最小规模算法在路面施工机械选型中的应用

如何选择既经济又能满足施工要求的施工机械,是沥青路面施工单位提高设备利用率和经济效益的重要举措,而对其进行量化分析是十分重要的。     

Evaluating the assumption of independent turning probabilities

Several urban traffic models make the convenient assumption that turning probabilities are independent, meaning that the probability of turning right (or left or going straight through) at the downstream intersection is the same for all travelers on that roadway, regardless of their origin or destination. In reality most travelers make turns according to planned routes from origins to destinations. The research reported here identifies and quantifies the deviations that result from this assumption of independent turning probabilities.An analysis of this type requires a set of reasonably realistic “original” route flows, which were obtained by a static user-equilibrium traffic assignment and an entropy maximization condition for most likely route flows. These flows are compared with those route flows resulting from the Assumption of Independent Turning Probabilities (ITP). A small subnetwork of 3 km by 5 km in Tucson, Arizona, was chosen as a case study. An overall “typical ratio” of 2.2 between original route flows and ITP route flows was obtained. Aggregating route flows to origin–destination flows led to an overall “typical ratio” of 1.7. Such deviations are particularly high for routes that go back-and-forth, reaching a ratio of more than 3 in certain time periods. Substantial deviations for origins and destinations that are on the same border of the subnetwork are also observed in the analyses. In addition, under the ITP assumption, morning rush hour traffic peaking is the same in all directions, while in the original flows some directions do not exhibit a peak in the morning rush hour period. Overall, the conclusion of the paper is that the assumption of independent turning probabilities leads to substantial deviations both at the route level and at the origin–destination level, even for such a small network of the case study. These deviations are particularly detrimental when a network is being modeled and studied for route-based measures of effectiveness such as the number and types of routes passing a point – for monitoring specified vehicles and/or managing detouring strategies.     

受调峰影响明显的基本站及沿程设计最低通航水位推算

结合汀江设计通航水位的研究,通过对基本站溪口、三河坝设计水位多种方法的推算分析研究,提出在无基流下泄受调峰影响严重的近坝河段,基本站在不超过35km范围内,可采用低水累积频率法计算设计最低通航水位,并对该类河段沿程瞬时水面线选择进行探讨。     

Correcting state dependence and serial correlation in the RP/SP combined estimation method

Revealed preference (RP) data and stated preference (SP) data have complementary characteristics for model estimation. To enhance the advantages of both data types, a combined estimation method is proposed. This paper discusses the method and practical considerations in applying it, and introduces a new method of considering serial correlation of RP and SP data. An empirical analysis is also presented.     

Modeling cyclists' facility choice and its application in bike lane usage forecasting

In some circumstances on streets equipped with new bike facilities, cyclists are not interested in using them. Instead, they continue to use shared spaces with pedestrians or motor vehicles. Thus, simply adding a bike facility does not guarantee that cyclists will switch to using it. Owing to the considerable development of bike facilities, the investigation of facility preference, particularly focusing on facility choice forecast, has become increasingly important. This study developed a model for predicting the facility choice of cyclists between on-street facilities (curb, traffic lane, and bike lane (BL)) and off-street facilities (sidewalks). Initially, the optimal model was selected using Bayesian Model Averaging method. Then, it was validated by both internal and external validations. Apart from the aforementioned factors, several other exogenous variables were also found to be significant predictors of bike facility choice, including the width of traffic lanes, existence of real-time stopping vehicle, type of bike, bus stop existence, and in-group cycling. Analysis of the relative importance of predictors indicated that bus stop existence, effective sidewalk width, and type of bike were the potential predictors. A framework for predicting BL usage, if it is present, was also developed. A test for the predictive performance of the application at a real site was carried out. By comparing predicted and actual BL usage figures, the analysis showed good predictive performance. The results of this study can help developers, planners, and designers to adopt reasonable investment decisions as well as better designs in developing new bike facilities.     

