Simulation assessment of incident detection by cellular phone call-in programs

This research study was designed to assess by simulation the efficacy of incident detection by cellular phone call-in programs. The assessment was conducted by varying the proportion of drivers with cellular phones on the highway so as to mirror the cellular industry statistics that show a continued growth of ownership of cellular phones in the United States. An analytical model, which combined simulation and the limited field data available in the literature, was used to determine measures of effectiveness of the cellular phone-based detection system. The results showed that a cellular phone detection system offers fast incident detection times and higher detection rates for both shoulder and lane blocking incidents. For example, in moderate traffic flow (i.e. 1,550 vehicles per hour per lane), 90 percent of incidents blocking two lanes were detected in 1.5 minutes when the proportion of drivers with cellular phones was one out of 10 drivers, even with only 20 percent of them willing to report incidents. When the current proportion of cellular ownership, i.e. 1 out of 3, was used in the simulation, the detection time improved to 0.8 minutes. The simulation analysis of incident detection by cellular phones also showed that there is a direct relationship between the probability of detection and the detection time; that is, the specification of a higher detection rate resulted in slower detection times. This is in sharp contrast with the results of field study of automatic incident detection (AID) systems which demonstrated an inverse relationship between probability of detection and detection time. This revised version was published online in June 2006 with corrections to the Cover Date.     

基于微观仿真模型的立交方案研究

采用微观交通仿真模型进行立交方案运行分析,可得到行程时间、速度、延误、排队长度等定量指标,为从交通运行角度研究立交方案提供了一种方法。文章阐述了采用微观交通仿真模型的立交方案分析流程,并结合南宁市某立交方案仿真分析实例,论证了采用该仿真模型进行立交方案交通运行分析的可行性。     

Including heavy vehicles in a car‐following model: modelling,calibrating and validating

Heavy vehicles influence general traffic in many different ways compared with passenger vehicles, and this may result in different levels of traffic instability. Increases in the number and proportion of heavy vehicles in the traffic stream will therefore result in different traffic flow conditions. This research initially outlines the different car‐following behaviour of drivers in congested heterogeneous traffic conditions indicating the necessity for developing a car‐following model, which includes these differences. A psychophysical car‐following model, similar in form to Weideman's car‐following model, was developed. Due to the complexity of the developed model, the calibration of the model was undertaken using a particle swarm optimisation algorithm with the data recorded under congested traffic conditions. This was then incorporated into a traffic microsimulation model. The results showed that the car‐following perceptual thresholds and thus action points of drivers differ based on their vehicle and the lead vehicle types. The inclusion of the heavy vehicles in the model showed significant impacts on the traffic dynamic and interactions amongst different vehicles. Copyright © 2016 John Wiley & Sons, Ltd.     

Microscopic simulation of pedestrians in accessibility evaluation

Evaluation of accessibility is of increasing importance to the design of the public realm – including both the built and moving environments and particularly the interface between them. This is of particular relevance to people who are living on the ‘margins of accessibility’, for example, elderly or disabled people. This paper discusses the interactions between a person, the environment and the activities they wish to pursue, and proposes a model that incorporates the concept of ‘capabilities’. The paper then describes how the systematization of these concepts could be tested by incorporating them in a microscopic simulation model of pedestrian activity. A worked example is used to demonstrate how the conceptual approach could yield consistent results under these circumstances. The paper concludes that the conceptual model provides a good basis for the evaluation of accessibility and that the microscopic simulation model incorporating these characteristics would be a useful way of testing pedestrian–environment interactions.     

Evaluation of the Transferability of Incident Detection Algorithms Developed for Singapore Expressways

ABSTRACT

Two new detection algorithms, single-station DV (dual-variable) and dual-station CODE (COmbined Detector Evaluation) were developed earlier using 160 incidents collected along Singapore's Central Expressway (CTE). The transferability of these CTE-developed algorithms is assessed, as a case study, using 100 incidents collected from the Tullamarine Freeway and South Eastern Freeway in Melbourne, Australia. The investigation covers the differences in traffic detector systems (loop detectors versus video-based), road geometry and behaviour between drivers in Singapore and Australia. The re-calibrated application of these algorithms to freeways in Melbourne yielded a reasonably good detection performance as well as satisfying the average expected performances of seven traffic management centres surveyed in the USA. The results suggested that the detection logic of the algorithms developed for CTE possessed reasonably good transferability and are also suitable for receiving traffic inputs from video-based detectors as well as from loop detectors.     

