scholarly journals Sustainable Renewal Methods of Urban Public Parking Spaces under the Scenario of Shared Autonomous Vehicles (SAV): A Review and A Proposal

2021 ◽  
Vol 13 (7) ◽  
pp. 3629
Author(s):  
Bing Xia ◽  
Jindong Wu ◽  
Jiaqi Wang ◽  
Yitao Fang ◽  
Haodi Shen ◽  
...  
Keyword(s):  
Urban Space ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Reference Value ◽  
Urban Morphology ◽  
Policy Implications ◽  
Parking Space ◽  
Demand Forecast ◽  
Operation Rate ◽  
Series Evaluation

Shared autonomous vehicles (SAVs) will be an important force to in reshaping urban morphology. The high operation rate and sharing degree of SAV are considered to result in a great reduction in parking area in future cities. Parking space is now a huge and widely distributed urban stock space type, which is bound to become a major challenge and opportunity for sustainable urban renewal in the digital era. Based on the SAV scenario, this paper reviews the current research on the sustainable renewal of urban public parking spaces, and proposes the four key issues involved: how much to renew (i.e., demand forecast analysis), when to renew (i.e., update time series evaluation), what to renew (i.e., function replacement decision) and how to update (i.e., design empirical research). Furthermore, it puts forward a preliminary idea on, and constructs a research framework for, the sustainable renewal methods of parking space under the SAV scenario. Finally, the theoretical, practical and policy implications of the research on sustainable renewal methods of urban public parking space are discussed. It will have great reference value for the redevelopment and reuse of the urban space types including fragmented, widely distributed and large-scale.

scholarly journals Sustainable Renewal of Underground Parking Space in the Scenario of Shared Autonomous Vehicles

Buildings ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 4
Author(s):  
Bing Xia ◽  
Yitao Fang ◽  
Haodi Shen ◽  
Jinli Shen ◽  
Shengzhang Pan
Keyword(s):  
Urban Space ◽  
Autonomous Vehicles ◽  
Evaluation Method ◽  
Parking Space ◽  
Design Strategies ◽  
Urban Centers ◽  
Future Design ◽  
Series Evaluation ◽  
Form Features ◽  
And Function

Shared autonomous vehicles (SAVs) are a major development direction in international scientific and technological innovation. One of the most popular features of SAVs in the urban space is that they can significantly reduce the need for parking. The urban underground parking space (UPS) is currently the largest static traffic space, especially in high-density urban centers. Under the SAV scenario, the need for the renewal of UPS will increase in the near future. However, renewal of the UPS is difficult due to its special form features, which are greatly restricted by the external environment, thus necessitating targeted methods and strategies. This research first conducted field investigations and data collection on the spatial morphology and service conditions of typical UPSs in different areas of Hangzhou city. Based on the driver status response and the multi-objective attribute models, the time-series evaluation method and function replacement decision model for the sustainable renewal of underground parking were established. The research also discusses appropriate design strategies for the combination of spatial characteristics and functional replacement goals of typical samples. The conclusions will provide scientific guidance for the future design practice of architects and urban designers in SAV.

scholarly journals Parking Line Based SLAM Approach Using AVM/LiDAR Sensor Fusion for Rapid and Accurate Loop Closing and Parking Space Detection

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4811 ◽  
Author(s):  
Gyubeom Im ◽  
Minsung Kim ◽  
Jaeheung Park
Keyword(s):  
Real Time ◽  
Sensor Fusion ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Outdoor Environment ◽  
Parking Space ◽  
Parking Space Detection ◽  
Localization Performance ◽  
Line Features ◽  
Loop Closing

Parking is a challenging task for autonomous vehicles and requires a centimeter level precision of distance measurement for safe parking at a destination to avoid collisions with nearby vehicles. In order to avoid collisions with parked vehicles while parking, real-time localization performance should be maintained even when loop closing occurs. This study proposes a simultaneous localization and mapping (SLAM) method, using around view monitor (AVM)/light detection and ranging (LiDAR) sensor fusion, that provides rapid loop closing performance. We extract the parking line features by utilizing the sensor fusion data for sparse feature-based pose graph optimization that boosts the loop closing speed. Hence, the proposed method can perform the loop closing within a few milliseconds to compensate for the accumulative errors even in a large-scale outdoor environment, which is much faster than other LiDAR-based SLAM algorithms. Therefore, it easily satisfies real-time localization performance. Furthermore, thanks to the parking line features, the proposed method can detect a parking space by utilizing the accumulated parking lines in the map. The experiment was performed in three outdoor parking lots to validate the localization performance and parking space detection performance. All of the proposed methods can be operated in real-time in a single-CPU environment.

