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1.
Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells’ states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected. 相似文献
2.
This paper examines CACC truck platooning on uphill grades. It was found that the design of CT policy should consider the effects of low crawl speeds on significant upgrades. Three simple solutions, which have different impacts on traffic flow efficiency, are proposed. Furthermore, truck platoons, controlled by a state-of-the-art CACC model, become asymptotically unstable beyond some critical grade. The errors are permanent, suggesting that trucks fail to re-engage after the upgrade. This occurs by complex interactions between the CACC control and the bounded acceleration capabilities of trucks. New control concepts are developed to complement the existing control model and achieve asymptotic (and string) stability. The instability mechanisms and new control concepts are not specific to the control model used. 相似文献
3.
The Macroscopic Fundamental Diagram (MFD) has been recognized as a powerful framework to develop network-wide control strategies. Recently, the concept has been extended to the three-dimensional MFD, used to investigate traffic dynamics of multi-modal urban cities, where different transport modes compete for, and share the limited road infrastructure. In most cases, the macroscopic traffic variables are estimated using either loop detector data (LDD) or floating car data (FCD). Taking into account that none of these data sources might be available, in this study we propose novel estimation methods for the space-mean speed of cars based on: (i) the automatic vehicle location (AVL) data of public transport where no FCD is available; and (ii) the fused FCD and AVL data sources where both are available, but FCD is not complete. Both methods account for the network configuration layout and the configuration of the public transport system. The first method allows one to derive either uni-modal or bi-modal macroscopic fundamental relationships, even in the extreme cases where no LDD nor FCD exist. The second method does not require a priori knowledge about FCD penetration rates and can significantly improve the estimation accuracy of the macroscopic fundamental relationships. Using empirical data from the city of Zurich, we demonstrate the applicability and validate the accuracy of the proposed methods in real-life traffic scenarios, providing a cross-comparison with the existing estimation methods. Such empirical comparison is, to the best of our knowledge, the first of its kind. The findings show that the proposed AVL-based estimation method can provide a good approximation of the average speed of cars at the network level. On the other hand, by fusing the FCD and AVL data, especially in case of sparse FCD, it is possible to obtain a more representative outcome regarding the performance of multi-modal traffic. 相似文献
4.
This paper describes procedures to develop truck trip generation (TTG) rates for small- and medium-sized urban areas and its implications. Ordinary least squares models are used to develop separate truck production and attraction equations with the number of employees as the independent variable for three industrial groups – retail, transportation and warehousing, and manufacturing. Results from this research indicate that number of employees is a statistically significant predictor, and has significant explanatory power in predicting the number of truck trips produced and attracted. The rates developed in this study are also found to be significantly different from rates developed in other studies with the implication that caution needs to be taken when transferring TTG rates. The rates are applied in a travel demand model as the initial step of incorporating truck traffic into the modeling process. 相似文献
5.
This study addresses the issue of eco-design for transportation in sustainable supply chain management (SSCM). Data envelopment analysis (DEA) is adopted and extended to construct a model for this application. This proposed model, together with the tractable algorithm developed in this research, can provide stakeholders with a Pareto Optimal transportation strategy. This derived transportation strategy can help stakeholders realize certain transportation goals with less resource consumption and pollution emission. The discussion presented leads to a heuristic Joint Transportation Policy and concludes with two useful suggestions for putting the strategy into practice. The proposed model was used in an empirical study of design sustainable transportation mechanism for one air-condition manufacturer in China to transport its products as well, the analysis further demonstrating the theoretical and practical value of this research. 相似文献
6.
Performance analysis has become a vital part of the management practices in the logistics infrastructure. Although there are numerous applications using Data Envelopment Analysis (DEA) models to estimate efficiency in ports and airports, research on railway efficiency remains scarce. Most of the efficiency studies of railways assume that inputs and outputs are known with absolute precision. Here, we compare Stochastic-DEA and Fuzzy-DEA models to assess, respectively, how the underlying randomness and fuzziness impact efficiency levels in railway operations in six different Asian countries: Japan, Thailand, Vietnam, Malaysia, Myanmar, and Indonesia. Findings reveal that conclusions with respect to the ranking of these railways may vary substantially depending upon the type of model chosen, although efficiency scores are similar to some extent when compared within the ambits of Stochastic-DEA and Fuzzy-DEA models. Additionally, modeling choices on fuzziness, rather than randomness, appear to be the most critical source for variations in efficiency rankings. 相似文献
7.
