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Update-efficient indexing of moving objects in road networks

GEOINFORMATICA 2009年第4期13卷 397-424页

作者： Chen, Jidong Meng, Xiaofeng Renmin Univ China Sch Informat Beijing Peoples R China MOE Key Lab Data Engn & Knowledge Engn Beijing Peoples R China

Recent advances in wireless sensor networks and positioning technologies have boosted new applications that manage moving objects. In such applications, a dynamic index is often built to expedite evaluation of spatial queries. However, the development of efficient indexes is a challenge due to frequent object movement. In this paper, we propose a new update-efficient index method for moving objects in road networks. We introduce a dynamic data structure, called adaptive unit, to group neighboring objects with similar movement patterns. To reduce updates, an adaptive unit captures the movement bounds of the objects based on a prediction method, which considers road-network constraints and the stochastic traffic behavior. A spatial index (e.g., R-tree) for the road network is then built over the adaptive unit structures. Simulation experiments, carried on two different datasets, show that an adaptive-unit based index is efficient for both updating and querying performances.

关键词： Spatial-temporal databases Moving objects Index structure road networks

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ExTCKNN: Expanding Tree-Based Continuous K Nearest Neighbor Query in road networks With Traffic Rules

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IEEE ACCESS 2018年 6卷 72594-72608页

作者： Li, Hongjun Cai, Biao Qiao, Shaojie Wang, Qing Wang, Yan Chengdu Univ Technol Sch Informat Sci & Technol Chengdu 610059 Sichuan Peoples R China Chengdu Univ Informat Technol Sch Cybersecur Chengdu 610225 Sichuan Peoples R China Florida Int Univ Sch Comp Sci Miami FL 33199 USA East China Jiaotong Univ Sch Software Nanchang 330013 Jiangxi Peoples R China

The existing continuous nearest neighbor query algorithms of moving objects in road networks do not consider any traffic rule and assume that the speed of moving objects is constant and the topology of road networks never change. However, in real road networks, the object's speed and the road network's structure change frequently Hence, these would make the existing methods ineffective when applying to the real-world road network environment To overcome the aforementioned disadvantages, we propose a Data Modeling approach of road networks with traffic rules (called DMRNR) and design a novel Expanding Tree-based Continuous k Nearest Neighbors algorithm (abbreviate for ExTCKNN) that can be well adopted to the actual road network environment. The algorithm consists of three steps: 1) it obtains the query results to store using DMRNR in the initial phase;2) it maintains the data model of road networks by monitoring the real-time change information;and 3) the results are generated according to the submitted query with the updated data model and the latest state of moving objects The merit of the proposed algorithm lies in that it queries the nearest neighbors by taking the movements of the moving object and the variety of the road networks into consideration Extensive experiments are conducted and the experimental results demonstrate a significant improvement of the proposed method when compared with conventional solutions.

关键词： road networks k nearest neighbor continuous query expanding tree data model of road network

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Identifying critical links on disruption-prone road networks: an approach that obviates scenario enumeration

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CURRENT SCIENCE 2020年第3期118卷 428-438页

作者： Patil, Gopal R. Bhavathrathan, B. K. Indian Inst Technol Dept Civil Engn Mumbai 400076 Maharashtra India Indian Inst Technol Palakkad Dept Civil Engn Palakkad 678557 India

road networks are susceptible to disruptions. Since disruptions on certain roads have graver impacts, critical link identification is vital in disruption preparedness. To identify critical links, most approaches systematically inject disruptions and evaluate the ensuing after-effects. Since degradation patterns are uncertain, such iterative approaches either presume knowledge of disruption patterns or try numerous patterns but soon escalate to computational impracticality on real-life road networks. This study obviates both, using a novel approach which measures the contribution of each link to a predefined operational limit on the network. It generates a criticality hierarchy on real-life networks, while on hypothetical symmetric networks it rightly identifies all links as critical.

关键词： Critical links disruptions minimax optimization road networks scenario enumeration

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Safest Nearby Neighbor Queries in road networks

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第7期24卷 7270-7284页

作者： Biswas, Punam Hashem, Tanzima Cheema, Muhammad Aamir Bangladesh Univ Engn & Technol Dept Comp Sci & Engn Dhaka 1205 Bangladesh Monash Univ Fac Informat Technol Melbourne Vic 3168 Australia

Safety on the roads has become a major concern in recent days. Travellers prefer to avoid road inconveniences that may occur from crime incidents, street harassment, protests or riots during unrest in a country. To facilitate safe travel, we introduce a novel query for road networks called the k safest nearby neighbor (SNN) query. Given a query location vl, a distance constraint dc and a point of interest pi, we define the safest path from vl to pi as the path with the highest path safety score among all the paths from vl to pi with length less than dc. The path safety score is computed considering the road safety of each road segment on the path. Given a query location vl, a distance constraint dc and a set of POIs P, a kSNN query returns k POIs with the k highest path safety scores in P along with their respective safest paths from the query location. We develop two novel indexing structures called Ct-tree and a safety score based Voronoi diagram (SNVD). We propose two efficient query processing algorithms each exploiting one of the proposed indexes to effectively refine the search space using the properties of the index. Our extensive experimental study on real datasets demonstrates that our solution is on average an order of magnitude faster than the baseline.

