Short-term speed predictions exploiting big data on large urban road networks

Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the road network and provide great opportunities for enhanced short-term traffic predictions based on real-time information on the whole network. Two network-based machine learning models, a Bayesian network and a neural network, are formulated with a double star framework that reflects time and space correlation among traffic variables and because of its modular structure is suitable for an automatic implementation on large road networks. Among different mono-dimensional time-series models, a seasonal autoregressive moving average model (SARMA) is selected for comparison. The time-series model is also used in a hybrid modeling framework to provide the Bayesian network with an a priori estimation of the predicted speed, which is then corrected exploiting the information collected on other links. A large floating car data set on a sub-area of the road network of Rome is used for validation. To account for the variable accuracy of the speed estimated from floating car data, a new error indicator is introduced that relates accuracy of prediction to accuracy of measure. Validation results highlighted that the spatial architecture of the Bayesian network is advantageous in standard conditions, where a priori knowledge is more significant, while mono-dimensional time series revealed to be more valuable in the few cases of non-recurrent congestion conditions observed in the data set. The results obtained suggested introducing a supervisor framework that selects the most suitable prediction depending on the detected traffic regimes.     

A multiple discrete-continuous model for independent- and joint-discretionary-activity participation decisions

This paper presents a multiple discrete-continuous econometric structure to model the daily time-investment decisions of couples in solo- and joint-discretionary activities incorporating intra-personal and inter-personal inter-dependencies. The empirical model was estimated using data from the 2000 Bay Area Travel Survey. The results indicate evidence of the positive impact of vehicle availability on independent activity participation and the negative impacts of the presence of children and mandatory time investments on the joint discretionary-activity engagement of the spouses. In addition, we also find the mandatory- and maintenance-activity-participation characteristics of the spouse to influence the discretionary activity choices of individuals. Finally, the analysis also indicates a strong impact of common unobserved factors on the decisions of couples. From a policy analysis perspective, these results imply that demand-management actions directly impacting one adult could also result in changes to the activity patterns of his/her spouse and to changes in joint activity participation characteristics. Dr. Sivaramakrishnan Srinivasan is an Assistant Professor in the Department of Civil and Coastal Engineering at the University of Florida. His research interests include travel-behavior analysis, activity-based travel-demand modeling, and the application of advanced econometric methods for transportation problems. Dr. Chandra R. Bhat has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE).     

Factors influencing support for local transportation sales tax measures

Sales tax measures passed at the local level and dedicated to transportation projects have become increasingly popular in the United States. While revenues from fuel taxes stagnate, growth of local transportation sales taxes (LTSTs), most approved in local elections, has led to a gradual shift of the financial base for transportation projects away from user fees and toward broader-based taxes. In this study, the relationship between voter support and the social, political, and geographic characteristics of the voters is explored. Using precinct-level voting data and census demographic data for three local transportation sales tax elections in Sonoma County, in the San Francisco Metropolitan area of California, regression models were constructed to analyze this relationship. In addition, the relationship between the outcomes of the three measures was explored to better understand which transportation projects might have garnered more support for the successful measure. It was found that the closer voters lived to the transportation projects to be funded, the greater their support. Higher incomes were also positively related to support, controlling for other variables. Political leanings were found to affect support, with the direction of the effect dependent upon the project list in each measure’s expenditure plan. Finally, it appears that the latest measure, which passed successfully, benefited greatly from its multi-modal expenditure plan.     

Role of Bus‐Based Park and Ride in the UK: A Temporal and Evaluative Review

Abstract

The number of bus‐based Park and Ride (P&R) schemes in the UK has grown substantially over the past 40 years as a result of its encouragement by the Government as a tool to deal with increasing traffic congestion and traffic‐related pollution. The aim of this article is to analyse the degree to which P&R is effective in the contemporary policy context. The authors identify phases of development of P&R since its emergence as a local solution to transport capacity constraints in historic towns. Policy goals are identified against which a review of literature is used to highlight its effectiveness. It is concluded that P&R may increase the distance travelled by its users due to low load factors on dedicated buses, public transport abstraction and trip generation, although it is highlighted that there are areas in which further research is required to clarify its impacts.     