Both the geographic information system (GIS) and transportation modeling environments have seen continually developing analytic concepts and techniques. However, these developments have seldom resulted in the integration of GISs and transportation models. This paper explores the potential inherent in merging of these environments through a systematic investigation of the fundamental basis of integration. To do this, the traditional four step transportation modeling process is extended to include input and output steps. We then define functional components for GIS data handling — data management, manipulation, and analysis. The steps of modeling are matched against the list of GIS data handling functions within a matrix‐based framework. GIS functions that enhance a land‐use based urban transportation modeling process are then categorized. Conclusions are drawn and directions for future developments are discussed. 相似文献
8.
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). 相似文献
9.
Abstract This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses. 相似文献
10.
Understanding people flow at a citywide level is critical for urban planning and commercial development. Thanks to the ubiquity of human location tracking devices, many studies on people mass movement with mobility logs have been conducted. However, high cost and severe privacy policy constraints still complicate utilization of these data in practice. There is no dataset that anyone can freely access, use, modify, and share for any purpose. To tackle this problem, we propose a novel dataset creation approach (called Open PFLOW) that continuously reports the spatiotemporal positions of all individual’s in urban areas based on open data. With fully consideration of the privacy protection, each entity in our dataset does not match the actual movement of any real person, so that the dataset can be totally open to public as part of data infrastructure. Because the result is shown at a disaggregate level, users can freely modify, process, and visualize the dataset for any purpose. We evaluate the accuracy of the dataset by comparing it with commercial datasets and traffic census indicates that it has a high correlation with mesh population and link-based traffic volume. 相似文献
11.
The primary objective of this study was to evaluate the risks of crashes associated with the freeway traffic flow operating at various levels of service (LOS) and to identify crash-prone traffic conditions for each LOS. The results showed that the traffic flow operating at LOS E had the highest crash potential, followed by LOS F and D. The traffic flow operating at LOS B and A had the lowest crash potential. For LOS A and B, the vehicle platoon and abrupt change in vehicle speeds were major contributing factors to crash occurrences. For LOS C, crash risks were correlated with lane-change maneuvers, speed variation, and small headways in traffic. For LOS D, crash risks increased with an increase in the temporal change in traffic flow variables and the frequency of lane-change maneuvers. For LOS E, crash risks were mainly affected by high traffic volumes and oscillating traffic conditions. For LOS F, crash risks increased with an increase in the standard deviation of flow rate and the frequency of lane-change maneuvers. The findings suggested that the mechanism of crashes were quite different across various LOS. A Bayesian random-parameters logistic regression model was developed to identify crash-prone traffic conditions for various LOS. The proposed model significantly improved the prediction performance as compared to the conventional logistic regression model. 相似文献
13.
With the availability of large volumes of real-time traffic flow data along with traffic accident information, there is a renewed interest in the development of models for the real-time prediction of traffic accident risk. One challenge, however, is that the available data are usually complex, noisy, and even misleading. This raises the question of how to select the most important explanatory variables to achieve an acceptable level of accuracy for real-time traffic accident risk prediction. To address this, the present paper proposes a novel Frequent Pattern tree (FP tree) based variable selection method. The method works by first identifying all the frequent patterns in the traffic accident dataset. Next, for each frequent pattern, we introduce a new metric, herein referred to as the Relative Object Purity Ratio (ROPR). The ROPR is then used to calculate the importance score of each explanatory variable which in turn can be used for ranking and selecting the variables that contribute most to explaining the accident patterns. To demonstrate the advantages of the proposed variable selection method, the study develops two traffic accident risk prediction models, based on accident data collected on interstate highway I-64 in Virginia, namely a k-nearest neighbor model and a Bayesian network. Prior to model development, two variable selection methods are utilized: (1) the FP tree based method proposed in this paper; and (2) the random forest method, a widely used variable selection method, which is used as the base case for comparison. The results show that the FP tree based accident risk prediction models perform better than the random forest based models, regardless of the type of prediction models (i.e. k-nearest neighbor or Bayesian network), the settings of their parameters, and the types of datasets used for model training and testing. The best model found is a FP tree based Bayesian network model that can predict 61.11% of accidents while having a false alarm rate of 38.16%. These results compare very favorably with other accident prediction models reported in the literature. 相似文献
14.
Alan J. Horowitz 《运输规划与技术》2013,36(1-2):139-153
Transportation network data structures must be designed to meet the requirements of the analyses being conducted and must be compatible with the selected graphical user interface. Increasing interest in geographic information systems (GIS) and intelligent transportation systems (ITS) have further burdened the network data structure. It is possible to implement object oriented programming (OOP) technology to satisfy these needs, without making the data structure excessively complicated. This paper shows how a well‐developed network data structure can incorporate major capabilities normally associated with stand‐alone GIS's. The design of a network data structure derives from both theoretical and practical considerations. A design of a network data structure, composed entirely of objects, is presented. Examples of its implementation, limitations, advantages, and possible extensions are drawn from experience with the General Network Editor (GNE). 相似文献
15.