关键词： Ct-tree road networks safest nearby neighbor safest path Voronoi diagram

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Discovering historic traffic-tolerant paths in road networks

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GEOINFORMATICA 2017年第1期21卷 1-32页

作者： Li, Pui Hang Yiu, Man Lung Mouratidis, Kyriakos Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Singapore Management Univ Sch Informat Syst Singapore Singapore

Historic traffic information is valuable in transportation analysis and planning, e.g., evaluating the reliability of routes for representative source-destination pairs. Also, it can be utilized to provide efficient and effective route-search services. In view of these applications, we propose the k traffic-tolerant paths (TTP) problem on road networks, which takes a source-destination pair and historic traffic information as input, and returns k paths that minimize the aggregate (historic) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to find. First, we propose an exact algorithm with effective pruning rules to reduce the search time. Second, we develop an anytime heuristic algorithm that makes 'best-effort' to find a low-cost solution within a given time limit. Extensive experiments on real and synthetic traffic data demonstrate the effectiveness of TTP and the efficiency of our proposed algorithms.

关键词： road networks road traffic

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A LANDIS-II extension for simulating forest road networks

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CANADIAN JOURNAL OF FOREST RESEARCH 2023年第7期53卷 503-518页

作者： Hardy, Clement Messier, Christian Valeria, Osvaldo Filotas, Elise Univ Quebec Dept Sci Biol 141 Ave President Kennedy Montreal PQ H2X 1Y4 Canada Univ Quebec Ctr Etud Foret 141 Ave President Kennedy Montreal PQ H2X 1Y4 Canada Univ Quebec TELUQ Ctr Forest Res 5800 Rue St Denis Montreal PQ H2S 3L5 Canada Univ Quebec TELUQ Data Sci Lab 5800 Rue St Denis Montreal PQ H2S 3L5 Canada Univ Quebec Outaouais Dept Sci Nat 58 Rue Principale Ripon PQ J0V 1V0 Canada Univ Quebec Outaouais Inst Sci Foret Temperee ISFORT 58 Rue Principale Ripon PQ J0V 1V0 Canada Univ Quebec Abitibi Temiscamingue Inst Rech Forets Boul Univ Rouyn Noranda PQ J9X 5E4 Canada Univ Quebec Abitibi Temiscamingue Ctr Etud Foret Boul Univ Rouyn Noranda PQ J9X 5E4 Canada Univ Mayor Escuela Ingn Forestal Fac Ciencias Hemera Ctr Observac Tierra Camino Piramide 5750 Santiago Chile

Forest roads are an important part of forest management, both in terms of cost and impact on surrounding ecosystems. Existing tools to simulate the construction of forest roads have been designed for tactical or operational planning purposes, for relatively small areas (<10 000 ha) and small-scale topographic information. Hence, no forest road simulation tool properly exists to assist forest landscape ecology and management research. Here, we present the Forest roads Simulation (FRS) extension for the LANDIS-II model--a spatially explicit landscape simulation model of forest succession and disturbances. The FRS extension simulates forest road networks via a least-cost path algorithm accounting for landscape structure, decision inputs, and forest road types. We demonstrate the accuracy with which the FRS extension reproduces several key characteristics of existing road networks in two managed regions in Quebec, Canada: road density, road position, and fragmentation of the landscape. The FRS extension is easy to parameterize, proposing many options for researchers to simulate forest road networks at a strategic level in managed landscapes. It can tackle new research questions investigating the effects of forest roads within management strategies, such as the cost of road construction and habitat fragmentation, across large management units and long planning horizons.

