This paper proposes a stochastic user equilibrium assignment model for ascertaining the difference in the travel mode choice behavior in a degradable multi-modal traffic network. In the proposed model, on the basis of the actual travel behavior which often needs to transfer different traffic modals, all the travels are categorized into two classes: pure car trip travelers and combined mode trip...

We introduce the concept of continuous transportation task to the context of multi-agent systems. A continuous transportation task is one in which a multi-agent team visits a number of fixed locations, picks up objects, and delivers them to a transportation hub. The goal is to maximize the rate of transportation while the objects are replenished over time . In this extended abstract, we present...

The proliferation of fake news and its serious negative social influence push detection methods to become necessary tools for web managers. Meanwhile, the multi-media nature media makes multi-modal popular ability capture more modal features than uni-modal methods. However, current literature on is likely pursue accuracy but ignore robustness (the in case abnormality malicious attack) detector....

This study defines a methodology to compute unitary costs for freight transportation modes. The main objective was to gather relevant costs data to support the formulation and evaluation of railway, road, pipelines and port projects. This article will concentrate on the following steps: Compilation and analysis of relevant modal cost studies, Methodological adjustments to make cost figures comp...

We introduce the concept of continuous transportation task to the context of multi-agent systems. A continuous transportation task is one in which a multi-agent team visits a number of fixed locations, picks up objects, and delivers them to a transportation hub. The goal is to maximize the rate of transportation while the objects are replenished over time . In this extended abstract, we present...

Whilst there is an increasing capability to instrument smart cities using fixed and mobile sensors to produce the big data to better understand and manage transportation use, there still exists a wide gap between the sustainability goals of smart cities, e.g., to promote less private car use at peak times, with respect to their ability to more dynamically support individualised shifts in multi-...

hris Harding is an assistant professor at Iowa State University’s Human-computerinteraction program and is interested in designing multi-modal interfaces for geoscientists. In his presentation, he will share some of the experiences of working with geoscientific Virtual Environments and multi-modal interfaces over the last years and talk about the opportunities and challenges of increasing the u...

An object model of multi-modal transport networks is developed with particular emphasis on applications in trip planning. The model caters for both public and private transport modes, and incorporates spatial and temporal data. A uniform approach to optimum trip nding across multi-modal transport networks is developed. The multi-modal network is spatially ordered using a quadtree storage object...

We introduce Multi-Modal Utility Trees (MMU), an algorithm for autonomously learning decision treebased state abstractions in Partially Observable Markov Decision Processes with multi-modal observations. MMU builds the trees using the Kolmogorov-Smirnov statistical test. Additionally, MMU incorporates the ability to perform online tree restructuring, enabling it to build and maintain a compact ...