A combined use of microscopic traffic simulation and extreme value methods for traffic safety evaluation

This paper proposes a combined usage of microscopic traffic simulation and Extreme Value Theory (EVT) for safety evaluation. Ten urban intersections in Fengxian District in Shanghai were selected in the study and three calibration strategies were applied to develop simulation models for each intersection: a base strategy with fundamental data input, a semi-calibration strategy adjusting driver behavior parameters based on Measures of Effectiveness (MOE), and a full-calibration strategy altering driver behavior parameters by both MOE and Measures of Safety (MOS). SSAM was used to extract simulated conflict data from vehicle trajectory files from VISSIM and video-based data collection was introduced to assist trained observers to collect field conflict data. EVT-based methods were then employed to model both simulated/field conflict data and derive the Estimated Annual Crash Frequency (EACF), used as Surrogate Safety Measures (SSM). PET was used for EVT measurement for three conflict types: crossing, rear-end, and lane change. EACFs based on three simulation calibration strategies were compared with field-based EACF, conventional SSM based on Traffic Conflict Techniques (TCT), and actual crash frequency, in terms of direct correlation, rank correlation, and prediction accuracy. The results showed that, MOS should be considered during simulation model calibration and EACF based on the full-calibration strategy appeared to be a better choice for simulation-based safety evaluation, compared to other candidate safety measures. In general, the combined usage of microscopic traffic simulation and EVT is a promising tool for safety evaluation.     

An evaluation framework for traffic calming measures in residential areas

The paper evaluates the effectiveness of various traffic calming measures from the perspectives of traffic performance and safety, and environmental and public health impacts. The proposed framework was applied to four calming measures – two types of speed humps, speed tables, and chicanes – to demonstrate its usefulness and applicability. A field experiment using probe vehicles equipped with global positioning system devices was conducted to obtain vehicle trajectory data for use in more realistic simulations. In addition, a recently developed vehicle emissions model was used for more accurate evaluation of environmental and public health impacts. The results show that chicane is better than the other types of traffic calming measures considered, except in terms of vehicle emissions.     

Categorization of the lane change decision process on freeways

Traffic operations for new road layouts are often simulated using microscopic traffic simulation packages. These traffic simulation packages usually simulate traffic on freeways by a combination of a car-following model and a lane change model. The car-following models have gained attention of researchers and are well calibrated versus data. The proposed lane change models are often representations of assumed reasonable behavior, not necessarily corresponding to reality. The current simulation packages apply solely one specific type of model for car-following or lane changing for all vehicles during the simulation. This paper investigates the decision process of lane changing maneuvers for a variety of drivers based on a two-stage test-drive. Participants are asked to take a drive on a freeway in the Netherlands in a camera-equipped vehicle. Afterwards, the drivers are asked to comment on their choices related to lane and speed choice, while watching the video. This paper reveals that different drivers have completely different strategies to choose lanes, and the choices to change lane are related to their speed choice. Four distinct strategies are empirically found. These strategies differ not only in parameter values, as is currently being modeled in most simulation packages, but also in their reasoning. Most remarkably, all drivers perceive their strategy as an obvious behavior and expect all other drivers to drive in a similar way. In addition to the interviews of the participants in the test-drive, 11 people who did not take part in the experiment were interviewed and questioned on lane change decisions. Moreover, the findings of this study have been presented to various groups of audience with different backgrounds (about 150 people). Their comments and feedback on the derived driving strategies have added some value to this study. The findings in this paper form a starting point for developing a novel lane change model which considers four different driving strategies among the drivers on freeway. This is a significant contribution in the area of driving behavior modeling, since the existing microscopic simulators consider only one type of lane change models for all drivers during the simulation. This could lead to significant changes in the way lane changes on freeways are modeled.     

Modelling lane changing and merging in microscopic traffic simulation

This paper introduces Simulation of Intelligent TRAnsport Systems (SITRAS), a massive multi-agent simulation system in which driver-vehicle objects are modelled as autonomous agents. The simulation outputs can be used for the evaluation of Intelligent Transport Systems applications such as congestion and incident management, public transport priority and dynamic route guidance. The model concepts and specifications, and the first applications of the model in the area of incident modelling in urban arterial networks were described in previous publications. This paper presents the details of the lane changing and merging algorithms developed for the SITRAS model. These models incorporate procedures for ‘forced’ and ‘co-operative’ lane changing which are essential for lane changing under congested (and incident-affected) traffic conditions. The paper describes the algorithms and presents simulation examples to demonstrate the effects of the implemented models. The results indicate that only the forced and cooperative lane changing models can produce realistic flow-speed relationships during congested conditions.     