Accounting for stochastic variables in discrete choice models

The estimation of discrete choice models requires measuring the attributes describing the alternatives within each individual’s choice set. Even though some attributes are intrinsically stochastic (e.g. travel times) or are subject to non-negligible measurement errors (e.g. waiting times), they are usually assumed fixed and deterministic. Indeed, even an accurate measurement can be biased as it might differ from the original (experienced) value perceived by the individual.Experimental evidence suggests that discrepancies between the values measured by the modeller and experienced by the individuals can lead to incorrect parameter estimates. On the other hand, there is an important trade-off between data quality and collection costs. This paper explores the inclusion of stochastic variables in discrete choice models through an econometric analysis that allows identifying the most suitable specifications. Various model specifications were experimentally tested using synthetic data; comparisons included tests for unbiased parameter estimation and computation of marginal rates of substitution. Model specifications were also tested using a real case databank featuring two travel time measurements, associated with different levels of accuracy.Results show that in most cases an error components model can effectively deal with stochastic variables. A random coefficients model can only effectively deal with stochastic variables when their randomness is directly proportional to the value of the attribute. Another interesting result is the presence of confounding effects that are very difficult, if not impossible, to isolate when more flexible models are used to capture stochastic variations. Due the presence of confounding effects when estimating flexible models, the estimated parameters should be carefully analysed to avoid misinterpretations. Also, as in previous misspecification tests reported in the literature, the Multinomial Logit model proves to be quite robust for estimating marginal rates of substitution, especially when models are estimated with large samples.     

Planning school transport: design of routes with flexible school opening times

Abstract

This paper puts forward a methodology for designing a system for school transport which, apart from designing routes, specifies school opening times. Traditionally school opening times have always been identical in the same area meaning many buses have to be used at the same time. This paper suggests the staggering of school opening times in order to minimise the number of buses and thereby reduce the enormous costs involved in running them. The methodology is based on: a first phase which addresses the classic routing problem by using mixed integer lineal programming and a second phase which uses bi-level programming to find the vector for school opening times, which, when staying within the constraints of the problem, minimises the direct costs of the system. The upper level represents the evaluation of the system costs and the lower level finds the best combination of optimum routes for the same bus.     

International experience with speed limits during and prior to the energy crisis of 1973–4

This paper presents an artificial neural network (ANN) based method for estimating route travel times between individual locations in an urban traffic network. Fast and accurate estimation of route travel times is required by the vehicle routing and scheduling process involved in many fleet vehicle operation systems such as dial‐a‐ride paratransit, school bus, and private delivery services. The methodology developed in this paper assumes that route travel times are time‐dependent and stochastic and their means and standard deviations need to be estimated. Three feed‐forward neural networks are developed to model the travel time behaviour during different time periods of the day‐the AM peak, the PM peak, and the off‐peak. These models are subsequently trained and tested using data simulated on the road network for the City of Edmonton, Alberta. A comparison of the ANN model with a traditional distance‐based model and a shortest path algorithm is then presented. The practical implication of the ANN method is subsequently demonstrated within a dial‐a‐ride paratransit vehicle routing and scheduling problem. The computational results show that the ANN‐based route travel time estimation model is appropriate, with respect to accuracy and speed, for use in real applications.     

客运专线旅客出行选择行为分析

旅客出行选择行为的研究，对了解旅客的实际出行需求状况，科学地制定客运专线运输组织模式具有重要的参考价值。本文在考虑影响旅客出行选择行为的各种因素的基础上，模拟了旅客出行的选择过程。利用非集计方法，构造了旅客出发时刻和运输方式选择行为的双层巢式逻辑决策模型，并对模型参数的估计方法进行分析。在大量问卷调查基础上，收集了石太客运专线旅客出行选择行为的叙述性偏好和显示性偏好数据，并对数据进行深层次的挖掘工作。利用最大似然法，对模型的上下选择层的参数进行估计。根据回归得到的参数，分析了当城际之间的客运通道引入客运专线时，旅客的个人社会经济因素、时间因素、运输方式等属性对旅客出行选择行为的影响。     

基于Agent的个性化信息服务研究与实现

针对ITS下的出行者信息服务领域中，出行者对出行信息的个性化需求问题，采用决策树方法来获取用户对信息的个性需求，利用Agent技术建立信息服务终端模型，并定义各组件的功能。此外，还在出行终端的基础上，提出以移动处理为指导思想的ITS信息服务网络结构模型。