An application of variance reduction techniques in freeway simulation

Computer simulation models are used in a variety of applications in transportation engineering and have become a prime aid in decision making. The applications range from evaluating traffic control strategies for single intersections to such complex decision processes as evaluating the impact of removing toll facilities at the George Washington Bridge in New York City. While it is widely accepted that simulation offers an unmatchable capability of evaluating alternate control policies, the high variance of the output variable presents a critical problem in such comparative analyses. The simulation models with high output variance must be run longer or replicated many times to achieve a desired precision level, and that corresponds to increased cost of computer resources. This paper describes and illustrates the application of variance reduction concepts that can improve the reliability and efficiency of the simulation experimental process by taking advantage of the simulation model structure. The two variance reduction concepts (common random numbers and antithetic variates) reduce the variance of the output variable by replacing the original sampling procedure with a new procedure that yields the same expected value but with a smaller variance. The application of the variance reduction concept was illustrated using results from experiments with a freeway simulation model. The results indicate that both common random numbers and antithetic variates sampling procedures appreciably reduce the variance of the simulation output measure.     

A computationally efficient simulation model for estimating energy consumption of electric vehicles in the context of route planning applications

The fact that electric vehicles (EVs) are characterized by relatively short driving range not only signifies the importance of routing applications to compute energy efficient or optimal paths, but also underlines the necessity for realistic simulation models to estimate the energy consumption of EVs. To this end, the present paper introduces an accurate yet computationally efficient energy consumption model for EVs, based on generic high-level specifications and technical characteristics. The proposed model employs a dynamic approach to simulate the energy recuperation capability of the EV and takes into account motor overload conditions to represent the vehicle performance over highly demanding route sections. To validate the simulation model developed in this work, its output over nine typical driving cycles is compared to that of the Future Automotive Systems Technology Simulator (FASTSim), which is a simulation tool tested on the basis of real-world data from existing vehicles. The validation results show that the mean absolute error (MAE) of cumulative energy consumption is less than 45 W h on average, while the computation time to perform each driving cycle is of the order of tens of milliseconds, indicating that the developed model strikes a reasonable balance between efficacy of representation and computational efficiency. Comprehensive simulation results are presented in order to exemplify the key features of the model and analyze its output under specific highly aggressive driving cycles for road gradients ranging from −6% to 6%, in support of its usability as a practical solution for estimating the energy consumption in EV routing applications.     

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.     

Gantry crane operations to transfer containers between trains: A simulation study of a Spanish terminal

Freight transfer operations are critical in combined transport networks. In this paper a simulation model and modelling approach to the transfer of cargo between trains at rail terminals is presented. The model is used to study the Port-Bou terminal, the main intermodal terminal at the Spanish-French frontier. Four different gantry crane operation modes to interchange containers between trains are evaluated. These operation rules are tested in several scenarios to examine the critical factors of the system and the best operation rule for each situation. Latest generation software is used to develop the model that incorporates modular programming and enhanced graphic systems for output representation. It allows a dynamic display of the simulated system and, likewise, the possibility of developing modules that can be reused in other studies. The research shows how simulation can be a useful planning tool in the rail transportation context.     

A simulation model for evaluating advanced dial-a-ride paratransit systems

This paper presents a simulation system that has been developed to model a variety of technology-oriented dial-a-ride paratransit systems operated in an urban environment. The latest advances in information technologies such as automatic vehicle location (AVL), digital telecommunication and computers have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. This opportunity has also prompted wide spread interest in quantifying the actual benefits that can be attained from such technological enhancement. The primary objective of the simulation model described in this paper was to facilitate the evaluation of the potential effects that these technologies may bring on a paratransit system. The paper discusses the general concepts, models and computational techniques applied in the simulation system, focusing on how various components are modeled and how they interact with each other in the overall simulation framework. The simulation system is applied to evaluate the potential operational improvement that may be attained from the application of automatic vehicle location technology.     

Development and implementation of the areawide Dynamic ROad traffic NoisE (DRONE) simulator

This paper discusses the areawide Dynamic ROad traffic NoisE (DRONE) simulator, and its implementation as a tool for noise abatement policy evaluation. DRONE involves integrating a road traffic noise estimation model with a traffic simulator to estimate road traffic noise in urban networks. An integrated traffic simulation-noise estimation model provides an interface for direct input of traffic flow properties from simulation model to noise estimation model that in turn estimates the noise on a spatial and temporal scale. The output from DRONE is linked with a geographical information system for visual representation of noise levels in the form of noise contour maps.     

Urban traffic flow prediction using a fuzzy-neural approach

This paper develops a fuzzy-neural model (FNM) to predict the traffic flows in an urban street network, which has long been considered a major element in the responsive urban traffic control systems. The FNM consists of two modules: a gate network (GN) and an expert network (EN). The GN classifies the input data into a number of clusters using a fuzzy approach, and the EN specifies the input–output relationship as in a conventional neural network approach. While the GN groups traffic patterns of similar characteristics into clusters, the EN models the specific relationship within each cluster. An online rolling training procedure is proposed to train the FNM, which enhances its predictive power through adaptive adjustments of the model coefficients in response to the real-time traffic conditions. Both simulation and real observation data are used to demonstrative the effectiveness of the method.     

Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design, achieve solutions for optimal design features before implementation, and help getting the design closer to the system optimal. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents’ respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since car movements are not as flexible as pedestrian movements, velocity angle constraints are included for cars. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs.     

直线电机式悬架电流滞环控制策略研究

本文设计出一种电流滞环控制策略,通过跟踪直线电机式悬架控制系统输出的最优阻尼力转变,得到参考电流,经过空间矢量调制后输出PWM波,输送到电流逆变器中转换为三相电流,进而控制直线电机的作用。经过仿真可以得出电流滞环控制策略控制效果良好,可以输出理想的阻尼力,为电动汽车主动悬架的研究提供基础。     

Robust calibration of macroscopic traffic simulation models using stochastic collocation

The predictions of a well-calibrated traffic simulation model are much more valid if made for various conditions. Variation in traffic can arise due to many factors such as time of day, work zones and weather. Calibration of traffic simulation models for traffic conditions requires larger datasets to capture the stochasticity in traffic conditions. In this study we use datasets spanning large time periods to incorporate variability in traffic flow, speed for various time periods. However, large data poses a challenge in terms of computational effort. With the increase in number of stochastic factors, the numerical methods suffer from the curse of dimensionality. In this study, we propose a novel methodology to address the computational complexity due to the need for the calibration of simulation models under highly stochastic traffic conditions. This methodology is based on sparse grid stochastic collocation, which, treats each stochastic factor as a different dimension and uses a limited number of points where simulation and calibration are performed. A computationally efficient interpolant is constructed to generate the full distribution of the simulated flow output. We use real-world examples to calibrate for different times of day and conditions and show that this methodology is much more efficient that the traditional Monte Carlo-type sampling. We validate the model using a hold out dataset and also show the drawback of using limited data for the calibration of a macroscopic simulation model. We also discuss the drawbacks of the predictive ability of a single calibrated model for all the conditions.     

Modelling dual carriageway lane changing using neural networks

Neural networks offer a potential alternative method of modelling driver behaviour within road traffic systems. This paper explores the application of neural networks to modelling the lane-changing decisions of drivers on dual carriageways. Two approaches are considered. The first, preliminary approach uses a prediction type of neural network with a single hidden layer and the back propagation learning algorithm to model the behaviour of an individual driver. A series of consecutive time-scan traffic patterns, which describe the driver's environment and changes over time as the selected vehicle travels along a link, are input to the neural network, which then predicts the new lane and position of the vehicle. Training data are collected from a human subject using an interactive driving simulation. The trained neural network successfully exhibited the rudiments of driving behaviour in terms of lane and speed changes. A major disadvantage of this approach was the difficulty in recording real-life data, which are required to train the neural network, for individual drivers. The second approach concentrates specifically on lane changing and makes use of a learning vector quantization classification type of neural network. Input to the neural network still consists primarily of time-scan traffic patterns, but the format is changed to facilitate the possibility of data acquisition using image processing. The neural network output classifies the input data by determining the new lane for the vehicle concerned. Performance in both testing and training was very good for data generated by the rule-based driver-decision model of a microscopic simulation. Performance in testing was less satisfactory for data taken directly from a road and highlighted the need for extensive data sets for successful training.     

Alternative methods for estimating full marginal costs of highway transportation

This paper presents various methods of estimating the full marginal cost (FMC) of highway passenger transportation. First, the computation of FMC is performed using the marginal cost functions, most of which were developed by Ozbay et al. [Ozbay, K., Bartin, B., Berechman, J., 2001. Estimation and evaluation of full marginal costs of highway transportation in New Jersey. Journal of Transportation and Statistics 4 (1)]. FMC is defined and calculated as “total cost per trip” as explained in this paper. However, in multiple origin-destination and multiple route highway networks, the practical application of the network-wide FMC concept is complicated. These issues are addressed in detail in this paper. Therefore, in the second method, a multiple route based FMC approach is proposed for a given origin-destination pair in the network. It is observed that the marginal values of different paths vary as much as 28%. Third, a comparison of FMC estimation results of two distinct measurement tools is presented. The FMC estimation is performed between a selected OD pair using the static transportation planning software output (TransCAD). The same analysis is repeated using the stochastic traffic simulation software output (PARAMICS). The differences in FMC values estimated by static transportation planning software and microscopic traffic simulation software are discussed.     

