Calibration of large-scale transport planning models: a structured approach
TL;DR: A structured approach for determining optimal calibrated transport model parameters is suggested, which involves joint estimation and calibration of demand and network models, with a major focus on avoiding any manipulation of the OD matrix.
Abstract: Traditionally, transport planning model systems are estimated and calibrated in an unstructured way, which does not allow for interactions among included parameters to be considered. Furthermore, the computational burden of model systems plays a key role in choosing a calibration approach, and usually forces modellers to calibrate demand-side and network models separately. Also, trial-and-error methods and expert opinion are currently the backbones of transport model calibration, which leaves room for error in the calibrated parameters. This paper addresses these challenges and suggests a structured approach for determining optimal calibrated transport model parameters. This approach involves joint estimation and calibration of demand and network models, with a major focus on avoiding any manipulation of the OD matrix. The approach can be applied to static or dynamic traffic assignments. The approach is applied by calibrating GTAModel—an example of a large-scale agent-based model system from Toronto, Canada.
Citations
More filters
TL;DR: An agent-based simulation model is introduced to analyse the effects of different parking policies in a realistic dynamic framework and a novel behavioural pricing formulation is integrated into the simulation model, which dynamically seeks to maximise the total utility of all agents in the system with consideration of their travel behaviours.
Abstract: Car parking policies often aim to relieve or better distribute parking demand in central urban areas. Evaluating their effectiveness requires the investigation of traveller behaviour and responses to parking attributes such as availability, cost, walking distance, and time restriction. Parking policies, which are usually cost-intensive to implement, are crucial in solving parking problems and transportation system problems in general. To investigate parking policy properly, developing agent-based parking systems is beneficial. Motivated by a recent parking management system designed for Kingsford, Sydney, this paper introduces an agent-based simulation model to analyse the effects of different parking policies in a realistic dynamic framework. Furthermore, a novel behavioural pricing formulation is integrated into the simulation model, which dynamically seeks to maximise the total utility of all agents in the system with consideration of their travel behaviours. The model is implemented for the Kingsford town centre, to investigate the effects of different parking policies and demand scenarios on parking utilisation and system performance.
17 citations
TL;DR: This study focuses on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics and proposes a stochastic gradient-based solution procedure that outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence.
Abstract: This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Finally, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.
13 citations
02 Nov 2020
TL;DR: In this paper, the authors proposed a set of effective policies and knowing when to use them to manage traffic congestion in urban areas, which can help to ease transport congestion within a crowded urban environment.
Abstract: Easing transport congestion within a crowded urban environment requires management of travel demand. Managing traffic congestion in urban areas requires a set of effective policies and knowing when...
12 citations
TL;DR: This study refines a tolerance-based column generation (TBCG) algorithm for solving BR-DATA problems in multi-state supernetworks without ATP enumeration and proves that the TBCG algorithm is capable of finding solutions that satisfy the BR- DATA user equilibrium conditions.
Abstract: Boundedly rational dynamic activity-travel assignment (BR-DATA) endogenously integrates activity-travel scheduling and dynamic traffic assignment to determine the interaction between land use transport supplies and activity-travel demands of boundedly rational travelers. The combinatorial explosion of activity-travel patterns (ATPs) involving multi-dimensional choice facets poses severe challenges to the model applicability in large networks. This study refines a tolerance-based column generation (TBCG) algorithm for solving BR-DATA problems in multi-state supernetworks without ATP enumeration. The refined TBCG algorithm employs spatial-temporal exploration to allocate activity-travel flows only to potential ATPs in the intermediate assignment process. The spatial-temporal exploitation intensifies ATP generation and network loading, which results in fewer iterations and ultimately substantial speedups compared with the original column generation algorithm. We prove that the TBCG algorithm is capable of finding solutions that satisfy the BR-DATA user equilibrium conditions. A series of numerical examples demonstrate that the TBCG algorithm has a speedup factor larger than two whilst producing approximately the same BR-DATA solutions as the original column generation algorithm.
10 citations
TL;DR: A novel multi-visit vehicle routing problem is proposed which does not enumerate the node and link visits and a set of splitting ratios are introduced to calibrate the model based on the major travel attributes of the travel survey data.
Abstract: In this paper, a novel transport planning model system (TPMS) is formulated built on the concepts of network, multi-modality, integrity and instant calibration. In the proposed formulation, activity-travel pattern (ATP) choice elements including the choices of activity, activity sequence, mode, departure time, and parking location, are all unified into a time-dependent ATPs generator. The proposed model accounts for the dynamicity of the network, including time-of-day and congestion effects in a joint structure for transport supply and demand. Moreover, the proposed TPMS explicitly formulates an operating capacitated public transport system. To allow visiting locations multiple times and to alleviate the complexity of the proposed model, a novel multi-visit vehicle routing problem is proposed which does not enumerate the node and link visits. In order to calibrate the model based on the major travel attributes of the travel survey data, a set of splitting ratios are introduced to distribute trips on the network. The model uses the splitting ratios to integrate the ATPs generator and the traffic assignment (TA) model in a unified TPMS structure. The effectiveness of the proposed structure is demonstrated through numerical examples provided.
6 citations
References
More filters
Book•
29 Aug 1995TL;DR: Using a practical approach, this book discusses two-level factorial and fractional factorial designs, several aspects of empirical modeling with regression techniques, focusing on response surface methodology, mixture experiments and robust design techniques.
Abstract: From the Publisher:
Using a practical approach, it discusses two-level factorial and fractional factorial designs, several aspects of empirical modeling with regression techniques, focusing on response surface methodology, mixture experiments and robust design techniques. Features numerous authentic application examples and problems. Illustrates how computers can be a useful aid in problem solving. Includes a disk containing computer programs for a response surface methodology simulation exercise and concerning mixtures.
10,104 citations
Book•
01 Jan 2003TL;DR: In this paper, the authors describe the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation, and compare simulation-assisted estimation procedures, including maximum simulated likelihood, method of simulated moments, and methods of simulated scores.
Abstract: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
7,768 citations
Book•
26 Sep 2011
TL;DR: This paper is concerned with the development of methods for dealing with the role of symbols in the interpretation of semantics.
Abstract: Preface. Acknowledgements. Notation and Symbols. Part I: Terminology and Theory. 1. Introduction. 2. Concepts. 3. Theoretical Background. Part II: Methods. 1. Introduction. 2. No-Preference Methods. 3. A Posteriori Methods. 4. A Priori Methods. 5. Interactive Methods. Part III: Related Issues. 1. Comparing Methods. 2. Software. 3. Graphical Illustration. 4. Future Directions. 5. Epilogue. References. Index.
4,976 citations
TL;DR: In this article, the authors present a set of conditions that will result in a product with a desirable combination of properties, which is a problem facing the product development community in general.
Abstract: A problem facing the product development community is the selection of a set of conditions which will result in a product with a desirable combination of properties. This essentially is a problem i...
4,109 citations
TL;DR: In this paper, a class of incomplete three level factorial designs useful for estimating the coefficients in a second degree graduating polynomial are described and the designs either meet, or approximately meet, the criterion of rotatability and for the most part can be orthogonally blocked.
Abstract: A class of incomplete three level factorial designs useful for estimating the coefficients in a second degree graduating polynomial are described. The designs either meet, or approximately meet, the criterion of rotatability and for the most part can be orthogonally blocked. A fully worked example is included.
3,194 citations