Link delay estimation using fuzzy logic

Traffic congestion poses a major problem not only in developing countries but also in developed countries due to various reasons. When subjected to traffic congestion, the travelers are likely to face delays both at intersections (road junctions) and on road links. Delays can occur due to some technical factors (traffic volume, traffic light cycle) and non-technical factors (road conditions, weather and visibility). An estimate on the level of traffic delay can be helpful in providing information to travelers for effective route selection. There are many publications on estimating traffic delays, but these are mainly based on mathematical models. Fuzzy logic has proved to be an important approach to model both technical non technical factors. This paper presents a fuzzy approach to delay estimation on road links.

[1]  Yetis Sazi Murat,et al.  Comparison of fuzzy logic and artificial neural networks approaches in vehicle delay modeling , 2006 .

[2]  Donald J Dailey,et al.  A statistical algorithm for estimating speed from single loop volume and occupancy measurements , 1999 .

[3]  Peter C. Nelson,et al.  Application of fuzzy logic and neural networks for dynamic travel time estimation , 1999 .

[4]  黒田 孝次,et al.  Highway Capacity Manual改訂の動向--テイラ-教授の講演より , 1984 .

[5]  Irfan Younas,et al.  A real time traffic management system , 2009, 2009 2nd IEEE International Conference on Computer Science and Information Technology.

[6]  A. Dumont,et al.  Link travel time estimation with probe vehicles in signalised networks , 2003 .

[7]  Tom Cherrett,et al.  The use of SCOOT type single loop detectors to measure speed, journey time and queue status on non SCOOT controlled links , 1996 .

[8]  F. Hall,et al.  ESTIMATION OF SPEEDS FROM SINGLE-LOOP FREEWAY FLOW AND OCCUPANCY DATA USING CUSP CATASTROPHE THEORY MODEL , 1994 .

[9]  Steven I-Jy Chien,et al.  Dynamic freeway travel time prediction using probe vehicle data: Link-based vs , 2001 .

[10]  Robert L. Bertini,et al.  Travel time estimation using NiagaraST and latte , 2007, SIGMOD '07.

[11]  J. Anderson,et al.  Travel time estimation in urban road networks , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[12]  Henry X. Liu,et al.  On-line Traffic Signal Control Scheme with Real-time Delay Estimation Technology , 2001 .

[13]  Hai Yang,et al.  Fuzzy logic based intersection delay estimation , 2002 .

[14]  I Okutani,et al.  Dynamic prediction of traffic volume through Kalman Filtering , 1984 .

[15]  Irfan Younas,et al.  A hybrid system for vehicle routing and traffic delay estimation , 2012, Int. J. Comput. Aided Eng. Technol..

[16]  L. Chu.  Adaptive Kalman Filter Based Freeway Travel time Estimation , 2004 .

[17]  Bruce Hellinga,et al.  Improving freeway speed estimates from single-loop detectors , 2002 .

[18]  Bhagwant Persaud,et al.  EVALUATION OF SPEED ESTIMATES MADE WITH SINGLE-DETECTOR DATA FROM FREEWAY TRAFFIC MANAGEMENT SYSTEMS , 1989 .