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Underground parking projects are expensive. The capital cost of underground parking projects has been, and still is, one of the promoter’s main economic concerns. Therefore, the capital cost estimation is an essential task in the early stages of underground parking projects. In this context, the promoters mainly use cost estimation models, most of them produced by methodologies with lack of precision and with low performances. Over the last years Portugal has embarked on a large programme of underground parking projects in the major cities. The present research work is based on data and knowledge colleted from that programme. This paper presents an analysis of the underground parking projects built and underway in Portugal. It discusses the main variables influencing the capital cost of under‐ground parking projects. Finally, it presents a mathematical model for estimating capital cost of this type of project during the planning phase.

This paper investigates the semantic association mechanisms of weak demand signals that facilitate innovative product development in terms of conceptual and temporal precedence, despite their inherent ambiguity and uncertainty.

To address this challenge, a domain ontology approach is proposed to construct a customer demand scenario-based framework that eliminates the blind spots in weak demand signal identification. The framework provides a basis for identifying such signals and introduces evaluation indices, such as depth, novelty and association, which are integrated to propose a three-dimensional weak signal recognition model based on domain ontology that outperforms existing research.

Empirical analysis is carried out based on customer comments of new energy vehicles on car platform such as “Auto Home” and “Bitauto”. Results demonstrate that in terms of recognition quantity, the three-dimensional weak demand signal recognition model, based on domain ontology, can accurately identify six demand weak signals. Conversely, the keyword analysis method exhibits a recognition quantity of four weak signals; in terms of recognition quality, the three-dimensional weak demand signal recognition model based on domain ontology can exclude non-demand signals such as “charging technology”, while keyword analysis methods cannot. Overall, the model proposed in this paper has higher sensitivity.

This paper proposes a novel method for identifying weak demand signals that considers the frequency of the signal's novelty, depth and relevance to the target demand. To verify its effectiveness, customer review data for new energy vehicles is used. The results provide a theoretical reference for formulating government policies and identifying weak demand signals for businesses.

This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

The purpose of this study is to solve the problem of path planning and path tracking in the automatic parking assistant system.

This paper first uses the method of reverse driving to confirm few control points based on the constraints of the construction of the vehicle and the environment information, then a reference path with free-collision and continuous curvature is designed based on the Bézier curve. According to the principle of the discrete linear quadratic regulator (LQR), a tracking controller that combines feedforward control and feedback control is designed.

Finally, simulation analysis are carried out in Simulink and CARSIM. The results show that the proposed method can obtain a better path tracking effect when the parking space size is appropriate.

According to the principle of the discrete LQR, a tracking controller that combines feedforward control and feedback control is designed.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.

This study aims investigate the status of applying technology in car parking facilities. It also examines the factors affecting the deployment of these technologies as they improve the efficiency and convenience of car parking facilities amidst changing transport needs in Asian smart cities.

A comprehensive literature review informs the relationships between car park provisions and the traffic congestion problem. A typology covering different technological solutions is then formulated. The factors affecting the use of two such common technologies (i.e. mechanical car parks and intelligent information systems) are examined in two emerging smart cities in Asia with the aid of a desk-top study for Singapore and a survey covering over 600 samples (including users and non-users, as both groups are important to derive influencing factors) in Hong Kong.

The extent to which mechanical car parks may help relieve the space shortage problem depends on their relative costs and the facility management performance. For real-time vacancy information systems, their wide spread use depends on drivers’ age and past parking experience.

Due to geographical constraints, only two Asian cities (Singapore and Hong Kong), where the use of smart technologies is flourishing, are included in the study. The survey on car parking apps is preliminary due to their relative short deployment in Asia. It is expected that the phenomena will quickly spread in the region as more smart cities are developed.

By expounding on the development of modern parking technologies in smart cities, the important influence of car parks as a strategic facility toward solving traffic congestion and environmental problems is brought to the attention of policy makers, in particular the influencing factors affecting strategies to promote the use of parking apps.

The purpose of this paper is to find a real-time parking location for a four-wheeler.

Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance cost, which is not affordable to all urban cities. The authors present statistical block matching algorithm (SBMA) for real-time parking management in small-town cities such as Bhavnagar using an in-built surveillance CCTV system, which is not installed for parking application. In particular, data from a camera situated in a mall was used to detect the parking status of some specific parking places using a region of interest (ROI). The method proposed computes the mean value of the pixels inside the ROI using blocks of different sizes (8 × 10 and 20 × 35), and the values were compared among different frames. When the difference between frames is more significant than a threshold, the process generates “no parking space for that place.” Otherwise, the method yields “parking place available.” Then, this information is used to print a bounding box on the parking places with the color green/red to show the availability of the parking place.

The real-time feedback loop (car parking positions) helps the presented model and dynamically refines the parking strategy and parking position to the users. A whole-day experiment/validation is shown in this paper, where the evaluation of the method is performed using pattern recognition metrics for classification: precision, recall and F1 score.

The authors found real-time parking availability for Himalaya Mall situated in Bhavnagar, Gujarat, for 18th June 2018 video using the SBMA method with accountable computational time for finding parking slots. The limitations of the presented method with future implementation are discussed at the end of this paper.

Older adults are increasingly being recognised as an important and growing consumer market, however they appear reticent in adopting new technologies. One contributing factor is that their needs are poorly understood by designers and products are thus poorly specified. Within the context of driving as a socially valuable skilled behaviour we applied a participatory design approach to engage with older people as valued partners in the design process.This article examines different strategies for involving older people as experts in their own domain, developing a better understanding of their needs and aspirations and empowering them within the design process. This research took account of new developments in car design and opportunities for intelligent driver assistance systems to support driver safety. The study found that older car drivers responded well to the opportunity to identify their needs and to evaluate prototypes and novel technologies. Their appraisal of these novel technologies particularly supported an improved understanding of the skilled behaviours of older drivers and of the mismatch between these and the technologies. When incorporated into the early stages of the design process, these evaluation activities offer important opportunities to enhance understanding of latent and implicit needs of older adults. In turn this can inform and refine design requirements.

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.

This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.

Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.

The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.

In 1990, a bill was enacted into federal law with the purpose of protecting people with disability from discrimination. Essentially it dictates that “no covered entity shall discriminate against a qualified individual with a disability because of the disability of such individual in regard to job application procedures, the hiring, advancement, or discharge of employees, employee compensation, job training, and other terms, conditions, and privileges of employment”. The employer must also “make reasonable accommodations to the known physical or mental limitations of an otherwise qualified individual with a disability who is an applicant or employee, unless covered entity can demonstrate that the accommodation would impose an undue hardship on the operation of the business”. The bill was aimed primarily at employers but also carries weight concerning public accommodations. All public buildings must reasonably accommodate handicapped individuals in respect to stairs, public transportation, entrances, water fountains, toilets, curbs, Automatic Teller Machines, parking and many, many other facilities. This does not even bring into account that there are thousands of other instances that have never been defined. In fact, the very definition of “disability” is extremely vague. On the surface the Americans with Disabilites Act does legitimately protect the general public from unfair discriminatory practices, but it opens another door in the long list of ways unethical people may take advantage of “the system”. In fact, many of the routes people follow to take advantage of the ADA can be equated to welfare fraud. Coupled with the fact that the United States is becoming a much more litigious society, the ADA is recognised by some as just another pathway to unearned income.