Transportmetrica 

About: Transportmetrica is an academic journal. The journal publishes majorly in the area(s): Poison control & Traffic flow. It has an ISSN identifier of 1812-8602. Over the lifetime, 685 publications have been published receiving 11975 citations.

Incorporating pro-environmental preferences towards green automobile technologies through a Bayesian hybrid choice model

Abstract: In this article we develop, implement and apply a Markov chain Monte Carlo (MCMC) Gibbs sampler for Bayesian estimation of a hybrid choice model (HCM), using stated data on both vehicle purchase decisions and environmental concerns. Our study has two main contributions. The first is the feasibility of the Bayesian estimator we derive. Whereas classical estimation of HCMs is fairly complex, we show that the Bayesian approach for HCMs is methodologically easier to implement than simulated maximum likelihood because the inclusion of latent variables translates into adding independent ordinary regressions; we also find that, using the Bayesian estimates, forecasting and deriving confidence intervals for willingness to pay measures is straightforward. The second is the capacity of HCMs to adapt to practical situations. Our empirical results coincide with a priori expectations, namely that environmentally-conscious consumers are willing to pay more for low-emission vehicles. The model outperforms standard discr...

A review of travel time estimation and forecasting for Advanced Traveller Information Systems

Abstract: Due to the increase in vehicle transit and congestion in road networks, providing information about the state of the traffic to commuters has become a critical issue for Advanced Traveller Information Systems. These systems should assist users in making pre-trip and en-route decisions and, for this purpose, delivering travel time information is very useful because it is very intuitive and easily understood by all travellers. The aim of this paper is to present a global view of the literature on the modelling of travel time, introducing essential concepts and giving a thorough classification of the existing techniques. Most of the attention will focus on travel time estimation and travel time prediction, which are two of the most relevant challenges in travel time modelling. The definition and goals of these two modelling tasks along with the methodologies used to carry them out will be further explored and categorised.

Dynamic traffic assignment: properties and extensions

Abstract: Dynamic Traffic Assignment (DTA) is long recognized as a key component for network planning and transport policy evaluations as well as for real-time traffic operation and management. How traffic is encapsulated in a DTA model has important implications on the accuracy and fidelity of the model results. This study compares and contrasts the properties of DTA modelled with point queues versus those with physical queues, and discusses their implications. One important finding is that with the more accurate physical queue paradigm, under certain congested conditions, solutions for the commonly adopted dynamic user optimal (DUO) route choice principle just do not exist. To provide some initial thinking to accommodate this finding, this study introduces the tolerance-based DUO principle. This paper also discusses its solution existence and uniqueness, develops a solution heuristic, and demonstrates its properties through numerical examples. Finally, we conclude by presenting some prospective future research di...

Short-term traffic flow prediction based on spatio-temporal analysis and CNN deep learning

Abstract: Accurate short-term traffic flow forecasting facilitates active traffic control and trip planning. Most existing traffic flow models fail to make full use of the temporal and spatial features of tr...

A new multi-class continuum model for traffic flow

Abstract: In this paper, we propose a new continuum model and study some qualitative properties. The new model contains an additional speed gradient term (anisotropic term) in comparison to Berg's model (Ber...