllers at the on-ramps for ramp metering are considered to control the flow distribution in the mixed network. The optimal traffic control problem is solved by a Model Predictive Control (MPC) approach in order to minimize total delay in the entire network. Several control policies with different levels of urban-freeway control coordination are introduced and tested to scrutinize the characteristics of the proposed controllers. Numerical results demonstrate how different levels of coordination improve the performance once compared with independent control for freeway and urban network. The approach presented in this paper can be extended to implement efficient real-world control strategies for large-scale mixed traffic networks.     

A stated-preference approach towards assessing a vehicle inspection and maintenance program

A stated-preference approach is used to analyzing responses towards the implementation of a vehicle inspection and maintenance program in Lebanon. A questionnaire-based survey was administered to 160 owners of private autos using a scenario-based approach to look at the choice between centralized and decentralized inspection stations as well as between car repair and payment of an emission fee. Binary-logit models are used to define inspection set-up and repair/fee payment choices. The centralized system with car repair were found to be the more popular options.     

Stochasticity of freeway operational capacity and chance-constrained ramp metering

The notion of capacity is essential to the planning, design, and operations of freeway systems. However, in the practice freeway capacity is commonly referred as a theoretical/design value without consideration of operational characteristics of freeways. This is evident from the Highway Capacity Manual (HCM) 2000 in that no influence from downstream traffic is considered in the definition of freeway capacity. In contrast to this definition, in this paper, we consider the impact of downstream traffic and define freeway operational capacity as the maximum hourly rate at which vehicles can be expected to traverse a point or a uniform section of a roadway under prevailing traffic flow conditions. Therefore freeway operational capacity is not a single value with theoretical notion. Rather, it changes under different traffic flow conditions. Specifically, this concept addresses the capacity loss during congested traffic conditions. We further study the stochasticity of freeway operational capacity by examining loop detector data at three specifically selected detector stations in the Twin Cities’ area. It is found that values of freeway operational capacity under different traffic flow conditions generally fit normal distributions. In recognition of the stochastic nature of freeway capacity, we propose a new chance-constrained ramp metering strategy, in which, constant capacity value is replaced by a probabilistic one that changes dynamically depending on real-time traffic conditions and acceptable probability of risk determined by traffic engineers. We then improve the Minnesota ZONE metering algorithm by applying the stochastic chance constraints and test the improved algorithm through microscopic traffic simulation. The evaluation results demonstrate varying degrees of system improvement depending on the acceptable level of risk defined.     

Will a higher free-flow speed lead us to a less congested freeway?

An approach based on cell transmission model (CTM) is proposed to estimate the impact of variable free-flow speeds (FFS) on the performance of a freeway system. Based on the basic CTM, four typical freeway control strategies consisting of non control, local ramp metering, coordinated ramp metering and global control are first formulated. Then the method of adjusting model parameters to the changed free-flow speeds is presented. Among the adjustments, an experimental function based on Fan and Seibold (2014) is proposed to change the jam density. Several useful measures are defined to estimate and compare the performances of different freeways. The following three main observations are obtained from numerical experiments. (a) With the gradually increasing FFS, the throughput of freeway will increase at the beginning and then change to decrease. (b) With the increasing FFS, the average delay of vehicles will decrease at the beginning and then change to increase. (c) A series of free-flow speeds associate with the best performance of freeway. These observations are theoretically analyzed through investigating the location and capacity of bottleneck. Study shows that in general the actual bottleneck capacity will increase at the beginning and then change to decrease with the continually increasing FFS. In view of the positive correlation between traffic delay and bottleneck capacity, the theoretical analysis confirms the numerical observations. The findings of this study can deepen the understanding of freeway systems and help management agents adopt proper measures to improve the performance of the whole system.     

一种智能无线遥控型恒电位仪

该智能无线遥控型恒电位仪是一种应用于阴极防腐保护的大功率直流电源。通过GSM短消息业务方式实现对恒电位仪主要运行参数和阴极保护电位的远程遥测控制,能够在阴极保护工程管理中实现分散控制、集中管理,具有智能化、系统化、网络化特点,极具推广价值。     

Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

This article presents a study on freeway networks instrumented with coordinated ramp metering and the ability of such control systems to produce arbitrarily complex congestion patterns within the dynamical limits of the traffic system. The developed method is used to evaluate the potential for an adversary with access to control infrastructure to enact high-level attacks on the underlying freeway system. The attacks are executed using a predictive, coordinated ramp metering controller based on finite-horizon optimal control and multi-objective optimization techniques. The efficacy of the control schemes in carrying out the prescribed attacks is determined via simulations of traffic network models based on the cell transmission model with onramps modeled as queue buffers. Freeway attacks with high-level objectives are presented on two illustrative examples: congestion-on-demand, which aims to create precise, user-specified pockets of congestion, and catch-me-if-you-can, which attempts to aid a fleeing vehicle from pursuant vehicles.     

