Discrete dynamic models for freeway incident detection systems

This paper considers the problem of freeway incident detection within the general framework of computer‐based freeway surveillance and control. A new approach to the detection of freeway traffic incidents is presented based on a discrete‐time stochastic model of the form ARIMA (0, 1, 3) that describes the dynamics of traffic occupancy observations. This approach utilizes real‐time estimates of the variability in traffic occupancies as detection thresholds, thus eliminating the need for threshold calibration and lessening the problem of false‐alarms. Because the moving average parameters of the ARIMA (0, 1, 3) model change over time, these parameters can be updated occasionally. The performance of the developed detection algorithm has been evaluated in terms of detection rate, false‐alarm rate, and average time‐lag to detection, using a total of 1692 minutes of occupancy observations recorded during 50 representative traffic incidents.     

Patterns of urbanization and energy requirements: recent regulation changes and simulation studies concerning American urban areas

In recent years, the world economy has become more integrated internationally and container transportation has become increasingly more important as the proportion of all trade using containers is continuously growing. In order to adapt to the increasing containerization trend, it is essential to plan and construct adequate ports and facilities to cope with this development.

Based on the analysis of factors influencing container movements, this paper illustrates the logical relationships for a distribution model, which has been used to predict the distribution of containers among the three main Seaports near Shenzhen and Hong Kong. A fuzzy number‐based distribution model is outlined in the paper. The paper illustrates the main influencing factors and their logical relationships and proposes a primary distribution model where the attractiveness of each port has been calibrated. The results show that the Port of Hong Kong is significantly more attractive than the other two ports modelled and is likely to continue to be so in the future.     

Collecting longitudinal data from freight operators: survey design and implementation ideas and challenges

Freight transport research has generally been limited by a lack of data of the breadth and quality available for passenger transport, particularly in terms of behavioural data. This paper discusses the survey design and implementation of a survey intended to collect longitudinal behavioural data on the responses of freight transport firms to environmental policies. The design of the survey is centred around a hypothetical scenario where respondents are asked how they would complete a given freight task within common constraints. One of the key components of the survey design is a dynamic component intended to simulate the changing business environment. The paper illustrates the many challenges in getting complex freight related surveys in the field.     

Flexible long range planning using low cost information

Contemporary transport planning requires a flexible modelling approach which can be used to monitor the implementation of a long term plan checking regularly its short term performance with easily available data; the original model is periodically updated using low cost information and this allows the evaluation of the changes to the plan which may be required. Such an approach requires models suited to regular updating and to the use of data from different sources. Models to update trip matrices from traffic counts have been available for some time; however, the estimation and/or updating of other model stages with low cost data has escaped analytical treatment. The paper discusses this idea and formulates the updating problem for an example involving a joint destination/mode choice model under various assumptions about the nature of the available data. Analytical solutions are proposed as well as some general conclusions.requests for offprints     

Origin–destination missing data estimation for freight transportation planning: a gravity model-based regression approach

This paper develops a log-linear regression approach to estimate missing data in a sparse origin–destination (O–D) matrix assuming the sampled or observed O–D trips follow a good gravity pattern. The approach is tested with randomly selected samples from the known portions of 1997, 2002, and 2007 US Commodity Flow Survey (CFS) O–D value and tonnage matrices and validated with 2007 US O–D tonnage matrix at the state level. The missing data are also estimated for the 2007 CFS tonnage matrix with the best intercept and coefficients obtained using all known entries of the matrix. The concept of the approach can be extended beyond the gravity model to any strong mathematical pattern embedded in the known set of a sparse O–D matrix to estimate its missing cells.     

“十三五”时期我国综合交通投资和运输形势分析

以综合交通运输行业发展中的建设投资、路网设施、旅客运输、货物运输方面统计数据指标为基础,通过分析总量指标在“十三五”时期的绝对值、增速,以及各交通运输方式结构指标变化情况,并与“十二五”时期相关指标变化进行对比分析,总结了“十三五”时期的综合交通建设投资、旅客运输和货物运输形势,表明“十三五”时期是综合交通运输从高速度增长向高质量发展的过渡阶段,具体表现为总量扩张趋缓、结构优化明显、升级动力减弱等三大特征,体现在交通投资和供给需求规模增速放缓,高快速交通方式的供需比重增加,交通生产投入的边际产出趋向递减等方面。     

What transportation modeling needs from a GIS: a conceptual framework

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.