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109
Mapmatching for lowsamplingrate GPS trajectories
 In Proc. ACM SIGSPATIAL GIS
, 2009
"... Mapmatching is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental preprocessing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount o ..."
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Cited by 54 (7 self)
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Mapmatching is the process of aligning a sequence of observed user positions with the road network on a digital map. It is a fundamental preprocessing step for many applications, such as moving object management, traffic flow analysis, and driving directions. In practice there exists huge amount of lowsamplingrate (e.g., one point every 25 minutes) GPS trajectories. Unfortunately, most current mapmatching approaches only deal with highsamplingrate (typically one point every 1030s) GPS data, and become less effective for lowsamplingrate points as the uncertainty in data increases. In this paper, we propose a novel global mapmatching algorithm called STMatching for lowsamplingrate GPS trajectories. STMatching considers (1) the spatial geometric and topological structures of the road network and (2) the temporal/speed constraints of the trajectories. Based on spatiotemporal analysis, a candidate graph is constructed from which the best matching path sequence is identified. We compare STMatching with the incremental algorithm and AverageFréchetDistance (AFD) based global mapmatching algorithm. The experiments are performed both on synthetic and real dataset. The results show that our STmatching algorithm significantly outperform incremental algorithm in terms of matching accuracy for lowsampling trajectories. Meanwhile, when compared with AFDbased global algorithm, STMatching also improves accuracy as well as running time.
Hidden Markov map matching through noise and sparseness
 In Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
, 2009
"... The problem of matching measured latitude/longitude points to roads is becoming increasingly important. This paper describes a novel, principled map matching algorithm that uses a Hidden Markov Model (HMM) to find the most likely road route represented by a timestamped sequence of latitude/longitud ..."
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Cited by 42 (3 self)
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The problem of matching measured latitude/longitude points to roads is becoming increasingly important. This paper describes a novel, principled map matching algorithm that uses a Hidden Markov Model (HMM) to find the most likely road route represented by a timestamped sequence of latitude/longitude pairs. The HMM elegantly accounts for measurement noise and the layout of the road network. We test our algorithm on ground truth data collected from a GPS receiver in a vehicle. Our test shows how the algorithm breaks down as the sampling rate of the GPS is reduced. We also test the effect of increasing amounts of additional measurement noise in order to assess how well our algorithm could deal with the inaccuracies of other location measurement systems, such as those based on WiFi and cell tower multilateration. We provide our GPS data and road network representation as a standard test set for other researchers to use in their map matching work. actual path 2 3
Performance Evaluation of SUVnet With RealTime Traffic Data
 IEEE Transactions on Vehicular Technology (TVT
, 2007
"... Abstract—In this paper, we present the characteristics of a vehicular ad hoc network (VANET), which is the Shanghai urban vehicular network (SUVnet). We construct a mobility model using the GPS data collected from more than 4000 taxis in Shanghai. The model is both realistic and large scale. Based o ..."
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Cited by 34 (6 self)
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Abstract—In this paper, we present the characteristics of a vehicular ad hoc network (VANET), which is the Shanghai urban vehicular network (SUVnet). We construct a mobility model using the GPS data collected from more than 4000 taxis in Shanghai. The model is both realistic and large scale. Based on this model, network topology and connectivity of SUVnet are studied. Because of the sparse distribution and dynamic topology of SUVnet, simply utilizing the conventional mobile ad hoc network routing protocols in SUVnet may not achieve a satisfactory performance. Therefore, we apply the delaytolerant network model to SUVnet and evaluate the epidemic routing protocols. We propose a new protocol, which is the distance aware epidemic routing (DAER), to improve the bundle delivery ratio. Results show that DAER performs well for a VANET. This paper provides a basis in studying a realistic urban VANET. Index Terms—Delaytolerant network (DTN), epidemic routing, mobility model, performance, vehicular ad hoc network (VANET). I.
Addressing the need for mapmatching speed: Localizing global curvematching algorithms
 In SSDBM
, 2006
"... With vehicle tracking data becoming an important sensor data resource for a range of applications related to traffic assessment and prediction, fast and accurate mapmatching algorithms become a necessary means to ultimately utilize this data. This work proposes a fast mapmatching algorithm which exp ..."