Dynamic control and traffic performance in a freeway corridor: a simulation study

This paper describes simulation studies that were conducted to assess the performance of a freeway corridor control system. The system combines an advanced traffic management system with a motorist information system that provides route guidance to individual drivers. It has a hierarchical structure: The corridor level control acts in a supervisory capacity dynamically allocating traffic among alternative corridor facilities, including freeways, frontage roads, and signalized arterials. The local level control then selects control parameters for the individual facilities based on the predicted usage at the corridor level. A user specified performance function is optimized in the process. Both recurrent and nonrecurrent congestion scenarios were simulated using the SCOT model as a test bed. It is shown that, in most cases, significant benefits in performance can be obtained when the system operates as designed.     

不同主导权结构下的双渠道供应链定价策略及协调机制研究

基于制造商开辟线上直销渠道与线下零售渠道构成双渠道供应链的背景下,结合实际的服务影响因素,对不同主导权结构下双渠道供应链各成员的定价策略和协调机制进行研究。分别构建制造商主导、零售商主导、垂直均衡三种分散决策下的两阶段Stackelberg博弈模型,研究发现相较于集中决策,分散决策下供应链成员在价格、需求、利润上均有所损失。为缓解渠道之间的矛盾与冲突,引入一种双向收益共享契约用于协调供应链。研究表明,在一定的收益共享范围内,双向收益共享契约可以完美协调供应链;对于主导企业而言,主导权越向自身集中,所需共享的收益比例也越小;随着零售商服务水平的增大,制造商的利润不断增大,零售商的利润不断减小,供应链整体利润呈先增后减趋势。     

A hybrid model predictive control for traffic flow stabilization and pollution reduction of freeways

In this work a control system is developed and analyzed for the suppression of moving jamwaves and the reduction of pollutant concentrations near motorways. The system is based on the second-order macroscopic freeway traffic model METANET, joined by an emission dispersion model, introduced in a previous work of the authors. For the control tasks dedicated controllers are designed, both using the nonlinear model predictive control method. The control objectives require a distinction in the utilized control measures, thus different controllers are designed and used in predefined control modes. The first mode of the controller is responsible for keeping pollutant concentrations below prescribed limits under stable conditions. The second mode of the controller is working in case of a shockwave threat, aiming for traffic stabilization. Between the control modes switching is based on an appropriate rule set that satisfies the stability of the controlled system. The hybrid controller structure is realized by a finite automata. A complex case study is presented for the evaluation of the suggested controller.     

Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network

Development of a universal freeway incident detection algorithm is a task that remains unfulfilled despite the promising approaches that have been recently explored. Incident detection researchers are realizing that an operationally successful detection framework needs to fulfill a full set of recognized needs. In this paper we attempt to define one possible set of universality requirements. Among the set of requirements, a freeway incident detection algorithm needs to be operationally accurate and transferable. Guided by the envisioned requirements, we introduce a new algorithm with potential for enhanced performance. The algorithm is a modified form of the Bayesian-based Probabilistic Neural Network (PNN) that utilizes the concept of statistical distance. The paper is divided into three main sections. The first section is a detailed definition of the attributes and capabilities that a potentially universal freeway incident detection framework should possess. The second section discusses the training and testing of the PNN. In the third section, we evaluate the PNN relative to the universality template previously defined. In addition to a large set of simulated incidents, we utilize a fairly large real incident databases from the I-880 freeway in California and the I-35W in Minnesota to comparatively evaluate the performance and transferability of different algorithms, including the PNN. Experimental results indicate that the new PNN-based algorithm is competitive with the Multi Layer Feed Forward (MLF) architecture, which was found in previous studies to yield superior incident detection performance, while being significantly faster to train. In addition, results also point to the possibility of utilizing the real-time learning capability of this new architecture to produce a transferable incident detection algorithm without the need for explicit off-line retraining in the new site. In this respect, and unlike existing algorithms, the PNN has been found to markedly improve in performance with time in service as it retrains itself on captured incident data, verified by the Traffic Management Center (TMC) operator. Moreover, the overall PNN-based framework promises potential enhancements towards the envisioned universality requirements.     