A Bayesian Methodology for Estimating the Impacts of Improved Coastal Ocean Information on the Marine Recreational Fishing Industry

The study develops a model of recreational fish catch probabilities, based on angler fishing strategies, that is conditional on uncertain information about the coastal ocean environment. We calculate expected catch based on a hypothetical Baseline Data Set and hypothetical data from an Integrated Ocean Observation System (IOOS) to demonstrate potential benefits from IOOS. The role of Bayesian probabilities in Random Utility Models of recreational fishing is identified. The study discusses the types of information that will be required by recreational anglers in the Gulf of Mexico. Results have implications for the construction of ocean observation systems for recreational fishermen.     

南宁市交通管理和控制系统优化方案分析工具的建立

交通仿真是采用计算机数字模型来反映复杂的交通现象,对交通运动随时间和空间的变化进行跟踪描述和分析。不同精度的交通仿真模型有不同的优缺点,要客观的评估城市的交通管理和控制系统优化措施,应将不同精度的模型配合,作为分析工具。本次研究采用中宏观的SATURN作为主导模型,对南宁市的宏观的交通进行整体分析,以及对不同交通改善方案进行评估。选用TSIS、SYNCHRO交通仿真软件作为辅助的交通分析工具,对局部地区的交通及信号配时作较为具体的分析,以利于本研究针对各种建议方案进行客观性的整合分析与应用。     

交通基础设施建设投资对国民经济拉动作用的定量分析

运用投入产出模型定量分析了公路交通基础设施建设投资对国民经济的拉动作用。拉动作用主要表现为公路建设投资所产生的直接、间接和诱导经济效益,其总和为公路建设投资的乘数效应,可分别用产出乘数、GDP乘数和就业乘数来测算。分析测算了我国近年来公路建设投资对国民经济的拉动作用。估算结果表明,(1)公路建筑业对其他部门的波及影响程度大于各部门的平均影响水平;(2)拉动作用在1998年最为显著,自1999年开始,公路投资拉动经济增长的百分比呈逐年上升的趋势。     

Analysing Demand for Suburban Trips: A Mixed RP/SP Model with Latent Variables and Interaction Effects

We analyse mode choice behaviour for suburban trips in the Grand Canary island using mixed revealed preference (RP)/stated preference (SP) information. The SP choice experiment allowed for interactions among the main policy variables: travel cost, travel time and frequency, and also to test the influence of latent variables such as comfort. It also led to discuss additional requirements on the size and sign of the estimated model parameters, to assess model quality when interactions are present. The RP survey produced data on actual trip behaviour and was used to adapt the SP choice experiment. During the specification searches we detected the presence of income effect and were able to derive willingness-to-pay measures, such as the subjective value of time, which varied among individuals. We also studied the systematic heterogeneity in individual tastes through the specification of models allowing for interactions between level-of-service and socio-economic variables. We concluded examining the sensitivity of travellers’ behaviour to various policy scenarios. In particular, it seems that contrary to political opinion, in a crowded island policies penalising the use of the private car seem to have a far greater impact in terms of bus patronage than policies implying direct improvements to the public transport service.     

模糊控制技术在船舶动力定位中的应用研究

在进行某船动力定位系统的设计过程中,采用了模糊控制器作为系统的控制器,并针对仿真过程中出现的问题进行优化,得到了一个切实可行的模糊控制器,并对该模糊控制器进行了仿真试验验证。     

基于遗传算法的舰船航速模糊控制研究

研究并建立了舰船航速控制系统的数学模型,并将模糊控制理论应用到该系统,提出了一种基于遗传算法的舰船航速模糊控制新方法。该方法较常规的模糊控制具有更优的控制性能,仿真实验结果表明该方法可行、有效。