Induced road traffic in Spanish regions: A dynamic panel data model

Distinguishing between traffic generated exclusively from the expansion of the road network (induced demand) and that resulting from other demand factors is of crucial importance to properly designed transport policies. This paper analyzes and quantifies the induced demand for road transport for Spain’s main regions from 1998 to 2006, years that saw mobility in Spain attain its highest growth rate. The lack of research in this area involving Spain and the key role played by the sector, given its high level of energy consumption and the negative externalities associated with it (accidents, noise, traffic congestion, emissions, etc.), endow greater relevance to this type of research. Based on a Dynamic Panel Data (DPD) reduced-form model, we apply alternative approaches (fixed and random effects and GMM-based methods) for measuring the induced demand. The results obtained provide evidence for the existence of an induced demand for transport in Spain, though said results vary depending on the estimating method employed.     

Identifying a behaviourally relevant choice set from stated choice data

Stated choice experiments are designed optimally in a statistical sense but not necessarily in a behavioural choice making sense. Statistical designs, and consequently model estimation, assume that the set of alternatives offered in the experiment are processed by respondents with a specific processing strategy. Much has been studied about attribute processing using discrete choice methods in travel choice studies, but this paper focuses more broadly on processing of alternatives in the choice set offered in the experiment. This paper is motivated by the primary idea that the distribution of predicted choice probabilities associated with a set of alternatives defining a given choice set might provide strong evidence on the strategies that agents appear to use when choosing a preferred alternative. In an empirical setting of a choice set of size three, four model specifications are considered including a model for the selection of the best alternative in the full choice set and three variants of a best–worst regime. Using state choice data on road pricing reform, the empirical analysis examines which model specification delivers the most accurate prediction of the chosen alternative. The results suggest which alternatives really matter in choice making and hence the alternatives that might be included in a choice set for model specification.     

The Increasing Role of Latent Variables in Modelling Bicycle Mode Choice

The growing interest in promoting non-motorised active transport has led to an increase in the number of studies to identify the key variables associated with bicycle use, and especially those related to the bicycle mode choice problem. This paper presents a comprehensive survey of the modelling literature on the choice of the bicycle for utilitarian purposes, and summarises and assesses the evolution of the explanatory variables and methodologies used. We review both the evolution of the incorporation of latent variables in bicycle mode choice models and the critical role they play. The chronological evolution of the studies is divided into three stages —initial, intermediate and late — according to the different ways of introducing attitudinal or perceptual indicators and latent variables into the models. Our review shows that the incorporation of latent variables in bicycle choice models has increased in the last decade, with a progressive use of more sophisticated methodologies until the arrival of complex models that explicitly and properly deal with psychological latent variables. In fact, with the use of hybrid choice models, latent variables have nowadays become the core of bicycle mode choice models. Based on our review, a set of questions is proposed as a uniform measurement scale to identify attitudes towards bicycling. Recommendations for future research are also presented.     

Estimating bus run times for new limited-stop service using archived AVL and APC data

In recent years, several transit agencies have been trying to be more competitive with the automobile to attract choice riders. Transit agencies can only be competitive if they can provide services that are reliable, have a short access and egress time, and have run times that are comparable to automobiles. Several transit agencies try to be competitive through offering faster service, such as limited-stop (express) bus service. This study uses AVL and APC data, in addition to a disaggregate data obtained from a travel behavior survey, to select stops and estimate run times for a new limited-stop service that will run parallel to a heavily used bus route (67 Saint-Michel) in Montréal, Canada. Three different scenarios are developed based on theory and practice to select stops to be incorporated in the new limited service. The time savings for each scenario are then evaluated as a range and a fourth scenario is developed. A limited-stop service is recommended based on selecting stops serving both directions of the route, major activity points and stop spacing. This study shows that implementing a limited-stop service would yield substantial time savings for both, the new limited service and the existing regular service running in parallel.     

A basic mathematical model for evacuation problems in urban areas

Real life situations like floods, hurricanes or chemical accidents may cause the evacuation of a certain area to rescue the affected population. To enable a fast and a safe evacuation a basic mixed-integer evacuation model has been developed that provides a reorganization of the traffic routing of a certain area for the case of an evacuation. This basic problem of evacuation minimizes the evacuation-time while prohibiting conflicts within intersections. Our evacuation model is a dynamic network flow problem with additional variables for the number and direction of used lanes and with additional complicating constraints.Because of the size of the time-expanded network, the computational effort required by standard software is already very high for tiny instances. To deal with realistic instances we propose a heuristic approach.     

An alternative model in traffic flow equations

The kinetic theory for traffic flow equations can be approached using the Grad’s method. This method, which is derived from the kinetic gas theory, was developed for the Paveri-Fontana equation when a special desired velocity model is assumed. A closure relation for the set of macroscopic equations is found when the density, the average velocity and the velocity variance are the relevant variables chosen to describe the system. Simulation results are also shown and a qualitative comparison with other models in the literature is presented.     

Revenue management in the parking industry: a multiple garage intelligent reservation model

This paper explores how advanced reservations, coupled with dynamic pricing (based on booking limits) can be used to maximize parking revenue. An integer programing formulation that maximizes parking revenue over a system of garages is presented. Furthermore, an intelligent parking reservation model is developed that uses an artificial neural network procedure for online reservation decision-making. Finally, the paper provides some strategic and managerial implications of multi-garage revenue management systems, and discusses techniques for identifying and implementing micro-market segmentation in the parking industry.     

Real-time traveler information for urban arterials: a method for selecting metropolitan routes of significance

Although multi-criteria analysis (MCA) has been commonly used to guide transportation decisions related to traditional infrastructure, limited applications are reported for intelligent transportation systems. The objective of this study is to apply MCA for selecting arterial routes for real-time traveler information, to conform with recent US federal regulations. This study applies the method in two metropolitan areas and the paper describes which criteria were chosen and how important each were considered. In all, this study guided the selection of seven arterial routes for deployment of real-time traveler information collection and dissemination. This study demonstrates how a transportation agency can apply MCA for traveler information planning and the method provides value for other agencies seeking to come into compliance with traveler information regulations.     

基于SVM的隧道衬砌空洞填充物雷达图像识别研究北大核心CSCD

衬砌背后空洞及其填充物对隧道结构安全具有重要影响,开展空洞探测识别对于结构安全评估和病害处置具有重要意义。首先采用室内试验和FDTD正演模拟相结合的方法,获得了空洞内填充空气、水、干砂、湿砂条件下的雷达图谱数据,并对不同填充物波形规律进行对比分析;然后,基于支持向量机算法对波形特征进行提取和分类识别,建立了一种空洞填充物的人工智能辨识方法。研究结果表明,采用傅里叶变换前的平均值、方差、平均绝对离差和傅里叶变换后的最大幅度值max(fft(X))四个统计量作为支持向量机的识别特征,可以有效区分出衬砌背后填充物的六种类型;当采取单一倾向数据时,识别准确率较好,六种物质二分类问题准确率均可以达到90%以上。     

Use of duration models for predicting vehicular delay at a US/Canadian border crossing

Delays caused by congestion at the US/Canadian border crossing between Washington state and British Columbia have underscored the need for some sort of intervention. One obvious congestion-mitigation measure would be to estimate delay times and then relay this information to motorists so that they could select among alternative border crossing sites, or delay their trips. This paper applies duration models to estimate vehicular delay and demonstrates the usefulness of such models as a basis for a fully automated motorist information system. The paper also explores the flexibility of duration models, in providing estimates of vehicle delay, by using alternate parametric forms and assessing prediction accuracy.