ITS applications for work zones

The use of Intelligent Transportation Systems (ITS) in construction work zones to disseminate traffic information has increased significantly in recent years, mainly with the use of Variable Message Signs (VMS). VMS are used based on the assumption that informed drivers will make better travel decisions, thereby reducing congestion. However, the extent of change in driver behavior is difficult to predict prior to ITS deployment. This difficulty leads to the larger problem of justifying investment in ITS. This article proposes an ITS deployment decision support tool using micro‐simulation. The approach determines the required diversion effectiveness of a work zone ITS deployment using VMS. The methodology was tested using the Glenmore Trail/Elbow Drive/5^th Street interchange project (GE5) in Calgary, Canada. The results indicate that the proposed approach will assist agencies in justifying ITS investment by exhibiting the potential resultant societal benefits.     

Agent-based en-route diversion: Dynamic behavioral responses and network performance represented by Macroscopic Fundamental Diagrams

This paper focuses on modeling agents’ en-route diversion behavior under information provision. The behavior model is estimated based on naïve Bayes rules and re-calibrated using a Bayesian approach. Stated-preference driving simulator data is employed for model estimation. Bluetooth-based field data is employed for re-calibration. Then the behavior model is integrated with a simulation-based dynamic traffic assignment model. A traffic incident scenario along with variable message signs (VMS) is designed and analyzed under the context of a real-world large-scale transportation network to demonstrate the integrated model and the impact of drivers’ dynamic en-route diversion behavior on network performance. Macroscopic Fundamental Diagram (MFD) is employed as a measurement to represent traffic dynamics. This research has quantitatively evaluated the impact of information provision and en-route diversion in a VMS case study. It proposes and demonstrates an original, complete, behaviorally sound, and cost-effective modeling framework for potential analyses and evaluations related to Advanced Traffic Information System (ATIS) and real-time operational applications.     

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.     

Genetic algorithm-based simulation optimization of the ALINEA ramp metering system: a case study in Atlanta

ABSTRACT

This paper presents a case study of the optimal ALINEA ramp metering system model of a corridor of the metro Atlanta freeway. Based on real-world traffic data, this study estimates the origin-destination matrix for the corridor. Using a stochastic simulation-based optimization framework that combines a micro-simulation model and a genetic algorithm-based optimization module, we determine the optimal parameter values of a combined ALINEA ramp metering system with a queue flush system that minimizes total vehicle travel time. We found that the performance of ramp metering with optimized parameters, which is very sensitive possibly because bottlenecks are correlated, outperforms the no control model with its optimized parameters in terms of reducing total travel time.     

Real-time traffic network state estimation and prediction with decision support capabilities: Application to integrated corridor management

This paper presents a real-time traffic network state estimation and prediction system with built-in decision support capabilities for traffic network management. The system provides traffic network managers with the capabilities to estimate the current network conditions, predict congestion dynamics, and generate efficient traffic management schemes for recurrent and non-recurrent congestion situations. The system adopts a closed-loop rolling horizon framework in which network state estimation and prediction modules are integrated with a traffic network manager module to generate efficient proactive traffic management schemes. The traffic network manger adopts a meta-heuristic search mechanism to construct the schemes by integrating a wide variety of control strategies. The system is applied in the context of Integrated Corridor Management (ICM), which is envisioned to provide a system approach for managing congested urban corridors. A simulation-based case study is presented for the US-75 corridor in Dallas, Texas. The results show the ability of the system to improve the overall network performance during hypothetical incident scenarios.     

Estimating potential reductions in externalities from rail-road substitution in Trans-European freight transport corridors

This paper develops a method for analysing and estimating savings in externalities that could be achieved by substituting truck with rail freight services in a given Trans-European freight transport corridor. The externalities affected include energy consumption, emissions of greenhouse gases, noise, congestion, and traffic incidents/accidents. The European Commission transport policy aims to provide an institutional framework for the medium- to long-term sustainable development of the transport sector. An important aspect of this policy is to stimulating the modal shift from truck to rail freight transport in inland Trans-European corridors.     

Optimal mainstream traffic flow control of large-scale motorway networks

The continuously increasing daily traffic congestions on motorway networks around the world call for innovative control measures that would drastically improve the current traffic conditions. Mainstream traffic flow control (MTFC) is proposed as a novel and efficient motorway traffic management tool, and its possible implementation and principal impact on traffic flow efficiency is analysed. Variable speed limits, suitably operated and enforced, is considered as one (out of several possible) way(s) for MTFC realisation, either as a stand-alone measure or in combination with ramp metering. A previously developed, computationally efficient software tool for optimal integrated motorway network traffic control including MTFC is applied to a large-scale motorway ring-road. It is demonstrated via several investigated control scenarios that traffic flow can be substantially improved via MTFC with or without integration with coordinated ramp metering actions.     