scholarly journals Impact of the municipal merger on watershed management: a study of Lake Kasumigaura, Japan

2021 ◽  
Author(s):  
Takeshi Mizunoya ◽  
Noriko Nozaki ◽  
Rajeev Kumar Singh
Keyword(s):  
Watershed Management ◽  
Large Scale ◽  
Environmental Changes ◽  
Water Environment ◽  
Reduction Rate ◽  
Oxygen Demand ◽  
Policy Implications ◽  
Pollution Reduction ◽  
Lake Kasumigaura ◽  
The Impact

AbstractIn the early 2000s, Japan instituted the Great Heisei Consolidation, a national strategy to promote large-scale municipal mergers. This study analyzes the impact that this strategy could have on watershed management. We select the Lake Kasumigaura Basin, the second largest lake in Japan, for the case study and construct a dynamic expanded input–output model to simulate the ecological system around the Lake, the socio-environmental changes over the period, and their mutual dependency for the period 2012–2020. In the model, we regulate and control the following water pollutants: total nitrogen, total phosphorus, and chemical oxygen demand. The results show that a trade-off between economic activity and the environment can be avoided within a specific range of pollution reduction, given that the prefectural government implements optimal water environment policies, assuming that other factors constraining economic growth exist. Additionally, municipal mergers are found to significantly reduce the budget required to improve the water environment, but merger budget efficiency varies nonlinearly with the reduction rate. Furthermore, despite the increase in financial efficiency from the merger, the efficiency of installing domestic wastewater treatment systems decreases drastically beyond a certain pollution reduction level and eventually reaches a limit. Further reductions require direct regulatory instruments in addition to economic policies, along with limiting the output of each industry. Most studies on municipal mergers apply a political, administrative, or financial perspective; few evaluate the quantitative impact of municipal mergers on the environment and environmental policy implications. This study addresses these gaps.

scholarly journals Automated Parking Space Allocation during Transition with both Human-Operated and Autonomous Vehicles

2021 ◽  
Vol 11 (2) ◽  
pp. 855
Author(s):  
Mingkang Wu ◽  
Haobin Jiang ◽  
Chin-An Tan
Keyword(s):  
Autonomous Vehicles ◽  
Transition Period ◽  
Search Algorithm ◽  
Parking Space ◽  
Key Factors ◽  
Comprehensive Method ◽  
Space Allocation ◽  
Shortest Distance ◽  
Parking Lot ◽  
Ranking Order

As fully automated valet parking systems are being developed, there is a transition period during which both human-operated vehicles (HVs) and autonomous vehicles (AVs) are present in the same parking infrastructure. This paper addresses the problem of allocation of a parking space to an AV without conflicting with the parking space chosen by the driver of a HV. A comprehensive assessment of the key factors that affect the preference and choice of a driver for a parking space is established by the fuzzy comprehensive method. The algorithm then generates a ranking order of the available parking spaces to first predict the driver’s choice of parking space and then allocate a space for the AV. The Floyd algorithm of shortest distance is used to determine the route for the AV to reach its parking space. The proposed allocation and search algorithm is applied to the examples of a parking lot with three designed scenarios. It is shown that parking space can be reasonably allocated for AVs.

What determines a boundary for navigating a complex street network: evidence from London taxi drivers

2021 ◽  
pp. 1-20
Author(s):  
Eva-Maria Griesbauer ◽  
Ed Manley ◽  
Daniel McNamee ◽  
Jeremy Morley ◽  
Hugo Spiers
Keyword(s):  
Urban Space ◽  
Large Scale ◽  
Route Planning ◽  
Taxi Drivers ◽  
Street Networks ◽  
Planning Models ◽  
Key Factor ◽  
Efficient Planning ◽  
Regent's Park ◽  
Insight Into

