Strategies for multi-step-ahead available parking spaces forecasting based on wavelet transform

A new methodology for multi-step-ahead forecasting was proposed herein which combined the wavelet transform(WT), artificial neural network(ANN) and forecasting strategies based on the changing characteristics of available parking spaces(APS). First, several APS time series were decomposed and reconstituted by the wavelet transform. Then, using an artificial neural network, the following five strategies for multi-step-ahead time series forecasting were used to forecast the reconstructed time series: recursive strategy, direct strategy, multi-input multi-output(MIMO) strategy, DIRMO strategy(a combination of the direct and MIMO strategies), and newly proposed recursive multi-input multi-output(RECMO) strategy which is a combination of the recursive and MIMO strategies. Finally, integrating the predicted results with the reconstructed time series produced the final forecasted available parking spaces. Three findings appear to be consistently supported by the experimental results. First, applying the wavelet transform to multi-step ahead available parking spaces forecasting can effectively improve the forecasting accuracy. Second, the forecasting resulted from the DIRMO and RECMO strategies is more accurate than that of the other strategies. Finally, the RECMO strategy requires less model training time than the DIRMO strategy and consumes the least amount of training time among five forecasting strategies.

Forecasting available parking space with largest Lyapunov exponents method

The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.

Developing Large-Scale Dry Ports—The Case of Arriyadh

The purpose of this paper is to explore the development process of a large scale dry port and to analyse what measures and actions are needed in order to support the decision making process and ensure an effective and efficient dry port that serves the City and the region’s current and future needs. The purpose is explored in the context of Saudi Arabiaand the city ofArriyadh. Key issues identified related to the dry port development are long term planning and crosssector collaboration. The interconnection between the dry port and the overall transport system and aspects, such as location of business, city logistics, road and rail infrastructure, local, regional and national regulations, etc., is strong. This puts challenge on the coordination and alignment of the different organizations, their strategies and objectives. In a complex situation, such as developing a dry port with many stakeholders, it is crucial that the roles of all actors are clearly defined. This is essential for utilizing the dry port as a regional tool for planning. In that regard, it is appropriate that the site location decision is clearly connected with an overall city freight vision and strategy.

Numerical Simulation of Dynamic Response of Saturated Sand During Shield Construction

In order to study the disturbance of the liquefiable stratum caused by the vibration induced by construction of the shield machine,the construction process of the shield tunnel was simulated based on the finite difference software FLAC 3 D.A sinusoidal velocity boundary that simulates the vibration of shield construction is applied in the horizontal direction of the excavation surface,and dynamic response analysis is carried out to analyze the excess pore water pressure,acceleration,and vertical effective stress time-history curves.The research results show that in the liquefiable stratum,the vibration induced by shield construction will form a certain liquefaction area in the soil in front of the excavation face.The area has not developed to the ground.The area where the vibration induced by shield construction has a great influence on the excess pore water pressure of the soil is below the excavation surface.This area is vortex-shaped.The excess pore water pressure of the overlying soil layer on the excavation surface increases,and the vertical effective stress decreases.The horizontal vibration wave induced by shield construction has no obvious attenuation in the horizontal direction,but has obvious attenuation during the propagation to the ground surface.In the area where the peak value of soil acceleration is large,the soil liquefaction is serious.

Automated Vehicle Handover Interface Design:Focus Groups with Learner,Intermediate and Advanced Drivers

Conditionally and highly automated vehicles will require drivers to take control as a result of a non-emergency,such as a geographical,terrain,capability or design boundary.It is anticipated that these events will provide the driver with a sufficient amount of time to prepare themselves for the transition of control.This study explores conditionally and highly automated vehicle transitions of control by asking how drivers of differing skill levels(learner,intermediate and advanced)approach the task of designing an interface responsible for making transitions safer,more usable and more efficient.Three focus groups generated detailed designs for vehicle-to-driver transitions in an 1-h and a 10-min“out-of-the-loop”scenarios and transitions from driver to vehicle.Results show great variation in the approaches taken by each skill group(e.g.,the reliance on visual interfaces for awareness assist and viewpoints on issues such as multimodal displays).Customization was a common theme throughout,with drivers desiring the option to adjust alert timings and modalities in which information is displayed.This paper presents these designs along with a detailed comparison of group designs and implements distributed situation awareness theory to discuss findings and draw conclusions.

Constraining Design:Applying the Insights of Cognitive Work Analysis to the Design of Novel In-Car Interfaces to Support Eco-Driving

The design with intent(DwI)toolkit assists designers in creating novel designs and interfaces.DwI,however,is not constrained to any degree,making it impossible to know whether the produced designs adequately account for users’needs.In contrast,cognitive work analysis(CWA)is a human factors research tool that seeks to map a system and account for users’needs,yet does not provide clear guidelines for progressing such analysis into workable designs with which users can interact.This paper seeks to present a proof-of-concept investigation to demonstrate that DwI can be suitably constrained and validated by insights gained from CWA.CWA,in turn,benefits by having a suitable toolkit for progressing insights.Two teams of individuals without design backgrounds were able to develop mock-up in-vehicle interfaces aimed at reducing fuel use.The teams were able to use DwI toolkit to articulate the genesis of their ideas,which in turn could be directly linked to system needs identified within CWA.