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Cited by 33 (8 self)
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With vehicle tracking data becoming an important sensor data resource for a range of applications related to traffic assessment and prediction, fast and accurate mapmatching algorithms become a necessary means to ultimately utilize this data. This work proposes a fast mapmatching algorithm which exploits tracking data error estimates in a provably correct way and offers a quality guarantee for the computed result trajectory. A new model for the mapmatching task is introduced which takes tracking error estimates into account. The proposed Adaptive Clipping algorithm (i) provably solves this mapmatching task and (ii) utilizes the weak Fréchet distance to measure similarity between curves. The algorithm uses the error estimates in the trajectory data to reduce the search space (erroraware pruning), while offering the quality guarantee of finding a curve which minimizes the weak Fréchet distance to the vehicle trajectory among all possible curves in the road network. Moreover, this work introduces an outputsensitive variant of an existing weak Fréchet mapmatching algorithm, which is also employed in the Adaptive Clipping algorithm. Outputsensitiveness paired with erroraware pruning makes Adaptive Clipping the first mapmatching algorithm that provably solves a welldefined mapmatching task. An experimental evaluation establishes further that Adaptive Clipping is also in a practical setting a fast algorithm that at the same time produces highquality matching results. 1
SeMiTri: A Framework for Semantic Annotation of Heterogeneous Trajectories
"... GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatiotemporal (x,y,t) points. For application purposes the stream is transformed into finite subsequences called trajectories. Existing knowledge extraction algorit ..."
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Cited by 29 (4 self)
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GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatiotemporal (x,y,t) points. For application purposes the stream is transformed into finite subsequences called trajectories. Existing knowledge extraction algorithms defined for trajectories mainly assume a specific context (e.g. vehicle movements) or analyze specific parts of a trajectory (e.g. stops), in association with data from chosen geographic sources (e.g. pointsofinterest, road networks). We investigate a more comprehensive semantic annotation framework that allows enriching trajectories with any kind of semantic data provided by multiple 3rd party sources. This paper presents SeMiTri the framework that enables annotating trajectories for any kind of moving objects. Doing so, the application can benefit from a “semantic trajectory” representation of the physical movement. The framework and its algorithms have been designed to work on trajectories with varying data quality and different structures, with the objective of covering abstraction requirements of a wide range of applications. Performance of SeMiTri has been evaluated using many GPS datasets from multiple sources – including both fast moving objects (e.g. cars, trucks) and people’s trajectories (e.g. with smartphones). These two kinds of experiments are reported in this paper.
Discovering Popular Routes from Trajectories
 In ICDE
, 2011
"... Abstract—The booming industry of locationbased services has accumulated a huge collection of users ’ location trajectories of driving, cycling, hiking, etc. In this work, we investigate the problem of discovering the Most Popular Route (MPR) between two locations by observing the traveling behavior ..."
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Cited by 28 (0 self)
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Abstract—The booming industry of locationbased services has accumulated a huge collection of users ’ location trajectories of driving, cycling, hiking, etc. In this work, we investigate the problem of discovering the Most Popular Route (MPR) between two locations by observing the traveling behaviors of many previous users. This new query is beneficial to travelers who are asking directions or planning a trip in an unfamiliar city/area, as historical traveling experiences can reveal how people usually choose routes between locations. To achieve this goal, we firstly develop a Coherence Expanding algorithm to retrieve a transfer network from raw trajectories, for indicating all the possible movements between locations. After that, the Absorbing Markov Chain model is applied to derive a reasonable transfer probability foreachtransfernodeinthe network, which is subsequently used as the popularity indicator in the search phase. Finally, we propose a Maximum Probability Product algorithm to discover the MPR from a transfer network based on the popularity indicators in a breadthfirst manner, and we illustrate the results and performance of the algorithm by extensive experiments. I.
Curve matching, time warping, and light fields: New algorithms for computing similarity between curves
 J. Mathematic Imaging and Vision
"... The problem of curve matching appears in many application domains, like time series analysis, shape matching, speech recognition, and signature verification, among others. Curve matching has been studied extensively by computational geometers, and many measures of similarity have been examined, amon ..."