Abstract Spatial boundaries play an important role in defining spaces, structuring memory and supporting planning during navigation. Recent models of hierarchical route planning use boundaries to plan efficiently first across regions and then within regions. However, it remains unclear which structures (e.g. parks, rivers, major streets, etc.) will form salient boundaries in real-world cities. This study tested licensed London taxi drivers, who are unique in their ability to navigate London flexibly without physical navigation aids. They were asked to indicate streets they considered as boundaries for London districts or dividing areas. It was found that agreement on boundary streets varied considerably, from some boundaries providing almost no consensus to some boundaries consistently noted as boundaries. Examining the properties of the streets revealed that a key factor in the consistent boundaries was the near rectilinear nature of the designated region (e.g. Mayfair and Soho) and the distinctiveness of parks (e.g. Regent's Park). Surprisingly, the River Thames was not consistently considered as a boundary. These findings provide insight into types of environmental features that lead to the perception of explicit boundaries in large-scale urban space. Because route planning models assume that boundaries are used to segregate the space for efficient planning, these results help make predictions of the likely planning demands of different routes in such complex large-scale street networks. Such predictions could be used to highlight information used for navigation guidance applications to enable more efficient hierarchical planning and learning of large-scale environments.

Different firm responses to the COVID-19 pandemic shocks: machine-learning evidence on the Vietnamese labor market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lam Hoang Viet Le ◽  
Toan Luu Duc Huynh ◽  
Bryan S. Weber ◽  
Bao Khac Quoc Nguyen
Keyword(s):  
Machine Learning ◽  
Labor Market ◽  
Large Scale ◽  
Government Support ◽  
Policy Implications ◽  
Machine Learning Techniques ◽  
Firm Characteristics ◽  
Data Set ◽  
Content Type ◽  
Firm Responses

PurposeThis paper aims to identify the disproportionate impacts of the COVID-19 pandemic on labor markets.Design/methodology/approachThe authors conduct a large-scale survey on 16,000 firms from 82 industries in Ho Chi Minh City, Vietnam, and analyze the data set by using different machine-learning methods.FindingsFirst, job loss and reduction in state-owned enterprises have been significantly larger than in other types of organizations. Second, employees of foreign direct investment enterprises suffer a significantly lower labor income than those of other groups. Third, the adverse effects of the COVID-19 pandemic on the labor market are heterogeneous across industries and geographies. Finally, firms with high revenue in 2019 are more likely to adopt preventive measures, including the reduction of labor forces. The authors also find a significant correlation between firms' revenue and labor reduction as traditional econometrics and machine-learning techniques suggest.Originality/valueThis study has two main policy implications. First, although government support through taxes has been provided, the authors highlight evidence that there may be some additional benefit from targeting firms that have characteristics associated with layoffs or other negative labor responses. Second, the authors provide information that shows which firm characteristics are associated with particular labor market responses such as layoffs, which may help target stimulus packages. Although the COVID-19 pandemic affects most industries and occupations, heterogeneous firm responses suggest that there could be several varieties of targeted policies-targeting firms that are likely to reduce labor forces or firms likely to face reduced revenue. In this paper, the authors outline several industries and firm characteristics which appear to more directly be reducing employee counts or having negative labor responses which may lead to more cost–effect stimulus.

scholarly journals Disorder or Reorder? The Spatial Production of State-Level New Areas in China

2018 ◽  
Vol 10 (10) ◽  
pp. 3628 ◽  
Author(s):  
Liang Zhuang ◽  
Chao Ye
Keyword(s):  
Urban Space ◽  
Large Scale ◽  
Regional Distribution ◽  
State Level ◽  
Growth Spurt ◽  
Rapid Urbanization ◽  
New Town ◽  
Spatial Production ◽  
Expansion Pattern ◽  
Reform And Opening Up

With rapid urbanization in the world, new town construction has become prosperous. In particular, new emerging towns in China are unique because of the most significant movement of “building cities”. Over four decades of reform and opening-up, this movement has brought about a special development model known as State-level New Area (SLNA) which, like a new town, is causing a growth spurt in national and regional economic development. By applying the critical theory of production of space, this paper gives an overall analysis. SLNAs generate a new expansion pattern of urban space in the regionalization process dominated by governments. To reveal the spatiotemporal evolution logic of SLNA, the framework identifies the main characteristics contributing to spatial production: both bottom-up and top-down project on construction; a sharp and unordered trend of increment in time scale; an unbalanced regional distribution in the sequential order of “Eastern–Western–Northeastern–Central” among regions; complex spatial overlaying with different development zones and administrative divisions; and large-scale spatial expanding. This paper finds that the ongoing growth of SLNAs is a rapid process of spatial production with more contradictions, which is especially marked by tension between disorder and reorder. We hope to provide theoretical reference and practical guidance for the sustainable urbanization and orderly regional development of SLNAs.

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