Alterations to the transyt-7F model to represent near-side transit stops

Transit vehicles stopping to load/unload passengers on-line at a signalized intersection can obstruct the flow of other vehicles. The TRANSYT model ignores the delay to other traffic caused by this loading/unloading process. This can cause TRANSYT to use incorrect flow profiles, resulting in signal timings that cater to these profiles rather than the actual ones. This paper describes a new model for representing near-side transit stops in lanes shared by public transit and private vehicles, and its implementation into the TRANSYT-7F program. The results of an initial application of the proposed model are also described. The proposed model, which is a deterministic simulation model, is able to represent the effect of near-side transit stops on the other traffic; this representation covers both total and partial blockage of the approaches during the transit loading. The procedure has been incorporated into the TRANSYT-7F program. This allows appropriate representation of the adverse effects of transit loading on-line during a green phase. It thus encourages the TRANSYT optimizer to push transit loading to the red phases.     

RENAISSANCE – A unified macroscopic model-based approach to real-time freeway network traffic surveillance

The paper presents a unified macroscopic model-based approach to real-time freeway network traffic surveillance as well as a software tool RENAISSANCE that has been recently developed to implement this approach for field applications. RENAISSANCE is designed on the basis of stochastic macroscopic freeway network traffic flow modeling, extended Kalman filtering, and a number of traffic surveillance algorithms. Fed with a limited amount of real-time traffic measurements, RENAISSANCE enables a number of freeway network traffic surveillance tasks, including traffic state estimation and short-term traffic state prediction, travel time estimation and prediction, queue tail/head/length estimation and prediction, and incident alarm. The traffic state estimation and prediction lay the operating foundation of RENAISSANCE since RENAISSANCE bases the other traffic surveillance tasks on its traffic state estimation or prediction results. The paper first introduces the utilized stochastic macroscopic freeway network traffic flow model and a real-time traffic measurement model, upon which the complete dynamic system model of RENAISSANCE is established with special attention to the handling of some important model parameters. The algorithms for the various traffic surveillance tasks addressed are described along with the functional architecture of the tool. A simulation test was conducted via application of RENAISSANCE to a hypothetical freeway network example with a sparse detector configuration, and the testing results are presented in some detail. Final conclusions and future work are outlined.     

Tree-building with complex cost structures — A new algorithm for incorporation into transport demand models

This paper highlights some of the difficulties involved in the implementation of complex cost structures in the tree-building section of a transport demand model. The conventional tree-building algorithm is briefly described and is seen to be inadequate for the present purpose. A new algorithm is then presented which is able to implement complex cost structures properly. An example is given of the application of this algorithm to the building of tree in a public transport network. The performance of a computer program incorporating the new alrogrithm is evaluated against alternative methods of implementing complex cost structures. Some mention is then made of the vast range of potential uses for the new algorithm in the field of transport modelling and simulation.     

Theory of safety surrogates using vehicle trajectories in macroscopic and microscopic settings: Application to dynamic message signs controlled traffic at work zones

This paper presents a new mathematical framework for obtaining quantitative safety measure using macroscopic as well as microscopic traffic data. The safety surrogate obtained from the macroscopic data is in terms of analysis performed on vehicle trajectories obtained from the macroscopic data. This method of obtaining safety measure can be used for many different types of applications. The safety surrogate for the traffic dynamics are developed in terms of a new concept of Negative Speed Differentials (NSD) that involve a convolution of vehicle speed function obtained from vehicle trajectories and then performing the integration of the square of the output for its negative values. The framework is applicable to microscopic traffic dynamics as well where we can use car following models for microscopic dynamics or the LWR model for macroscopic dynamics. This paper then presents the use of this new safety surrogate on the development of a feedback control law for controlling traffic in work zones using Dynamic Message Signs. A hybrid dynamics model is used to represent the switching dynamics due to changing DMS messages. A feedback control design for choosing those messages is presented as well as a simple simulation example to show its application.     

Modelling negative interactions among pedestrians in high density situations

Situations characterised by the presence of a high density of pedestrians involved in negative interactions (e.g. flows in opposite directions) often represent a problematic scenario for simulation models, especially those taking a discrete approach to the representation and management of spatial aspects of the environment. While these situations can be relatively infrequent, and even if architects, event organisers and crowd managers actually try to prevent them as much as possible, they simply cannot be neglected and they actually represent interesting situations to be analysed by means of simulation. The paper presents specific extensions to a floor-field Cellular Automata pedestrian model that are specifically aimed at supporting the simulation of high density situations comprising negative interactions among pedestrians without incurring in the traditional limits of discrete approaches. The models are formally described and experimented in experimental and real world situations.     

Two-class freeway traffic regulation to reduce congestion and emissions via nonlinear optimal control

The objective of this paper is the regulation of freeway traffic by means of optimal control techniques. A first innovative aspect of the proposed approach is the adopted objective function in which, besides the reduction of traffic congestion (which is typically considered in traffic control schemes), the minimization of traffic emissions is also included. Moreover, a multi-class framework is defined in which two classes of vehicles (cars and trucks) are explicitly modelled, and specific control actions for each vehicle class are sought. This results in the formulation of a multi-objective optimal control problem which is described in the paper and for which a specific solution algorithm is developed and used. The algorithm exploits a specific version of the feasible direction algorithm whose effectiveness is demonstrated in the paper by means of simulation results.