Search

The discrete choice analysis of residential location choice forms an important part of land use-transport modelling systems but gives rise to a number of significant modelling challenges, one of which is the choice set formation problem. A number of alternative approaches exist to addressing the choice set formation problem, but to the best of our knowledge, there have been no efforts to empirically compare their performance using real choice data. In this paper, we propose to address this gap by examining the performance of several choice set formation methods within the context of residential location choice in London. The paper presents a brief review of the relevant theoretical and empirical literature on the treatment of the choice set formation problem in the context of spatial choice and sets out the characteristics of the specific modelling approaches implemented in the empirical research. In particular, we compare a recently proposed hazard-based screening model with more conventional pure statistical treatments. The empirical research uses a specially constructed data-set on residential location choice, developed by the authors for the Greater London area, which draws on information from a number of separate data sources (including revealed preference data from the London Area Travel Survey). The alternative choice set formation approaches are assessed in terms of their prediction performance on a hold-out validation sub-sample and also in terms of estimated model parameters. [ABSTRACT FROM PUBLISHER]

Vehicular Ad-Hoc Networks (VANETs) attract considerable research and commercial interest with promising applications in a number of areas including cooperative vehicle-highways systems, sensor networks, and safety systems. However, as a result of high speed and variable driver behavior, automotive ad-hoc networks behave in fundamentally different ways to the most prevalent models in Mobile Ad-Hoc Network (MANET) research. Previous work in MANETs has mostly assumed that the mobile nodes move randomly with an unconstrained mobility model, and it is clear that a random mobility model is not adequate to represent the major characteristics of real-world vehicle motions and may therefore lead to unreliable results. Recent studies of VANETs have attempted to introduce macro- and micromobility constraints to model vehicle motions, but they have mostly focused on modeling the mobility of generic private vehicles. Given the potential for the coordinated deployment of network nodes on centrally managed fleet vehicles, it has become important to model the characteristics of a VANET featuring vehicles of different types, with systematically different behavior patterns. In this article, the authors study the connectivity of mobile ad-hoc networks that consist of buses moving in urban area and examine the implications for transport-related services. Buses have a unique set of behavior characteristics (e.g., fixed routes, schedules, bus stops, specific priorities), which gives rise to distinct effect on node connectivity in the communication network. Through extensive simulations on the basis of real bus routes in central London, the authors (a) demonstrated the effect of the locations of stops and the prevailing traffic patterns on node connectivity (including the distributions of contact duration and intercontact time between buses) and (b) explored its implication on the design of a dissemination system to capture and disseminate data. Their results give a key message that the mobility of buses has to be modeled explicitly, and such kind of knowledge of connectivity among buses will be significant for the studies of routing algorithms and other networking functions in interbus communication networks. [ABSTRACT FROM AUTHOR]

The space and time dynamics of moving vehicles regulated by traffic signals governs the node connectivity and communication capability of vehicular ad hoc networks (VANETs) in urban environments. However, none of the previous studies on node connectivity has considered such dynamics with the presence of traffic lights and vehicle interactions. In fact, most of them assume that vehicles are distributed homogeneously throughout the geographic area, which is unrealistic. We introduce in this paper a stochastic traffic model for VANETs in signalized urban road systems. The proposed model is a composite of the fluid model and stochastic model. The former characterizes the general flow and evolution of the traffic stream so that the average density of vehicles is readily computable, while the latter takes into account the random behavior of individual vehicles. As the key contribution of this paper, we attempt to approximate vehicle interactions and capture platoon formations and dissipations at traffic signals through a density-dependent velocity profile. The stochastic traffic model with approximation of vehicle interactions is evaluated with extensive simulations, and the distributional result of the model is validated against real-world empirical data in London. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the knowledge of the mean vehicular density dynamics and its probability distribution from the stochastic traffic model, we determine the degree of connectivity in the communication network and illustrate that system engineering and planning for optimizing both the transport (in terms of congestion) and communication networks (in terms of connectivity) can be carried out with the proposed model. [ABSTRACT FROM PUBLISHER]

Travel time is an important indicator of network performance used in traffic operations and management. Commonly deployed inductive loop detectors (ILDs) measure time-mean-speed (TMS), whereas space-mean-speed (SMS) is required to calculate the travel time. A well-known relationship between the TMS and the SMS was derived by Wardrop. However, this relationship cannot be used in practice to estimate travel times as it requires knowledge of the variance of the SMS. The variance of the SMS is not measured by the ILDs and is normally not available in practice. A novel formulation is presented in this paper to estimate the SMS using TMS obtained from ILDs. In addition, two additional models based on the formulation are developed to improve the estimation performance by taking traffic states into account. The initial results show that the proposed formulation can used to estimate the SMS, and hence the travel time, accurately using real-world data. [ABSTRACT FROM AUTHOR]

Abstract: This paper discusses a number of issues relating to the pre-analysis and cleaning of stated choice data, where we look specifically at the problems caused by non-trading, lexicographic and inconsistent response patterns. We argue that this process is considerably more complex and challenging than many in the field have hitherto acknowledged, with the standard practice being the use of rather ad hoc procedures for the identification of these phenomena. A detailed analysis on four different stated choice datasets highlights the potential impacts of these methods on model estimation results. [Copyright &y& Elsevier]