TY - GEN
T1 - Autonomous agent oriented traffic control system
AU - Afsar, Sadiaa
AU - Malik, Zafar Iqbal
AU - Elnaffar, Said
PY - 2010
Y1 - 2010
N2 - Emerging trends in software development has been changed due to the huge amount of data, growth of internet, mobile, dynamic and smart applications. Most of such applications consist of small, intelligent, flexible and distributed components known as agents. Number of agent methodologies has been presented but few of these are evaluated and verified. Due to the invention of agent technology, the way to analyze, design and build the systems has been changed. Agents take input from the multiple sources and have real time response. Vehicle traffic management especially in large cities is rapidly becoming one of the major challenges due to heavy growth in population and vehicles. Our research proposed a solution for traffic control and management system using intelligent/ autonomous agents technology. These agents have the ability to observe, act and learn from their experience. Our system uses the knowledge of flow of previous signal to predict the incoming flow for the next signal. The proposed architecture involves the video analysis and exploration using some machine learning techniques to estimate and guess the flow of traffic.
AB - Emerging trends in software development has been changed due to the huge amount of data, growth of internet, mobile, dynamic and smart applications. Most of such applications consist of small, intelligent, flexible and distributed components known as agents. Number of agent methodologies has been presented but few of these are evaluated and verified. Due to the invention of agent technology, the way to analyze, design and build the systems has been changed. Agents take input from the multiple sources and have real time response. Vehicle traffic management especially in large cities is rapidly becoming one of the major challenges due to heavy growth in population and vehicles. Our research proposed a solution for traffic control and management system using intelligent/ autonomous agents technology. These agents have the ability to observe, act and learn from their experience. Our system uses the knowledge of flow of previous signal to predict the incoming flow for the next signal. The proposed architecture involves the video analysis and exploration using some machine learning techniques to estimate and guess the flow of traffic.
KW - Agent
KW - Autonomic
KW - Optimization
KW - Prediction
KW - Traffic management
UR - http://www.scopus.com/inward/record.url?scp=77952656265&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77952656265&partnerID=8YFLogxK
U2 - 10.1109/ICCAE.2010.5451523
DO - 10.1109/ICCAE.2010.5451523
M3 - Conference contribution
AN - SCOPUS:77952656265
SN - 9781424455850
T3 - 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
SP - 321
EP - 324
BT - 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
T2 - 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
Y2 - 26 February 2010 through 28 February 2010
ER -