A Study of Pre-Processing Technique for Map-Matching Schemes of GPS-Enabled Vehicles

doi:10.12785/IJCDS/060104

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A Study of Pre-Processing Technique for Map-Matching Schemes of GPS-Enabled Vehicles

Journal Article•DOI•

A Study of Pre-Processing Technique for Map-Matching Schemes of GPS-Enabled Vehicles

Aftab Ahmed Chandio, Fan Zhang, Zubair Ahmed Kalhoro, Imtiaz Ali Korejo, Muhammad Saleem Chandio - Show less +1 more

01 Jan 2017-International Journal of Computing (University of Bahrain)-Vol. 6, Iss: 1, pp 37-44

TL;DR: The pre-processing technique is introduced; the road network graph and processing the Single Source Shortest Path in synchronize parallel processing in the Hadoop environment enables the map-matching schemes efficient to align the GPS points on the digital road networks.

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Abstract: This study towards the Map-Matching process that is useful to align a location of Global Positioning System (GPS) of vehicles on the digital road networks. Today’s GPS-enabled vehicles in developed countries generate a big volume of GPS data. On the other hand, the development of new roads in the city enables the road network very complex and difficult to match the vehicles’ location. So therefore, different techniques (i.e., pre-processing techniques) may be applied before the map-matching process is a recent concern of the Intelligent Transport System (ITS) research community. In this paper, we introduce the pre-processing technique; splitting the road network graph and processing the Single Source Shortest Path (SSSP) in synchronize parallel processing in the Hadoop environment. The proposed technique enables the map-matching schemes efficient to align the GPS points on the digital road networks. In the experimental work, the results of the map-matching schemes (i.e., found in the literature review) incorporated with our proposed pre-processing technique shows better performance in aspect to the response time.

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Journal Article•DOI•

Augmenting Neural Machine Translation through Round-Trip Training Approach

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Benyamin Ahmadnia¹, Bonnie J. Dorr²•Institutions (2)

Tulane University¹, Florida Institute for Human and Machine Cognition²

11 Oct 2019

TL;DR: A round-trip training approach to bilingual low-resource NMT that takes advantage of monolingual datasets to address training data bottleneck, thus augmenting translation quality and outperforms the baseline systems and improves translation quality.

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Abstract: Abstract The quality of Neural Machine Translation (NMT), as a data-driven approach, massively depends on quantity, quality and relevance of the training dataset. Such approaches have achieved promising results for bilingually high-resource scenarios but are inadequate for low-resource conditions. Generally, the NMT systems learn from millions of words from bilingual training dataset. However, human labeling process is very costly and time consuming. In this paper, we describe a round-trip training approach to bilingual low-resource NMT that takes advantage of monolingual datasets to address training data bottleneck, thus augmenting translation quality. We conduct detailed experiments on English-Spanish as a high-resource language pair as well as Persian-Spanish as a low-resource language pair. Experimental results show that this competitive approach outperforms the baseline systems and improves translation quality.

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23 citations

Journal Article•DOI•

Map matching based on multi-layer road index

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Zhouhao Wu¹, Jun Xie², Yuanqing Wang¹, Yu (Marco) Nie³•Institutions (3)

Chang'an University¹, Southwest Jiaotong University², Northwestern University³

01 Sep 2020-Transportation Research Part C-emerging Technologies

TL;DR: Numerical experiments show the proposed algorithm improves match efficiency by up to two order of magnitude compared to the benchmark algorithms, and achieves this remarkable speedup with negligible losses in matching accuracy.

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Abstract: This study develops a new map matching algorithm targeting off-line applications. The algorithm takes a holistic view of the entire GPS trajectory and finds its match by first dividing it into several segments. This segmentation is made possible through creating a multi-layer road index system for the original road network. For each segment, a global map matching strategy is employed to identify the best match. The algorithm is compared against three state-of-the-art map matching algorithms from the literature. To get ground truth data, we design and perform numerous test drives with predefined paths that have a total length of 234 km. GPS trajectories recorded during the test drives are used to evaluate the algorithms. Our numerical experiments show the proposed algorithm improves match efficiency by up to two order of magnitude compared to the benchmark algorithms. Importantly, it achieves this remarkable speedup with negligible losses in matching accuracy.

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16 citations

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Journal Article•DOI•

A note on two problems in connexion with graphs

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Edsger W. Dijkstra

01 Dec 1959-Numerische Mathematik

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.