Collecting ambient vehicle trajectories from an instrumented probe vehicle: High quality data for microscopic traffic flow studies

This paper presents the methodology and results from a study to extract empirical microscopic vehicular interactions from a probe vehicle instrumented with sensors to monitor the ambient vehicles as it traverses a 28 mi long freeway corridor. The contributions of this paper are two fold: first, the general method and approach to seek a cost-effective balance between automation and manual data reduction that transcends the specific application. Second, the resulting empirical data set is intended to help advance traffic flow theory in general and car following models in particular. Generally the collection of empirical microscopic vehicle interaction data is either too computationally intensive or labor intensive. Historically automatic data extraction does not provide the precision necessary to advance traffic flow theory, while the labor demands of manual data extraction have limited past efforts to small scales. Key to the present study is striking the right balance between automatic and manual processing. Recognizing that any empirical microscopic data for traffic flow theory has to be manually validated anyway, the present study uses a “pretty good” automated processing algorithm followed by detailed manual cleanup using an efficient user interface to rapidly process the data. The study spans roughly two hours of data collected on a freeway during the afternoon peak of a typical weekday that includes recurring congestion. The corresponding data are being made available to the research community to help advance traffic flow theory in general and car following models in particular.     

Fine-tuning ADAS algorithm parameters for optimizing traffic safety and mobility in connected vehicle environment

Under the Connected Vehicle environment where vehicles and road-side infrastructure can communicate wirelessly, the Advanced Driver Assistance Systems (ADAS) can be adopted as an actuator for achieving traffic safety and mobility optimization at highway facilities. In this regard, the traffic management centers need to identify the optimal ADAS algorithm parameter set that leads to the optimization of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. Once the ADAS-equipped drivers implement the optimal parameter set, they become active agents that work cooperatively to prevent traffic conflicts, and suppress the development of traffic oscillations into heavy traffic jams. Measuring systematic effectiveness of this traffic management requires am analytic capability to capture the quantified impact of the ADAS on individual drivers’ behaviors and the aggregated traffic safety and mobility improvement due to such an impact. To this end, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through a multi-objective optimization approach that uses the Genetic Algorithm. The developed methodology is tested at a freeway facility under low, medium and high ADAS market penetration rate scenarios. The case study reveals that fine-tuning the ADAS algorithm parameter can significantly improve the throughput and reduce the traffic delay and conflicts at the study site in the medium and high penetration scenarios. In these scenarios, the ADAS algorithm parameter optimization is necessary. Otherwise the ADAS will intensify the behavior heterogeneity among drivers, resulting in little traffic safety improvement and negative mobility impact. In the high penetration rate scenario, the identified optimal ADAS algorithm parameter set can be used to support different control objectives (e.g., safety improvement has priority vs. mobility improvement has priority).     

Evaluation of a model predictive control framework for motorway traffic involving conventional and automated vehicles

A Model Predictive Control (MPC) strategy for motorway traffic management, which takes into account both conventional control measures and control actions executed by vehicles equipped with Vehicle Automation and Communication Systems (VACS), is presented and evaluated using microscopic traffic simulation. A stretch of the motorway A20, which connects Rotterdam to Gouda in the Netherlands, is taken as a realistic test bed. In order to ensure the reliability of the application results, extensive speed and flow measurements, collected from the field, are used to calibrate the site’s microscopic traffic simulation model. The efficiency of the MPC framework, applied to this real sizable and complex network under realistic traffic conditions, is examined for different traffic conditions and different penetration rates of equipped vehicles. The adequacy of the control application when only VACS equipped vehicles are used as actuators, is also considered, and the related findings underline the significance of conventional control measures during a transition period or in case of increased future demand.     