Evaluation of forced flows on freeways with single‐loop detectors

This paper documents the development of a simple method for identifying and/or predicting freeway congestion using single loop detection systems. The proposed algorithm is simple and easy to incorporate into most freeway management systems. The Washington State Department of Transportation's Traffic Systems Management Center (TSMC) sponsored the original study. The investigation also led to a recommendation to replace the original TSMC definition of congestion or forced flow conditions with a more reliable indicator. Although, the TSMC has recently implemented a more advanced prediction system based on fuzzy set theory and neural networks to further identify patterns and rules for ramp metering strategies, the findings presented here continue to be constructive to freeway managers looking for quick and easy analyses that rely solely on single‐loop detection systems. The Seattle Area freeway study section used for the original study was the portion of mainline 1–5 northbound starting at the downtown Seattle Station 108 and ending at the Mountlake Terrace Station 193. Several days' worth of volume and lane‐occupancy data were collected for the afternoon time period from 2:30 p.m. to 6:30 p.m. Time intervals of 20 seconds were chosen for each data collection period. Important products of this research include the following:

• simple, and more reliable criterion for the definition of “bottleneck” or forced flow conditions than that originally used by the TSMC.
• simple, and reliable criterion for predicting impending “bottlenecks” or forced flow conditions.
• A proposed variable for improved selection of the appropriate metering rate. (Further analysis of the use of this variable for determining metering rates is recommended for future studies.

The proposed criteria are simple and easy to incorporate into current freeway management computer systems. Further investigation of freeway performance measurement using volume and occupancy data obtained from single‐loop systems is currently being performed.     

Surrounding traffic complexity analysis for efficient and stable conflict resolution

The constant increase in air traffic demand increases a probability of the separation minima infringements in certain areas as a consequence of increased traffic density. The Annual Safety Report 2016 reports that in recent years the number of infringements, measured per million flight hours, had been increased at a lower rate (Eurocontrol, 2018). However, this level of infringements still generates a continuous pressure on the air traffic control (ATC) system and seeks for more control resources ready to tactically solve potential conflicts, while increasing at the same time the operational costs. Considering present air traffic management (ATM) trade-off criteria: increased airspace capacity and traffic efficiency but reducing the cost while preserving safety, new services must be designed to distribute the separation management ATC task loads among other actors. Based on the Single European Sky Air Traffic Management Research and Next Generation Air Transportation System initiatives, this paper proposes an innovative separation management service to shift the completely centralized tactical ATC interventions to more efficient decentralized tactical operations relying on an advanced surrounding traffic analysis tool, to preserve the safety indicators while considering the operational efficiency. A developed methodology for the proposed service is an application-oriented, trying to respond to characteristics and requirements of the current operational environment. The paper further analysis the traffic complexity taking into consideration the so-called domino effect, i.e. a number of the surrounding aircraft causally involved in the separation management service by the means of identification of the spatiotemporal interdependencies between them and the conflicting aircraft. This complexity is driven by the interdependencies structure and expressed as a time-criticality in quantifying the total number of the system solutions, that varies over time as the aircraft are approaching to each other. The results from two randomly selected ecosystem scenarios, extracted from a simulated traffic, illustrate different avoidance capacities for a given look-ahead time and the system solutions counts, that in discrete moments reach zero value.     

Optimization of mainline traffic via an adaptive co-ordinated ramp-metering control model with dynamic OD estimation

Frequently implemented at freeway accesses to streamline traffic, ramp-metering control strategy is often implemented during rush hours in heavily congested areas. This paper presents a novel ramp-metering control model capable of optimizing mainline traffic by providing metering rates for accesses within the control segments. Based on Payne's continuum traffic stream model, a linear dynamic model with a quadratic objective function is constructed for integrated-responsive ramp-metering control. Incorporating on-line origin–destination (OD) estimation of co-ordinated interchanges into the proposed model increases efficiency of the control. In addition, an iterative algorithm is proposed to obtain the optimal solution. Simulation results demonstrate the robustness of the proposed model and its ability to streamline freeway traffic while avoiding traffic congestion.     