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Abstract: We consider n points (nodes), some or all pairs of which are connected by a branch; the length of each branch is given. We restrict ourselves to the case where at least one path exists between any two nodes. We now consider two problems. Problem 1. Constrnct the tree of minimum total length between the n nodes. (A tree is a graph with one and only one path between every two nodes.) In the course of the construction that we present here, the branches are subdivided into three sets: I. the branches definitely assignec~ to the tree under construction (they will form a subtree) ; II. the branches from which the next branch to be added to set I, will be selected ; III. the remaining branches (rejected or not yet considered). The nodes are subdivided into two sets: A. the nodes connected by the branches of set I, B. the remaining nodes (one and only one branch of set II will lead to each of these nodes), We start the construction by choosing an arbitrary node as the only member of set A, and by placing all branches that end in this node in set II. To start with, set I is empty. From then onwards we perform the following two steps repeatedly. Step 1. The shortest branch of set II is removed from this set and added to

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22,704 citations

Proceedings Article•DOI•

Pregel: a system for large-scale graph processing

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Grzegorz Malewicz, Matthew H. Austern¹, Aart J. C. Bik¹, James C. Dehnert¹, Ilan Horn¹, Naty Leiser¹, Grzegorz Czajkowski¹ - Show less +3 more•Institutions (1)

Google¹

06 Jun 2010

TL;DR: A model for processing large graphs that has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier.

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Abstract: Many practical computing problems concern large graphs. Standard examples include the Web graph and various social networks. The scale of these graphs - in some cases billions of vertices, trillions of edges - poses challenges to their efficient processing. In this paper we present a computational model suitable for this task. Programs are expressed as a sequence of iterations, in each of which a vertex can receive messages sent in the previous iteration, send messages to other vertices, and modify its own state and that of its outgoing edges or mutate graph topology. This vertex-centric approach is flexible enough to express a broad set of algorithms. The model has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier. Distribution-related details are hidden behind an abstract API. The result is a framework for processing large graphs that is expressive and easy to program.

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3,840 citations

"A Study of Pre-Processing Technique..." refers methods in this paper

...Specifically, BSP [16-18] parallel computing paradigm implemented in HAMA [19] graph processing tool is selected to process SSSP function....
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...Specifically, BSP [16-18] parallel computing paradigm implemented in HAMA [19] graph processing tool is selected to process SSSP function....
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...The complete pseudo-code of the modified SSSP function approaching BSP parallel model is clearly explained in our previous work [15]....
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...In this paper, we used our modified SSSP function approaching BSP parallel computing model proposed in our previous work [15]....
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...NOMENCLATURE Notation Description SPQ Shortest Path Query BSP Bulk Synchronous Parallel 𝐺(𝑉, 𝐸) A digital road network graph 𝑉 Vertexes of a graph 𝐸 Edges of a graph 𝐾 A number of sub-graphs (𝐺𝐾) 𝑘 A given number required for partitions 𝑚𝑖𝑛𝐶 and 𝑚𝑎𝑥𝐶 Smallest (minimum) and largest (maximum) value of graph’s coordination (i.e., longitude and latitude) 𝑣 Total number of vertexes in a graph 𝑝𝑎𝑟𝑡𝑖𝑎𝑙𝐶 Partial coordination of a partition 𝑇𝐻 Threshold value to adjust the partition coordination 𝑎𝑝𝑝𝑟𝑜𝑥𝑉 Approximate number of vertexes in a partition 𝑡𝑜𝑡𝑎𝑙𝑉 Total number of vertexes counted into the space covered 𝑚𝑖𝑛𝐶 and 𝑚𝑎𝑥𝐶 coordination of the partition 𝑙𝑜𝑤𝐶and ℎ𝑖𝑔ℎ𝐶 Coordinate values used for extra space covered in order to connect the neighbor partition. http://journals.uob.edu.bh Specifically, this algorithm takes an input of a road network graph 𝐺(𝑉, 𝐸) and a number 𝑘 which is given for producing 𝐾 number of partitions formulated in subgraphs....
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Proceedings Article•DOI•

Map-matching for low-sampling-rate GPS trajectories

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Yin Lou¹, Chengyang Zhang¹, Yu Zheng¹, Xing Xie¹, Wei Wang², Yan Huang³ - Show less +2 more•Institutions (3)

Microsoft¹, Fudan University², University of North Texas³

04 Nov 2009

TL;DR: The results show that the ST-matching algorithm significantly outperform incremental algorithm in terms of matching accuracy for low-sampling trajectories and when compared with AFD-based global algorithm, ST-Matching also improves accuracy as well as running time.

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Abstract: Map-matching is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental pre-processing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount of low-sampling-rate (e.g., one point every 2--5 minutes) GPS trajectories. Unfortunately, most current map-matching approaches only deal with high-sampling-rate (typically one point every 10--30s) GPS data, and become less effective for low-sampling-rate points as the uncertainty in data increases. In this paper, we propose a novel global map-matching algorithm called ST-Matching for low-sampling-rate GPS trajectories. ST-Matching considers (1) the spatial geometric and topological structures of the road network and (2) the temporal/speed constraints of the trajectories. Based on spatio-temporal analysis, a candidate graph is constructed from which the best matching path sequence is identified. We compare ST-Matching with the incremental algorithm and Average-Frechet-Distance (AFD) based global map-matching algorithm. The experiments are performed both on synthetic and real dataset. The results show that our ST-matching algorithm significantly outperform incremental algorithm in terms of matching accuracy for low-sampling trajectories. Meanwhile, when compared with AFD-based global algorithm, ST-Matching also improves accuracy as well as running time.