W-SPSA in practice: Approximation of weight matrices and calibration of traffic simulation models

The development and calibration of complex traffic models demands parsimonious techniques, because such models often involve hundreds of thousands of unknown parameters. The Weighted Simultaneous Perturbation Stochastic Approximation (W-SPSA) algorithm has been proven more efficient than its predecessor SPSA (Spall, 1998), particularly in situations where the correlation structure of the variables is not homogeneous. This is crucial in traffic simulation models where effectively some variables (e.g. readings from certain sensors) are strongly correlated, both in time and space, with some other variables (e.g. certain OD flows). In situations with reasonably sized traffic networks, the difference is relevant considering computational constraints. However, W-SPSA relies on determining a proper weight matrix (W) that represents those correlations, and such a process has been so far an open problem, and only heuristic approaches to obtain it have been considered.This paper presents W-SPSA in a formally comprehensive way, where effectively SPSA becomes an instance of W-SPSA, and explores alternative approaches for determining the matrix W. We demonstrate that, relying on a few simplifications that marginally affect the final solution, we can obtain W matrices that considerably outperform SPSA. We analyse the performance of our proposed algorithm in two applications in motorway networks in Singapore and Portugal, using a dynamic traffic assignment model and a microscopic traffic simulator, respectively.     

给水管网水力模型系统应用分析

文中介绍了国内3个给水管网水力模型工程实例,并由此分析了国内现有的水力模型建立和应用情况。具体举例说明了给水管网水力模型在自来水公司日常工作中运行的情况。总结了水力模型在现代自来水公司的运行和管理中遇到的问题,并提出了相应的解决方案。得出了水力模型给自来水公司的运行和管理在很多方面可以带来益处的结论。     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from whatever data are available. This paper presents a generic data assimilation framework to reconstruct such plausible trajectories on signalized urban arterials using microscopic traffic flow models and data from loops (individual vehicle passages and thus vehicle counts); traffic control data; and (sparse) travel time measurements from whatever source available. The key problem we address is that loops suffer from miss- and over-counts, which result in unbounded errors in vehicle accumulations, rendering trajectory reconstruction highly problematic. Our framework solves this problem in two ways. First, we correct the systematic error in vehicle accumulation by fusing the counts with sparsely available travel times. Second, the proposed framework uses particle filtering and an innovative hierarchical resampling scheme, which effectively integrates over the remaining error distribution, resulting in plausible trajectories. The proposed data assimilation framework is tested and validated using simulated data. Experiments and an extensive sensitivity analysis show that the proposed method is robust to errors both in the model and in the measurements, and provides good estimations for vehicle accumulation and vehicle trajectories with moderate sensor quality. The framework does not impose restrictions on the type of microscopic models used and can be naturally extended to include and estimate additional trajectory attributes such as destination and path, given data are available for assimilation.     

A Modeling Framework for Bus Rapid Transit Operations Evaluation and Service Planning

Abstract

In this paper, we present a dynamic traffic assignment-simulation modeling framework (DYNASMART-P) to support the evaluation and planning of Bus Rapid Transit (BRT) services in urban transportation networks. The model represents the different characteristics associated with BRT operations such as: exclusive right-of-way lanes, limited-stop service, signal prioritization at congested intersections, and enhanced bus stops to reduce passenger boarding times. A set of simulation experiments is conducted using the model to study the impact of introducing a hypothetical BRT service in the Knoxville area in the State of Tennessee. In these experiments, the different operational characteristics of BRT are evaluated in terms of potential impact on transit ridership and on the interacting auto traffic. The results illustrate the advantages of BRT for increasing transit ridership and improving overall system performance.     

Network-wide impacts of eco-routing strategies: A large-scale case study

This paper quantifies the system-wide impacts of implementing a dynamic eco-routing system, considering various levels of market penetration and levels of congestion in downtown Cleveland and Columbus, Ohio, USA. The study concludes that eco-routing systems can reduce network-wide fuel consumption and emission levels in most cases; the fuel savings over the networks range between 3.3% and 9.3% when compared to typical travel time minimization routing strategies. We demonstrate that the fuel savings achieved through eco-routing systems are sensitive to the network configuration and level of market penetration of the eco-routing system. The results also demonstrate that an eco-routing system typically reduces vehicle travel distance but not necessarily travel time. We also demonstrate that the configuration of the transportation network is a significant factor in defining the benefits of eco-routing systems. Specifically, eco-routing systems appear to produce larger fuel savings on grid networks compared to freeway corridor networks. The study also demonstrates that different vehicle types produce similar trends with regard to eco-routing strategies. Finally, the system-wide benefits of eco-routing generally increase with an increase in the level of the market penetration of the system.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.