Automatic linguistic report of traffic evolution in roads

In the field of intelligent transportation systems, one important challenge consists of maintaining updated the electronic panels installed in roads with relevant information expressed in natural language. Currently, these messages are produced by human experts. However, the amount of data to analyze in real time and the number of available experts are imbalanced and new computational tools are required to assist them in this work. Moreover, the same problem appears when we deal with automatically generating linguistic reports to assist traffic managers that must take their decisions based on large amounts of quickly evolving information. In this paper, we contribute to solve this problem by designing a computational application based on our research in the field of computational theory of perceptions. Here, we present an application where we generate linguistic descriptions of the traffic behavior evolving in time and changing between different levels of service. We include some results obtained with both, simulated and real data.

[1]  Gracián Triviño,et al.  Linguistic reporting of driver behavior: Summary and event description , 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

[2]  Fabrizio Granelli,et al.  Intelligent extended floating car data collection , 2009, Expert Syst. Appl..

[3]  Lotfi A. Zadeh,et al.  From Computing with Numbers to Computing with Words - from Manipulation of Measurements to Manipulation of Perceptions , 2005, Logic, Thought and Action.

[4]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[5]  Alejandro Sanchez,et al.  Linguistic description of traffic in a roundabout , 2010, International Conference on Fuzzy Systems.

[6]  Daniel Sánchez,et al.  Fuzzy cardinality based evaluation of quantified sentences , 2000, Int. J. Approx. Reason..

[7]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[8]  R. R. Yager,et al.  Fuzzy summaries in database mining , 1995, Proceedings the 11th Conference on Artificial Intelligence for Applications.

[9]  Erhan Bas,et al.  Road and Traffic Analysis from Video , 2007 .

[10]  Angel Barriga,et al.  Linguistic summarization of network traffic flows , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[11]  K J Button.  ECONOMICS OF TRANSPORT NETWORKS. IN: HANDBOOK OF TRANSPORT SYSTEMS AND TRAFFIC CONTROL , 2001 .

[12]  Gracián Triviño,et al.  Combining Semantic Web technologies and Computational Theory of Perceptions for text generation in financial analysis , 2010, International Conference on Fuzzy Systems.

[13]  Enrique H. Ruspini,et al.  A New Approach to Clustering , 1969, Inf. Control..

[14]  Michel Pasquier,et al.  A novel self-organizing fuzzy rule-based system for modelling traffic flow behaviour , 2009, Expert Syst. Appl..

[15]  R. Blake,et al.  Image Processing in Road Traffic Analysis , 2005 .

[16]  Lotfi A. Zadeh,et al.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[17]  W WEN,et al.  A dynamic and automatic traffic light control expert system for solving the road congestion problem , 2008, Expert Syst. Appl..

[18]  Gracián Triviño,et al.  Automatic linguistic description about relevant features of the Mars' surface , 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

[19]  Chris Rizos,et al.  Positioning Systems in Intelligent Transportation Systems , 1997 .

[20]  W. Wen,et al.  An intelligent traffic management expert system with RFID technology , 2010, Expert Syst. Appl..

[21]  Gonzalo Bailador,et al.  Application of the computational theory of perceptions to human gait pattern recognition , 2010, Pattern Recognit..

[22]  Oscar Cordón,et al.  Body posture recognition by means of a genetic fuzzy finite state machine , 2011, 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

[23]  José M. Alonso,et al.  Human activity recognition applying computational intelligence techniques for fusing information related to WiFi positioning and body posture , 2010, International Conference on Fuzzy Systems.

[24]  Ralph Arnote,et al.  Hong Kong (China) , 1996, OECD/G20 Base Erosion and Profit Shifting Project.

[25]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[26]  David A. Hensher,et al.  Handbook of Transport Systems and Traffic Control , 2001 .

[27]  José Angel Olivas Varela,et al.  An adaptive approach to enhanced traffic signal optimization by using soft-computing techniques , 2011 .

[28]  Oscar Cordón,et al.  Human Gait Modeling Using a Genetic Fuzzy Finite State Machine , 2012, IEEE Transactions on Fuzzy Systems.

[29]  Juan Luis Castro,et al.  Fuzzy logic controllers are universal approximators , 1995, IEEE Trans. Syst. Man Cybern..

[30]  E. H. Mamdani,et al.  Application of Fuzzy Logic to Approximate Reasoning Using Linguistic Synthesis , 1976, IEEE Transactions on Computers.

[31]  Beatriz Delgado,et al.  Fuzzy linguistic reporting in driving simulators , 2011, 2011 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Proceedings.

[32]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning - II , 1975, Inf. Sci..

[33]  S. Savas Durduran,et al.  A decision making system to automatic recognize of traffic accidents on the basis of a GIS platform , 2010, Expert Syst. Appl..