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817 citations

"A Study of Pre-Processing Technique..." refers background or methods in this paper

...The ST-MM [1] and LB-MM [8] map-matching schemes are considered to evaluate the proposed pre-processing technique....
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..., Spatial and Temporal MapMatching, STMM [1] and Location-Based MapMatching, LB-MM [8] found in the literature review) providing better performance in aspect to overall response time with slightly effects on the accuracy....
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...We further evaluate our pre-processing technique by incorporating with map-matching schemes, i.e., ST-MMU and LB-MM-U....
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...(b) In the experimental work, the proposed pre-processing technique is incorporated with the map-matching schemes (i.e., Spatial and Temporal MapMatching, STMM [1] and Location-Based MapMatching, LB-MM [8] found in the literature review) providing better performance in aspect to overall response time with slightly effects on the accuracy....
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...A fundamental pre-process and useful service in Location-Based Services (LBS) is a map-matching process [1]....
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Proceedings Article•

On map-matching vehicle tracking data

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Sotiris Brakatsoulas¹, Dieter Pfoser¹, Randall Salas², Carola Wenk²•Institutions (2)

Research Academic Computer Technology Institute¹, University of Texas at San Antonio²

30 Aug 2005

TL;DR: This work presents three algorithms that consider especially the trajectory nature of the data rather than simply the current position as in the typical map-matching case, and proposes an incremental algorithm that matches consecutive portions of the trajectory to the road network.

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Abstract: Vehicle tracking data is an essential "raw" material for a broad range of applications such as traffic management and control, routing, and navigation. An important issue with this data is its accuracy. The method of sampling vehicular movement using GPS is affected by two error sources and consequently produces inaccurate trajectory data. To become useful, the data has to be related to the underlying road network by means of map matching algorithms. We present three such algorithms that consider especially the trajectory nature of the data rather than simply the current position as in the typical map-matching case. An incremental algorithm is proposed that matches consecutive portions of the trajectory to the road network, effectively trading accuracy for speed of computation. In contrast, the two global algorithms compare the entire trajectory to candidate paths in the road network. The algorithms are evaluated in terms of (i) their running time and (ii) the quality of their matching result. Two novel quality measures utilizing the Frechet distance are introduced and subsequently used in an experimental evaluation to assess the quality of matching real tracking data to a road network.

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633 citations

"A Study of Pre-Processing Technique..." refers methods in this paper

...More specifically, the map-matching process is categorized into three categories: (a) local or incremental method [2, 3], (b) global method [1] [4, 5] and (c) statistical method [6, 7]....
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Book Chapter•DOI•

Voronoi-based K nearest neighbor search for spatial network databases

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Mohammad R. Kolahdouzan¹, Cyrus Shahabi¹•Institutions (1)

University of Southern California¹

31 Aug 2004

TL;DR: This paper proposes a novel approach to efficiently and accurately evaluate KNN queries in spatial network databases using first order Voronoi diagram, which outperforms approaches that are based on on-line distance computation by up to one order of magnitude, and provides a factor of four improvement in the selectivity of the filter step as compared to the index-based approaches.

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Abstract: A frequent type of query in spatial networks (e.g., road networks) is to find the K nearest neighbors (KNN) of a given query object. With these networks, the distances between objects depend on their network connectivity and it is computationally expensive to compute the distances (e.g., shortest paths) between objects. In this paper, we propose a novel approach to efficiently and accurately evaluate KNN queries in spatial network databases using first order Voronoi diagram. This approach is based on partitioning a large network to small Voronoi regions, and then pre-computing distances both within and across the regions. By localizing the precomputation within the regions, we save on both storage and computation and by performing across-the-network computation for only the border points of the neighboring regions, we avoid global pre-computation between every node-pair. Our empirical experiments with several real-world data sets show that our proposed solution outperforms approaches that are based on on-line distance computation by up to one order of magnitude, and provides a factor of four improvement in the selectivity of the filter step as compared to the index-based approaches.

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520 citations

"A Study of Pre-Processing Technique..." refers background in this paper

...Kolahdouzan and Shahabi [10] proposed: “a novel approach to evaluate k-Nearest Neighbor (kNN) queries in spatial network databases using first order Voronoi diagram based on partitioning a large network to small Voronoi regions, and then pre-computing distances both within and across the regions”....
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...To propose new model of road network is fundamental problem in Geographic Information System (GIS) databases for LBS applications [9-13]....
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