Airline-driven ground delay programs: A benefits assessment

Three decades of research studies in ground delay program (GDP) decision-making, and air traffic flow management in general, have produced several analytical models and decision support tools to design GDPs with minimum delay costs. Most of these models are centralized, i.e., the central authority almost completely decides the GDP design by optimizing certain centralized objectives. In this paper, we assess the benefits of an airline-driven decentralized approach for designing GDPs. The motivation for an airline-driven approach is the ability to incorporate the inherent differences between airlines when prioritizing, and responding to, different GDP designs. Such differences arise from the airlines’ diverse business objectives and operational characteristics. We develop an integrated platform for simulating flight operations during GDPs, an airline recovery module for mimicking the recovery actions of each individual airline under a GDP, and an algorithm for fast solution of the recovery problems to optimality. While some of the individual analytical components of our framework, model and algorithm share certain similarities with those used by previous researchers, to the best of our knowledge, this paper presents the first comprehensive platform for simulating and optimizing airline operations under a GDP and is the most important technological contribution of this paper. Using this framework, we conduct detailed computational experiments based on actual schedule data at three of the busiest airports in the United States. We choose the recently developed Majority Judgment voting and grading method as our airline-driven decentralized approach for GDP design because of the superior theoretical and practical benefits afforded by this approach as shown by multiple recent studies. The results of our evaluation suggest that adopting this airline-driven approach in designing the GDPs consistently and significantly reduces airport-wide delay costs compared to the state-of-the-research centralized approaches. Moreover, the cost reduction benefits of the resultant airline-driven GDP designs are equitably distributed across different airlines.     

公路工程钢筋区域化集中加工发展模式分析

首先分析了公路工程建设模式的发展趋势对钢筋加工的新需求,提出可采用区域化集中加工的公路工程钢筋加工发展模式。结合对典型施工单位的调研,进行了现有公路工程现有钢筋加工厂有效生产时间、有效生产时间内钢筋加工厂的生产能力情况、钢筋加工厂用地指标、钢筋加工厂用电能耗指标、钢筋加工厂其他能耗指标等方面的调研。从调研结果可见,区域化钢筋集中加工存在比各标段自建钢筋加工厂的合理性,在条件适宜的前提下,将各标段自建钢筋加工厂转化为区域化钢筋集中加工厂是合理、可行的。在此基础上,探讨了公路工程区域性钢筋集中加工的主要实施模式以及各模式的特点及优势。     

A new approach to time-of-day control based on a dynamic freeway traffic model

This paper presents a new approach to time-of-day control. While time-of-day control strategies presented up-to-now are only optimal under steady-state conditions, the control algorithm derived in this paper takes into account the evolution of traffic flow according to the time delay between a volume change at a ramp and its subsequent disturbance at a freeway point downstream. The new control strategy is based on the solution of a linear programming optimization problem and makes freeway volume hold the capacity constraints for the total time of control operation. In order to reduce the computational effort a simplified version of the new algorithm is also discussed. Simulation results obtained by use of two different traffic flow models show that control derived through the new algorithm can avoid congestion and ensure operation with peak performance even if a steady-state condition is never attained.     

Patterns and projections of technical development in freeway surveillance and control in the U.S.A.

This paper explores the historical trends in freeway traffic management technology in the U.S., and the most likely projections for the coming two decades. First, existing computer‐supervised freeway surveillance and control techniques are reviewed with particular emphasis on the scientific and technological landmarks which has led to the evolution of these techniques. Next, the major underlying trends which bear on the future of automated freeway surveillance and control are identified. Finally, extrapolative projections are made to determine the most likely future of this technology. The paper concludes with implications for the issues of meeting short‐term transportation needs of urban areas through more efficient use of existing transportation facilities.     

Dynamic traffic assignment of cooperative adaptive cruise control

Advances in connected and automated vehicle technologies have resulted in new vehicle applications, such as cooperative adaptive cruise control (CACC). Microsimulation models have shown significant increases in capacity and stability due to CACC, but most previous work has relied on microsimulation. To study the effects of CACC on larger networks and with user equilibrium route choice, we incorporate CACC into the link transmission model (LTM) for dynamic network loading. First, we derive the flow-density relationship from the MIXIC car-following model of CACC (at 100% CACC market penetration). The flow-density relationship has an unusual shape; part of the congested regime has an infinite congested wave speed. However, we verify that the flow predictions match observations from MIXIC modeled in VISSIM. Then, we use the flow-density relationship from MIXIC in LTM. Although the independence of separate links restricts the maximum congested wave speed, for common freeway link lengths the congested wave speed is sufficiently high to fit the observed flows from MIXIC. Results on a freeway and regional networks (with CACC-exclusive lanes) indicate that CACC could reduce freeway congestion, but naïve deployment of CACC-exclusive lanes could cause an increase in total system travel time.