Queue length estimation at metered freeway‐to‐freeway connectors

Freeway‐to‐freeway connector metering is a cost‐effective and proven freeway management strategy for relieving recurrent congestion. However, one of the critical challenges in design and operation of freeway‐to‐freeway connector metering is the lack of up‐to‐date queue storage length design guidance. In this study, it was found that ramp queue is dynamically related to the metering rate, on‐ramp demand, and traffic flow arrival pattern. Hence, simply using an average demand cannot provide accurate queue length estimation and is also not suitable for queue storage design where the maximum or a percentile queue length is generally used. A mesoscopic queue length simulation model was developed based on the input–output method for estimating queue lengths under various demand‐to‐capacity ratio scenarios. Simulation results indicate that for under‐saturated situations, the ramp queue may exist temporally due to the random short‐term surge of traffic arrivals, and the exponential function could best capture the relationship between queue length and demand‐to‐capacity ratio. For over‐saturated situations, the ramp queue tends to prolong linearly with the demand‐to‐capacity ratio. Based on the simulation, it was recommended that queue storage length be designed as 4.3% of on‐ramp demand when demand is lower than 1200 vph or 2.3% when demand is between 1200 and 2400 vph. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluation of ramp control algorithms using microscopic traffic simulation

Ramp metering has emerged as an effective freeway control measure to ensure efficient freeway operations. A number of algorithms have been developed in recent years to ensure an effective use of ramp metering. As the performance of ramp metering depends on various factors (e.g. traffic volume, downstream traffic conditions, queue override policy etc), these algorithms should be evaluated under a wide range of traffic conditions to check their applicability and performance and to ensure their successful implementation. In view of the expenses of and confounding effects in field testing, simulation plays an important role in the evaluation of such algorithms. This paper presents an evaluation study of two ramp metering algorithms: ALINEA and FLOW. ALINEA is a local control algorithm and FLOW is an area wide coordinated algorithm. The purpose of the study is to use microscopic simulation to evaluate systematically how the level of traffic demand, queue spillback handling policy and downstream bottleneck conditions affect the performance of the algorithms. It is believed that these variables have complex interactions with ramp metering. MITSIM microscopic traffic simulator is used to perform the empirical study. The study consists of two stages. In the first stage, key input parameters for the algorithms were identified and calibrated. The calibrated parameters were then used for the second stage, where the performance of the algorithms were compared with respect to three traffic variables mentioned above using an orthogonal fraction of experiments. Regression analysis was used to identify the impacts of some of the interactions among experimental factors on the algorithms' performance, which is not otherwise possible with a tabular analysis. These results provide insights which may be helpful for design and calibration of more efficient ramp control algorithms.     

A multi-criteria decision support methodology for implementing truck operation strategies

This study proposes a multi-criteria decision support methodology to enable the prioritization of potential alternative transportation system operations strategies and then demonstrates the effectiveness of the methodology using a case study involving truck operations. The primary feature of this methodology is its ability to help policymakers consider economic, public, and private sector standpoints simultaneously. The economic criterion is cost to the public sector where four criteria related to truck impacts on the transportation system are incorporated. These are traffic congestion, safety hazards, air pollution, and pavement damage. In addition, reliability and productivity are regarded as metrics representing the private sector viewpoint since they can significantly affect profitability. The methodology combines qualitative and quantitative aspects of these standpoints. In order to demonstrate the applicability of this methodology, a corridor with some of the highest truck traffic in the US is selected as a case study and three forms of left lane restrictions for trucks are considered. For qualitative analysis, survey data were collected from two groups classified as public agency and transportation industry professionals who are experts in trucking. In addition, a micro traffic simulation model was used to produce various performance measurements that can describe quantitative impacts. As a result, the methodology provides a rational argument for prioritizing potential alternative truck strategies.     

Pareto-improving ramp metering strategies for reducing congestion in the morning commute

This paper presents an alternative approach to internalize congestion externality during the morning commute. We consider a linear freeway with multiple on-ramps and a downstream bottleneck and commuters accessing the freeway via different on-ramps try to arrive at work on time. Rather than charging congestion tolls as widely suggested by economists, we show that the old-fashioned engineering approach – ramp metering – can be a powerful tool to affect travelers’ departure time choice and thereby alter the congestion externality distribution among travelers. With carefully designed time-dependent metering plans, travelers from different origins can be channelized and will access the freeway bottleneck in different time periods, resulting in less total cost for the system compared to the no-metering case. The metering strategies are Pareto-improving, with travelers from the on-ramp with the highest priority having the smallest individual costs and travelers from the on-ramp with the lowest priority having their costs equal to those in the no-metering scenario. By changing the priority order of the ramps periodically, the benefit of the Pareto-improving metering strategies can be distributed evenly among all travelers. Numerical experiments show that the total user cost can be reduced by up to 40% with the proposed metering strategies. This study offers researchers and policy makers a different angle of looking at congestion externality, and the results provide an overview of the potential long term benefits that dynamic ramp metering strategies can achieve.     