关键词： LANDIS-II forest roads road networks forestry spatially explicit modeling forest ecology

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Efficient Path Routing Over road networks in the Presence of Ad-Hoc Obstacles

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INFORMATION SYSTEMS 2020年 88卷

作者： Al-Baghdadi, Ahmed Lian, Xiang Cheng, En Kent State Univ Dept Comp Sci Kent OH 44242 USA Educ Al Qadisiyah Al Diwaniyah 58001 Iraq Univ Akron Dept Comp Sci Akron OH 44325 USA

Nowadays, the path routing over road networks has become increasingly important, yet challenging, in many real-world applications such as location-based services (LBS), logistics and supply chain management, transportation systems, map utilities, and so on. While many prior works aimed to find a path between a source and a destination with the smallest traveling distance/time, they do not take into account the quality constraints (e.g., obstacles) of the returned paths, such as uneven roads, roads under construction, and weather conditions on roads. Inspired by this, in this paper, we consider two types of ad-hoc obstacles, keyword-based and weather-based obstacles, on road networks, which can be used for modeling roads that the returned paths should not pass through. In the presence of such ad-hoc obstacles on roads, we formulate a path routing query over road networks with ad-hoc obstacles (PRAO), which retrieves paths from source to destination on road networks that do not pass ad-hoc keyword and weather obstacles and have the smallest traveling time. In order to efficiently answer PRAO queries, we design effective pruning methods and indexing mechanism to facilitate efficient PRAO query answering. Extensive experiments have demonstrated the efficiency and effectiveness of our approaches over real/synthetic data sets. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Ad-hoc weather-based obstacles Ad-hoc keyword-based obstacles road networks Path routing query over road networks with ad-hoc obstacles

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Hybrid spatial air index for processing queries in road networks

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CLUSTER COMPUTING-THE JOURNAL OF networks SOFTWARE TOOLS AND APPLICATIONS 2018年第1期21卷 149-161页

作者： Veeresha, M. Sugumaran, M. Pondicherry Engn Coll Dept Comp Sci & Engn Pondicherry India

In case of road networks, for the clients to disseminate data, wireless broadcast is a scalable and secure strategy. As far as network partition index (NPI) is concerned, it doesn't address certain problems;as to how to handle if there has been a large number of data objects in broadcast system, in the same way how to handle link errors and cache management. Hence, to address such problems, hybrid spatial air index (HSAI) an NPI based air index has been proposed wherein hybrid broadcast scheduling, adaptive XOR-based network coding and adaptive cooperative caching are effectively used for spatial queries in road networks. Experiments are conducted for evaluating query performance and HSAI is compared with state-of-the-art NPI. The experimental results show the outperformance of HSAI.

关键词： Hybrid spatial air index Network partition index Hybrid broadcast scheduling Adaptive XOR-based network coding Adaptive cooperative caching road networks

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Multiple domination models for placement of electric vehicle charging stations in road networks

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COMPUTERS & OPERATIONS RESEARCH 2018年 96卷 69-79页

作者： Gagarin, Andrei Corcoran, Padraig Cardiff Univ Sch Math 21-23 Senghennydd Rd Cardiff CF24 4AG S Glam Wales Cardiff Univ Sch Comp Sci & Informat Queens Bldg5 Parade Cardiff CF24 3AA S Glam Wales

Electric and hybrid vehicles play an increasing role in road transport networks. Despite their advantages, they have a relatively limited cruising range in comparison to traditional diesel/petrol vehicles, and require significant battery charging time. We propose to model the facility location problem of the placement of charging stations in road networks as a multiple domination problem on reachability graphs. This model takes into consideration natural assumptions such as a threshold for remaining battery charge, and provides some minimal choice for a travel direction to recharge the battery. Experimental evaluation and simulations for the proposed facility location model are presented in the case of real road networks corresponding to the cities of Boston and Dublin. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： road networks Electric vehicles Facility location problem k-Domination alpha-Domination Heuristic optimization

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A Graph Deep Learning-Based Fast Traffic Flow Prediction Method in Urban road networks

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IEEE ACCESS 2023年 11卷 93754-93763页

作者： Yang, Dongfang Lv, Liping Zhengzhou Shengda Univ Sch Informat Engn Zhengzhou 451191 Peoples R China

In modern smart cities, road networks are becoming more and more complicated, resulting in more complex format of graphs. This brings many challenges to the forecasting of traffic flow in road graphs. Most of traditional traffic flow forecasting methods ignored many implicit relationships inside road graphs. And this cannot be well suitable for modern road networks in smart cities. Besides, the operation of smart cities is accompanied with real-time big data stream. The running efficiency of forecasting methods is another important concern. To handle this issue, this paper proposes a graph deep learning-based fast traffic flow forecasting method in urban road networks. Firstly, the theory about graph convolution operations is deduced and can be used as the basis of a graph convolution network (GCN). Then, the whole road network is viewed as a complex road graph, and the GCN is introduced to establish a novel forecasting method for graph-level traffic flow. With roads being regarded as nodes and their relations being regarded as edges, graph-level forecasting can be realized with the use of the proposed method. Experiments are carried out on a standard real dataset to evaluate the proposal. The experimental results show a proper performance of the proposal.

关键词： Graph deep learning road traffic prediction fast prediction traffic flow road networks

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