In this paper we review freight forecasting models and current advances needs with respect to data model development. We then present a case study suggest which should be developed for the State of California in US. several alternatives including an aggregate commodity flow model, disaggregate regional logistics hybrid truck touring model. point out however, that requirements latter would extensive. addition, development models, example progress integration urban will introduce new problems...

A primary goal of intelligent transportation systems is to improve road safety. The ability vehicles communicate a promising way alleviate traffic accidents by reducing the response time associated with human reaction nearby drivers. Vehicle mobility patterns caused varying dynamics and travel behavior lead considerable complexity in efficiency reliability vehicular communication networks. This causes two major routing issues: broadcast storm problem network disconnection problem. In this...

We present ADDSEN middleware as a holistic solution for Adaptive Data processing and dissemination Drone swarms in urban SENsing. To efficiently process sensed data the middleware, we have proposed cyber-physical sensing framework using partially ordered knowledge sharing distributed management drone swarms. A reinforcement learning strategy is implemented framework. uses online techniques to adaptively balance broadcast rate loss periodically. The learned adapted by executing state...

Hyperspectral images (HSIs) have gained high spectral resolution due to recent advances in imaging technologies. This incurs problems, such as an increased data scale and number of bands for HSIs, which results a complex correlation between different bands. In the applications remote sensing earth observation, ground objects represented by each HSI pixel are composed physical chemical non-Euclidean structures, classification (HIC) is becoming more challenging task. To solve above we propose...

In the field of hyperspectral image (HSI) classification, deep learning has helped achieve great successes. However, most these achievements are made with very large amounts labeled training data. Manual annotation HSIs is labor intensive and time consuming. practical HSI there may only be a few samples available. To perform classification small number samples, new few-shot model based on adaptive subspaces featurewise transformation proposed in this article. First, we design 3-D local...

The procurement of transportation services is an important task for shippers because the need to control costs while providing high service levels. When transport goods and materials, they seek from outside companies typically issue a request quotes group carriers. then assign contracts on basis negotiated charges. This process similar simple sealed-bid auction in which each bidder submits sealed bid single item. In past, when needed procure set distinctive delivery routes (called lanes),...

It is a challenge to design efficient routing protocols for vehicular ad hoc networks (VANETs) because of their highly dynamic properties. We address the communication problem in urban hybrid and present scheme data dissemination VANETs. Location-based crowdsourcing nearby roadside units (RSUs) has been applied infrastructural support inter-vehicle, vehicle-to-roadside, inter-roadside communications The combination RSU resources involves an online probabilistic retrieval algorithm that uses...

Convolutional neural networks (CNNs) have achieved remarkable performance in driver drowsiness detection based on the extraction of deep features drivers' faces. However, methods decreases sharply when complications, such as illumination changes cab, occlusions and shadows driver's face, variations head pose, occur. In addition, current are not capable distinguishing between states, talking versus yawning or blinking closing eyes. Therefore, technical challenges remain detection. this...

At the core of any flight schedule is four dimensional (4D) trajectories which are comprised three spatial dimensions with time added as fourth dimension. Each trajectory contains and temporal features that associated uncertainties make prediction process complex. Because increasing demand for air transportation, airports airlines must have optimized schedules to best use airports' infrastructure potential. This possible using advanced methods. paper proposes a novel hybrid deep learning...

Individuals driving private cars in the urban environments to fulll their travel needs have become one of major daily activities. In particular, unlike with floating such as taxis or ride-hailing vehicles, behaviors exhibit a certain degree regularity based on demands. Understanding behavior facilitates many applications, e.g., intelligent transportation, smart city planning, and location-based services (LBS). this paper, we focus extracting regular trajectory data analysis. Specifically,...

The problem of dynamic fleet management for truckload carrier operations is introduced, and the principal elements a simulation framework evaluation systems are described. application simulated to investigation performance family real-time operational strategies, which include load acceptance, assignment, reassignment also described an example first-generation tool systems. Selected experimental results highlighted. These intended illustrate some issues encountered in role modeling...

The application of intelligent transportation system technologies to freight mobility requires dynamic decision-making techniques for commercial fleet operations, using real-time information. Recognizing the productivity-enhancing operational changes possible information about vehicle locations and demands coupled with constant communication between dispatchers drivers, a general carrier management is described. features dispatching, load acceptance, pricing strategies. A simulation...

We consider a finite-horizon, periodic-review inventory model with demand forecasting updates following the martingale of forecast evolution (MMFE). The optimal policy is state-dependent base-stock policy, which, however, computationally intractable to obtain. develop tractable bounds on levels and use them devise general class heuristic solutions. Through this analysis, we identify necessary sufficient condition for myopic be optimal. Finally, assess effectiveness policies, upper their...

The scarcity of parking spaces in cities leads to a high demand for timely information about their availability. In this paper, we propose crowdsensed system, namely ParkCrowd, aggregate on-street and roadside space reliably, disseminate drivers manner. Our system not only collects disseminates basic information, such as hours price, but also provides with on the real time future availability based aggregated crowd knowledge. To improve reliability being disseminated, dynamically evaluate...

Small to medium sized transportation and logistics companies are usually constrained by limited computing IT professional resources on implementing an efficient parallel metaheuristic algorithm for planning or management solutions. In this paper we extend the standard meta-description genetic algorithms (GA) with a simple non-trivial implementation. Our GA framework is chiefly concerned development of straightforward way engineers modify existing implementations real problems make use...

The graph-based hyperspectral image classification (HSIC) method has attracted wide attention because it can extract information with a non-Euclidean structure. Many HSIC works have achieved good results, but unresolved technical issues remain. For example, many graph nodes lead to high computational costs, and the mining of structures is not sufficient. To solve these problems, we propose network an adaptive structure (GAT-AGSM) approach. Specifically, first framework superpixel feature...