Summary
The use of soft computing methodologies in the field of traffic and transport systems is of particular interest to researchers and practitioners due to their ability to handle quantitative and qualitative measures, and to efficiently solve problems which involve complexity, imprecision and uncertainty. This paper provides a survey of soft computing applications. A classification scheme for soft computing applications is defined. The current frameworks and some future directions of soft computing applications to traffic and transport systems are discussed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pappis C, Mamdani EH (1977) A Fuzzy Logic Controller for a Traffic Junction, IEEE Transactions on Systems, Man and Cybernetics SMC-7:707–717
Niittymäki J, Pursula M (2000) Signal Control using Fuzzy Logic, Fuzzy Sets and Systems 116:1:11–22
Kaczmarek M, Rakiewicz M (1980) Fuzzy Control and its Application to Over Saturated Traffic Flows, Second International ATEC Congress, Regulation 80, Paris, France
Chen LL, May AD, Auslander DM (1990) Freeway Ramp Control using Fuzzy Set Theory for Inexact Reasoning, Transportation Research A 24:15–25
Kuo KY, Lin J (2000) Application of Fuzzy Set Theory to the Change Intervals at a Signalized Intersection, Fuzzy Sets and Systems
Papageorgiou M, Messmer A, Azema J, Drewanz D (1995) A Neural Network Approach to Freeway Network Traffic Control, Control Engineering Practice 3:1719–1726
Park B, Chang M (2002) Realizing Benefits of Adaptive Signal Control at an Isolated Intersection. Transportation Research Record 1811
Sha’Aban J, Tomlinson A, Heydecker B, Bull L (2002) Adaptive Traffic Control using Evolutionary Algorithms, The 13th Mini-Euro Conference, Bari, Italy
Sun D (2003) Multi-Objective Intersection Signal Timing Optimization with Evolutionary Algorithms, The 10th World Congress on Intelligent Transport Systems, Madrid, Spain
Park D, Rilett LR, Han G (1999) Spectral Basis Neural Networks for Real-Time Travel Time Forecasting, Journal of Transportation Engineering 125:6:515–523
Ishak S, Kotha P, Alecsandru C (2003) Optimization of Dynamic Neural Network Performance for Short-Term Traffic Prediction. In Transportation Research Record 1836:45–56
Hatipkarasulu Y, Wolshon B (2003) Variable Response Time Lag Module for Car-Following Models: Development and Structuring with Fuzzy Set Theory. Transportation Research Record 1843:50–60
Hsiao C-H, Lin C-T, Cassidy M (1994) Application of Fuzzy Logic and Neural Networks to Automatically Detect Freeway Traffic Incidents, Journal of Transportation Engineering 120:5:753–772
Teodorović D, Kikuchi S (1990) Transportation Route Choice Model using Fuzzy Inference Technique, Proceedings of ISUMA’ 90, IEEE Computer Society Press, College Park, Maryland, pp. 140–145
Lotan T, Koutsopoulos HN (1993) Models for Route Choice Behavior in the Presence of Information using Concepts from Fuzzy Set Theory and Approximate Reasoning, Transportation 20:129–155
Henn V (2000) Fuzzy Route Choice Model for Traffic Assignment, Fuzzy Sets and Systems 116:1:77–101
Lyons GD, Hunt JG (1993) Traffic Models — A Role for Neural Networks? The Third International Conference on the Application of Artificial Intelligence to Civil and Structural Engineering, Edinburgh, UK, pp. 71–79
Vythoulkas PC (1994) An Approach to travel Behavior Based on the Concepts of fuzzy Logic and Neural Networks. The 22nd PTRC Transport Forum, Education and Research Services, London, UK, pp. 189–205
Nakayama S, Kitamura R (2000) Route Choice Model with Inductive Learning, Transportation Research Record 1725
Přibyl O (2003) Clustering of Activity Patterns using Genetic Algorithms. The 8th World Conference on Soft Computing in Industrial Applications
Xu W, Chan Y (1993) Estimating an Origin-Destination Matrix with Fuzzy Weights, Part I: Methodology, Transportation Planning and Technology 17:127–137
Tao Y, Xinmiao Y (1998) Fuzzy Comprehensive Assessment, Fuzzy Clustering Analysis and its Application for Urban Traffic Environment Quality Evaluation, Transportation Research D 3:1:51–57
Kim D (2001) Neural Networks for Trip Generation Model, Journal of the Eastern Asia Society for Transportation Studies 4:2:201–208
Avineri E, Prashker JN, Ceder A (2000) Transportation Projects Selection Process using Fuzzy Sets Theory, Fuzzy Sets and Systems 116:1:35–47
Batanović V, Petrović R (1997) Determining the Best Location for a Logistic Center on a Motorway, The 9th Mini-EURO Conference, Budva, Yugoslavia
Vukadinović K, Teodorović D, Paković G (1997) A NeuroFuzzy Approach to the Vehicle Assignment Problem, The 9th Mini-EURO Conference, Budva, Yugoslavia
Jung S, Haghani A (2000) Genetic Algorithm for a Pickup and Delivery Problem with Time Windows, Transportation Research Record 1733
Gunaratne M, Chameau JL, Altschaeff AG (1984) Introduction to Fuzzy Sets in Pavement Evaluation (Abridgment), Transportation Research Record 985
Juang, CH, Ulshafer ML (1990) Development of an Expert System for Preliminary Selection of Pile Foundation, Transportation Research Record 1277
Kaseko MS, Ritchie SG (1993) A Neural Network-based Methodology for Pavement Crack Detection and Classification, Transportation Research C
Fwa TF, Chan WT, Tan CY (1994) Optimal Programming by Genetic Algorithms for Pavement Management, Transportation Research Record 1455
Taha MA, Hanna AS (1995) Evolutionary Neural Network Model for the Selection of Pavement Maintenance Strategy, Transportation Research Record 1497
Lee C, Chen CF, Huang S-M, Hsu C-J (2002) Application of Neural Network for Selection of Airport Rigid Pavement Maintenance Strategies, The 81st Annual Meeting of the Transportation Research Board, Washington, D.C.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Avineri, E. (2005). Soft Computing Applications in Traffic and Transport Systems: A Review. In: Hoffmann, F., Köppen, M., Klawonn, F., Roy, R. (eds) Soft Computing: Methodologies and Applications. Advances in Soft Computing, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32400-3_2
Download citation
DOI: https://doi.org/10.1007/3-540-32400-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25726-4
Online ISBN: 978-3-540-32400-3
eBook Packages: EngineeringEngineering (R0)