TY - GEN
T1 - HBA-histogram based algorithm for real time route forecasting in urban area
AU - El-Sayed, Hesham
AU - Zhang, Liren
AU - Thandavarayan, Gokulnath
AU - Hawas, Yasser
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/12
Y1 - 2016/7/12
N2 - Intelligent Transport System (ITS) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous traffic system, while providing communication access to vehicles with various Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication for the development of a safety commuting service. Building a route forecasting system is a complex task, mainly because of the changing traffic conditions. This paper presents a new route guidance algorithm and presents a compact road traffic model with real time updating. The algorithm enables to select a shortest path between source to destination by estimating the histogram model which captures the higher order distribution function using ITS. The data entity collection through sensors used for histogram modelling is presented in detail. A microscopic simulation model is utilized to evaluate the effectiveness of the proposed traffic model against the existing algorithm. Average travel time and overall network productivity are measured using the simulation. Various scenarios were created to study the impact of the proposed model in the traffic modelling.
AB - Intelligent Transport System (ITS) shall be able to incorporate transparently and seamlessly a large number of different and heterogeneous traffic system, while providing communication access to vehicles with various Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication for the development of a safety commuting service. Building a route forecasting system is a complex task, mainly because of the changing traffic conditions. This paper presents a new route guidance algorithm and presents a compact road traffic model with real time updating. The algorithm enables to select a shortest path between source to destination by estimating the histogram model which captures the higher order distribution function using ITS. The data entity collection through sensors used for histogram modelling is presented in detail. A microscopic simulation model is utilized to evaluate the effectiveness of the proposed traffic model against the existing algorithm. Average travel time and overall network productivity are measured using the simulation. Various scenarios were created to study the impact of the proposed model in the traffic modelling.
KW - Histograms
KW - Route Forecasting
KW - Traffic Modelling
KW - VANET
UR - http://www.scopus.com/inward/record.url?scp=84981309716&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84981309716&partnerID=8YFLogxK
U2 - 10.1109/ICC.2016.7511189
DO - 10.1109/ICC.2016.7511189
M3 - Conference contribution
AN - SCOPUS:84981309716
T3 - 2016 IEEE International Conference on Communications, ICC 2016
BT - 2016 IEEE International Conference on Communications, ICC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Communications, ICC 2016
Y2 - 22 May 2016 through 27 May 2016
ER -