Goldstein and Satellite Center

Haifa, Israel

Goldstein and Satellite Center

Haifa, Israel
SEARCH FILTERS
Time filter
Source Type

Puzis R.,University of Maryland University College | Altshuler Y.,Massachusetts Institute of Technology | Elovici Y.,Ben - Gurion University of the Negev | Bekhor S.,Technion - Israel Institute of Technology | And 2 more authors.
Journal of Intelligent Transportation Systems: Technology, Planning, and Operations | Year: 2013

Network planning and traffic flow optimization require the acquisition and analysis of large quantities of data such as the network topology, its traffic flow data, vehicle fleet composition, emission measurements and so on. Data acquisition is an expensive process that involves household surveys and automatic as well as semiautomatic measurements performed all over the network. For example, in order to accurately estimate the effect of a certain network change on the total emissions produced by vehicles in the network, assessment of the vehicle fleet composition for each origin-destination pair is required. As a result, problems that optimize nonlocal merit functions become highly difficult to solve. One such problem is finding the optimal deployment of traffic monitoring units. In this article we suggest a new traffic assignment model that is based on the concept of shortest path betweenness centrality measure, borrowed from the domain of complex network analysis. We show how betweenness can be augmented in order to solve the traffic assignment problem given an arbitrary travel cost definition. The proposed traffic assignment model is evaluated using a high-resolution Israeli transportation data set derived from the analysis of cellular phones data. The group variant of the augmented betweenness centrality is then used to optimize the locations of traffic monitoring units, hence reducing the cost and increasing the effectiveness of traffic monitoring. © 2013 Taylor & Francis Group, LLC.


Elor Y.,Goldstein and Satellite Center | Bruckstein A.M.,Goldstein and Satellite Center
Theoretical Computer Science | Year: 2011

We consider two variants of the task of spreading a swarm of agents uniformly on a ring graph. Ant-like oblivious agents having limited capabilities are considered. The agents are assumed to have little memory, they all execute the same algorithm and no direct communication is allowed between them. Furthermore, the agents do not possess any global information. In particular, the size of the ring (n) and the number of agents in the swarm (k) are unknown to them. The agents are assumed to operate on an unweighted ring graph. Every agent can measure the distance to his two neighbors on the ring, up to a limited range of V edges. The first task considered, is dynamical (i.e. in motion) uniform deployment on the ring. We show that if either the ring is unoriented, or the visibility range is less than ⌊nk⌋, this is an impossible mission for the agents. Then, for an oriented ring and V


Elor Y.,Goldstein and Satellite Center | Bruckstein A.M.,Goldstein and Satellite Center
Theoretical Computer Science | Year: 2012

A source-seeking process for a pair of simple, low capability robots using only point measurements is proposed and analyzed. The robots are assumed to be memoryless, to lack the capability of performing complex computations and to have no direct communication abilities. Their only implicit form of communication is by sensing their relative position and the only response of a robot to the point measurement it makes is by moving to adjust its distance to the other robot according to a predetermined rule. The proposed algorithm is robust: we prove that the algorithm performs correctly even when the robots frequently err due to noisy sensor readings. © 2012 Elsevier B.V. All rights reserved.


Elor Y.,Goldstein and Satellite Center | Bruckstein A.M.,Goldstein and Satellite Center
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

In a previous paper [1], we proposed a new approach to the simultaneous cooperative localization of a very large group of simple robots capable of performing dead-reckoning and sensing the relative position of nearby robots. The idea behind the proposed averaging process is the following: every time two robots meet, they simply average their location estimates. This paper extends the results of [1] by considering noisy relative location measurements and by presenting a novel analysis based on the Well Mixing Movement Pattern assumption. The results of this paper are more precise than what was previously reported. Nevertheless, when considering the limit of a large group of robots, and after a long "stabilization" time, the final results turn out to be identical. © 2012 Springer-Verlag.


Elor Y.,Goldstein and Satellite Center | Bruckstein A.M.,Goldstein and Satellite Center
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

We consider two variants of the task of spreading a swarm of agents uniformly on a ring graph. Ant-like oblivious agents having limited capabilities are considered. The agents are assumed to have little memory, they all execute the same algorithm and no direct communication is allowed between them. Furthermore, the agents do not possess any global information. In particular, the size of the ring (n) and the number of agents in the swarm (k) are unknown to them. The agents are assumed to operate on an unweighted ring graph. Every agent can measure the distance to his two neighbors on the ring, up to a limited range of V edges. The first task considered, is uniformly spread dynamical (i.e. in motion) deployment on the ring. We show that if either the ring is unoriented, or the visibility range is less than [n/k], this is an impossible mission for the agents. Then, for an oriented ring and V ≥ [n/k], we propose an algorithm which achieves the deployment task within the optimal time. The second task discussed, called quiescent spread, requires the agents to spread uniformly over the ring and stop moving. We prove that under our model in which every agent can measure the distance only to his two neighbors, this task is impossible. Subsequently, we propose an algorithm which achieves quiescent and almost uniform spread. The algorithms we present are scalable and robust. In case the environment (the size of the ring) or the number of agents changes during the run, the swarm adapts and re-deploys without requiring any outside interference. © 2010 Springer-Verlag Berlin Heidelberg.

Loading Goldstein and Satellite Center collaborators
Loading Goldstein and Satellite Center collaborators