相关论文: Detecting and Analyzing Mobility Hotspots using Su…
A powerful framework for studying graphs is to consider them as geometric graphs: nodes are randomly sampled from an underlying metric space, and any pair of nodes is connected if their distance is less than a specified neighborhood radius.…
Automatic detection of public transport (PT) usage has important applications for intelligent transport systems. It is crucial for understanding the commuting habits of passengers at large and over longer periods of time. It also enables…
Vehicle trajectory data collected via GPS-enabled devices have played increasingly important roles in estimating network-wide traffic, given their broad spatial-temporal coverage and representativeness of traffic dynamics. This paper…
We present a simple model to predict network activity at the edge level, by extending a known approximation method to compute Betweenness Centrality (BC) with a repulsive mechanism to prevent unphysical densities. By taking into account the…
Moving window and hot spot detection analyses are statistical methods used to analyze point patterns within a given area. Such methods have been used to successfully detect clusters of point events such as car thefts or incidences of…
Clustering trajectory data attracted considerable attention in the last few years. Most of prior work assumed that moving objects can move freely in an euclidean space and did not consider the eventual presence of an underlying road network…
Mobility analytics using data generated from the Internet of Mobile Things (IoMT) is facing many challenges which range from the ingestion of data streams coming from a vast number of fog nodes and IoMT devices to avoiding overflowing the…
Urban transportation plays a vital role in modern city life, affecting how efficiently people and goods move around. This study analyzes transportation patterns using two datasets: the NYC Taxi Trip dataset from New York City and the Pathao…
In the field of urban planning, road network system planning is often the first step and the main purpose of urban planning is to create a spatial configuration of different functions such as residence, education, business, etc. Generally…
The central points of communication network flow has often been identified using graph theoretical centrality measures. In real networks, the state of traffic density arises from an interplay between the dynamics of the flow and the…
Road transportation is of critical importance for a nation, having profound effects in the economy, the health and life style of its people. With the growth of cities and populations come bigger demands for mobility and safety, creating new…
With the pervasiveness of IoT devices, smart-phones and improvement of location-tracking technologies huge volume of heterogeneous geo-tagged (location specific) data is generated which facilitates several location-aware services. The…
Human mobility regularity is crucial for understanding urban dynamics and informing decision-making processes. This study first quantifies the periodicity in complex human mobility data as a sparse identification of dominant positive…
A major problem in road network analysis is discovery of important crossroads, which can provide useful information for transport planning. However, none of existing approaches addresses the problem of identifying network-wide important…
The intense demands for higher data rates and ubiquitous network coverage have raised the stakes on developing new network topology and architecture to meet these ever-increasing demands in a cost-effective manner. The telecommunication…
Given a network, the critical node detection problem finds a subset of nodes whose removal disrupts the network connectivity. Since many real-world systems are naturally modeled as graphs, assessing the vulnerability of the network is…
We introduce a community detection method that finds clusters in network time-series by introducing an algorithm that finds significantly interconnected nodes across time. These connections are either increasing, decreasing, or constant…
Real-time traffic volume inference is key to an intelligent city. It is a challenging task because accurate traffic volumes on the roads can only be measured at certain locations where sensors are installed. Moreover, the traffic evolves…
The movement changes the underlying spatial representation of the participated mobile objects or nodes. In real world scenario, such mobile nodes can be part of any biological network, transportation network, social network, human…
Spatial road networks have been widely employed to model the structure and connectivity of cities. In such representation, the question of spatial scale of the entities in the network, i.e. what its nodes and edges actually embody in…