A microscopic simulation model for merging control on a dedicated-lane automated highway system

The automated highway systems (AHS) are not designed as stand-alone transportation facilities. Drivers will by necessity drive from their origins to the AHS entrance, and from the AHS exit to their final destinations. Therefore, the AHS will affect other transportation facilities, and should be integrated with all other facilities in the transportation system. Interfaces create much of the congestion for today’s transportation systems. Likewise, AHS interfaces may cause a similar problem, due to either AHS interactions with conventional systems or internal limitations from AHS merging capabilities. If these problems exist, either the AHS or the conventional road network cannot function properly. Consequently, the system as a whole may break down and the AHS could potentially become a detriment to the overall transportation system.Clearly, not enough is known about the automated merging process to determine what conditions would lead to congestion at interface points. The current macroscopic analysis techniques assume parameters that are not applicable to an AHS, and no detailed AHS merging models have been developed and validated. This paper addresses the interface problem between an AHS, and conventional roadway. Specifically, it presents a microscopic simulation model for one scenario of the automated merging maneuver. The results of the model show that for low flows and conventional highway speeds, an one-lane AHS merging section with a dedicated automated entrance ramp has many similar characteristics as a two-lane conventional freeway with or without fixed-time ramp metering. However, when the conventional freeway starts to “break down” near its capacity, the AHS continues to perform with little delay. The model also validates that the minimum ramp length requirements are a function of the merging vehicle’s speed, the mainline vehicles’ speed, and the acceleration and deceleration rates of the merging vehicle.     

Ramp metering and freeway bottleneck capacity

This study aims to determine whether ramp meters increase the capacity of active freeway bottlenecks. The traffic flow characteristics at 27 active bottlenecks in the Twin Cities have been studied for seven weeks without ramp metering and seven weeks with ramp metering. A methodology for systematically identifying active freeway bottlenecks in a metropolitan area is proposed, which relies on two occupancy threshold values and is compared to an established diagnostic method – transformed cumulative count curves. A series of hypotheses regarding the relationships between ramp metering and the capacity of active bottlenecks are developed and tested against empirical traffic data. It is found that meters increase the bottleneck capacity by postponing and sometimes eliminating bottleneck activations, accommodating higher flows during the pre-queue transition period, and increasing queue discharge flow rates after breakdown. Results also suggest that flow drops after breakdown and the percentage flow drops at various bottlenecks follow a normal distribution. The implications of these findings on the design of efficient ramp control strategies, as well as future research directions, are discussed.     

Hierarchical model predictive control for multi-lane motorways in presence of Vehicle Automation and Communication Systems

A widespread deployment of vehicle automation and communication systems (VACS) is expected in the next years. This may lead to improvements in traffic management efficiency because of the novel possibilities of using VACS both as sensors and as actuators, as well as of a variety of new communications channels (vehicle-to-vehicles, vehicle-to-infrastructure) and related opportunities. To achieve this traffic flow efficiency, appropriate studies, developing potential control strategies to exploit the VACS availability, are essential. This paper describes a hierarchical model predictive control framework that can be used for the coordinated and integrated control of a motorway system, considering that an amount of vehicles are equipped with specific VACS. The concept employs and exploits the synergistic (integrated) action of a number of old and new control measures, including ramp metering, vehicle speed control, and lane changing control at a macroscopic level. The effectiveness and the computational feasibility of the proposed approach are demonstrated via microscopic simulation for a variety of penetration rates of equipped vehicles.     

Integrated fuzzy signal and ramp‐metering at a diamond interchange

We propose a fuzzy logic control for the integrated signal operation of a diamond interchange and its ramp meter, to improve traffic flows on surface streets and motorway. This fuzzy logic diamond interchange (FLDI) comprises of three modules: fuzzy phase timing (FPT) module that controls the green time extension of the current phase, phase logic selection (PLS) module that decides the next phase based on the pre‐defined phase sequence or phase logic and, fuzzy ramp‐metering (FRM) module that determines the cycle time of the ramp meter based on current traffic volumes and conditions of the surface streets and the motorways. The FLDI is implemented in Advanced Interactive Microscopic Simulator for Urban and Non‐Urban Network Version 6 (AIMSUN 6), and compared with the traffic actuated signal control. Simulation results show that the FLDI outperforms the traffic‐actuated models with lower system total travel time, average delay, and improvements in downstream average speed and average delay. Copyright © 2011 John Wiley & Sons, Ltd.     