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Cited by 24 (0 self)
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The problem of curve matching appears in many application domains, like time series analysis, shape matching, speech recognition, and signature verification, among others. Curve matching has been studied extensively by computational geometers, and many measures of similarity have been examined, among them being the Fréchet distance (sometimes referred in folklore as the “dogman ” distance). A measure that is very closely related to the Fréchet distance but has never been studied in a geometric context is the Dynamic Time Warping measure (DTW), first used in the context of speech recognition. This measure is ubiquitous across different domains, a surprising fact because notions of similarity usually vary significantly depending on the application. However, this measure suffers from some drawbacks, most importantly the fact that it is defined between sequences of points rather than curves. Thus, the way in which a curve is sampled to yield such a sequence can dramatically affect the quality of the result. Some attempts have been made to generalize the DTW to continuous domains, but the resulting algorithms have exponential complexity. In this paper we propose similarity measures that attempt to capture the “spirit ” of dynamic time warping while being defined over continuous domains, and present efficient algorithms for computing them. Our formulation leads to a very interesting connection with finding short paths in a combinatorial manifold defined on the input chains, and in a deeper sense relates to the way light travels in a medium of variable refractivity. 1
Exact Algorithm for Partial Curve Matching via the Fréchet Distance
 Proc. 20th ACMSIAM Symposium on Discrete Algorithms
, 2009
"... Curve matching is a fundamental problem that occurs in many applications. In this paper, we study the problem of measuring partial similarity between curves. Specifically, given two curves, we wish to maximize the total length of subcurves that are close to each other, where closeness is measured by ..."
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Cited by 24 (4 self)
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Curve matching is a fundamental problem that occurs in many applications. In this paper, we study the problem of measuring partial similarity between curves. Specifically, given two curves, we wish to maximize the total length of subcurves that are close to each other, where closeness is measured by the Fréchet distance, a common distance measure for curves. The resulting maximal length is called the partial Fréchet similarity between the two input curves. Given two polygonal curves P and Q in IR d of size m and n, respectively, we present the first exact algorithm that runs in polynomial time to compute Fδ(P, Q), the partial Fréchet similarity between P and Q, under the L1 and L ∞ norms. Specifically, we formulate the problem of computing Fδ(P, Q) as a longest path problem, and solve it in O(mn(m + n) log(mn)) time, under the L1 or L∞ norm, using a “shortestpath map ” type decomposition. To the best of our knowledge, this is the first paper to study this natural definition of partial curve similarity in the continuous setting (with all points in the curve considered), and present a polynomialtime exact algorithm for it. 1
Approximating the Fréchet distance for realistic curves in near linear time
 In Proc. 26th Annu. ACM Sympos. Comput. Geom
, 2010
"... We present a simple and practical (1 + ε)approximation algorithm for the Fréchet distance between two polygonal curves in IRd. To analyze this algorithm we introduce a new realistic family of curves, cpacked curves, that is closed under simplification. We believe the notion of cpacked curves to ..."
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Cited by 21 (7 self)
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We present a simple and practical (1 + ε)approximation algorithm for the Fréchet distance between two polygonal curves in IRd. To analyze this algorithm we introduce a new realistic family of curves, cpacked curves, that is closed under simplification. We believe the notion of cpacked curves to be of independent interest. We show that our algorithm has near linear running time for cpacked polygonal curves, and similar results for other input models, such as low density polygonal curves. 1
Fréchet distance for curves, revisited
 In ESA
, 2006
"... Abstract. We revisit the problem of computing the Fréchet distance between polygonal curves, focusing on the discrete Fréchet distance, where only distance between vertices is considered. We develop efficient approximation algorithms for two natural classes of curves: κbounded curves and backbone c ..."
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Cited by 20 (6 self)
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Abstract. We revisit the problem of computing the Fréchet distance between polygonal curves, focusing on the discrete Fréchet distance, where only distance between vertices is considered. We develop efficient approximation algorithms for two natural classes of curves: κbounded curves and backbone curves, the latter of which are widely used to model molecular structures. We also propose a pseudo–outputsensitive algorithm for computing the discrete Fréchet distance exactly. The complexity of the algorithm is a function of the complexity of the freespace boundary, which is quadratic in the worst case, but tends to be lower in practice. 1