多相流管线的内腐蚀直接评价方法 总被引：1，自引：0，他引：1
主要结合墨西哥的一条使用了该评价技术的多相流管线实例,介绍油、气、水混输的多相流管线内腐蚀直接评价（ICDA）技术,重点介绍了多相流管线ICDA的间接检测阶段。采用多相流瞬态模拟软件（0LGA）结合风险分析技术绘制出基于风险分析的内腐蚀敏感度剖面图,从而确定出管线最容易发生腐蚀的高风险临界位置。 相似文献
16.
Various market-based measures have been proposed to reduce CO2 emissions from international shipping. One promising mechanism under consideration is the Emission Trading Scheme (ETS). This study analyzes and benchmarks the economic implications of two alternative ETS mechanisms, namely, an open ETS compared to a Maritime only ETS (METS). The analytical solutions and model calibration results allow us to quantify the impacts of alternative ETS schemes on the container shipping sector and the dry bulk shipping sector. It is found that an ETS, whether open or maritime only, will decrease shipping speed, carrier outputs and fuel consumption for both the container and dry bulk sectors, even in the presence of a “wind-fall” profit to shipping companies. Under an open ETS, the dry bulk sector will suffer from a higher proportional reduction in output than the container sector, and will thus sell more emission permits or purchase fewer permits. Under an METS, container carriers will buy emission permits from the dry bulk side. In addition, under an METS the degree of competition within one sector will have spill-over effects on the other sector. Specifically, when the sector that sells (buys) permits is more collusive (competitive), the equilibrium permit price will rise. This study provides a framework for identifying the moderating effects of market structure and competition between firms on emission reduction schemes, and emphasizes the importance of understanding the differential impacts of ETS schemes on individual sectors within an industry when considering alternative policies. 相似文献
17.
Different models using belief functions are proposed and compared in this article to share and manage imperfect information about events on the road in vehicular networks. In an environment without infrastructure, the goal is to provide to driver the synthesis of the situation on the road from all acquired information. Different strategies are considered: discount or reinforce towards the absence of the event to take into account messages agings, keep the original messages or only the fusion results in vehicles databases, consider the world update, manage the spatiality of traffic jams by taking into account neighborhood. Methods are tested and compared using a Matlab™ simulator. Two strategies are introduced to tackle fog blankets spatiality; they are compared through an example. 相似文献
18.
In this paper we present a route-level patronage model that incorporates transit demand, supply and inter-route effects in a simultaneous system. The model is estimated at the route-segment level by time of day and direction. The results show strong simultaneity among transit demand, supply and competing routes. Transit ridership is affected by the level of service, which in turn is determined by current demand and ridership in the previous year. The model demonstrates that a service improvement has a twofold impact on ridership; it increases ridership on the route with service changes, but it also reduces the ridership on competing routes so that the net ridership change is small. The model is thus useful for both system-level analysis and route-level service planning. 相似文献
19.
Nowadays, new mobility information can be derived from advanced traffic surveillance systems that collect updated traffic measurements, both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities that academics and practitioners have only partially explored so far.The paper looks at some of these opportunities within the Dynamic Demand Estimation problem (DDEP). At first, data heterogeneity, accounting for different sets of data providing a wide spatial coverage, has been investigated for the benefit of off-line demand estimation. In an attempt to mimic the current urban networks monitoring, examples of complex real case applications are being reported where route travel times and route choice probabilities from probe vehicles are exploited together with common link traffic measurements.Subsequently, on-line detection of non-recurrent conditions is being recorded, adopting a sequential approach based on an extension of the Kalman Filter theory called Local Ensemble Transformed Kalman Filter (LETKF).Both the off-line and the on-line investigations adopt a simulation approach capable of capturing the highly nonlinear dependence between the travel demand and the traffic measurements through the use of dynamic traffic assignment models. Consequently, the possibility of using collected traffic information is enhanced, thus overcoming most of the limitations of current DDEP approaches found in the literature. 相似文献
20.
In this paper, we investigate the influence of scalability on the accuracy of different synthetic populations using both fitting and generation-based approaches. Most activity-based models need a base-year synthetic population of agents with various attributes. However, when several attributes need to be synthesized, the accuracy of the synthetic population may decrease due to the mixed effects of scalability and dimensionality. We analyze two population synthesis methods for different levels of scalability, i.e. two to five attributes and different sample sizes – 10%, 25% and 50%. Results reveal that the simulation-based approach is more stable than Iterative Proportional Fitting (IPF) when the number of attributes increases. However, IPF is less sensitive to changes in sample size when compared to the simulation-based approach. We also demonstrate the importance of choosing the appropriate metric to validate the synthetic populations as the trends in terms of RMSE/MAE are different from those of SRMSE. 相似文献