Development and evaluation of a knowledge-based system for traffic congestion management and control

This paper describes a real-time knowledge-based system (KBS) for decision support to Traffic Operation Center personnel in the selection of integrated traffic control plans after the occurrence of non-recurring congestion, on freeway and arterial networks. The uniqueness of the system, called TCM, lies in its ability to cooperate with the operator, by handling different sources of input data and inferred knowledge, and providing an explanation of its reasoning process. A data fusion algorithm for the analysis of congestion allows to represent and interpret different types of data, with various levels of reliability and uncertainty, to provide a clear assessment of traffic conditions. An efficient algorithm for the selection of control plans determines alternative traffic control responses. These are proposed to an operator, along with an explanation of the reasoning process that led to their development and an estimation of their expected effect on traffic. The validation of the system, which is one of only few examples of validation of a KBS in transportation, demonstrates the validity of the approach. The evaluation results, in a simulated environment demonstrate the ability of TCM to reduce congestion, through the formulation of traffic diversion and control schemes.     

Analysis of the optimal length of road expansion – A case study of the Taipei metropolitan area

This study explores the optimal investment in the length of an expanded section of road to mitigate the congestion on a transportation corridor. It is assumed that one end of the road is in the central business district (CBD) and that the households are uniformly distributed along the road. Each individual makes trips from his/her residence to the CBD. Trip demand is elastic and depends on the cost of the trip (including congestion costs). During the first stage, the government determines the length of the expanded section given the width of that section. In the second stage, road users determine their trip demands by taking into consideration the trip cost function. In the process of solving this problem, the equilibrium traffic volume is first solved using differential equations. The optimal length of the expanded section is then solved by maximizing the social welfare. The analysis is then applied to the case of the Tucheng city – Banciao city – Taipei CBD corridor in the Taipei metropolitan area. The scheme of road expansion without tolling performs closely to the first-best scheme for the case of a high potential demand. This study’s approach can serve as valuable reference for city planners engaged in road planning in a transportation corridor between the CBD and satellite cities in a metropolitan area.     

Network operation reliability in a Manhattan-like urban system with adaptive traffic lights

Traffic breakdown to global gridlock occurring in congested traffic network makes the serious traffic congestion even much worse. This paper has proposed to use Network Operation Reliability (NOR) to quantitatively depict the probabilistic feature of traffic breakdown to global gridlock. The Nagel–Schreckenberg cellular automaton model has been used to simulate the traffic flow in a Manhattan-like urban network. A simple adaptive traffic light strategy has been proposed. It has been shown that if vehicles choose to use geometric shortest path, the adaptive traffic signals are able to remarkably enhance the NOR and sometimes the average velocity and the arrival rate as well. The vehicle distribution has been investigated, which has heuristically explained the enhancement of the NOR. A simple perimeter control strategy has been shown to fail to enhance the NOR. Finally, we show that if the time shortest path information could be provided and updated timely, then the NOR can be remarkably enhanced but the adaptive traffic signals have only trivial effect on NOR.     

Optimisation of dynamic motorway traffic via a parsimonious and decentralised approach

This paper presents an optimisation framework for motorway management via ramp metering and variable speed limit. We start with presenting a centralised global optimal control problem aiming to minimise the total travel delay in a motorway system. Given the centralised global optimal control solutions, we propose a set of decentralised ramp metering and speed control strategies which operate on a novel parsimonious dynamic platform without needing an underlying traffic model. The control strategies are applied to a case on UK M25 motorway. The results show that the proposed set of decentralised control is able to deliver a performance that is close to the global optimal ones with significantly less computational and implementation effort. This study provides new insights to motorway management.     

Convexity and robustness of dynamic traffic assignment and freeway network control

We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), where turning ratios are instead assigned exogenous parameters. It is known that relaxation of the supply and demand constraints in the cell-based formulations of the DTA problem results in a linear program. However, solutions to the relaxed problem can be infeasible with respect to traffic dynamics. Previous work has shown that such solutions can be made feasible by proper choice of ramp metering and variable speed limit control for specific traffic networks. We extend this procedure to arbitrary networks and provide insight into the structure and robustness of the proposed optimal controllers. For a network consisting only of ordinary, merge, and diverge junctions, where the cells have linear demand functions and affine supply functions with identical slopes, and the cost is the total traffic volume, we show, using the Pontryagin maximum principle, that variable speed limits are not needed in order to achieve optimality in the FNC problem, and ramp metering is sufficient. We also prove bounds on perturbation of the controlled system trajectory in terms of perturbations in initial traffic volume and exogenous inflows. These bounds, which leverage monotonicity properties of the controlled trajectory, are shown to be in close agreement with numerical simulation results.