Perspective of Adaptive CN System for Forecasting Congestion of Road Traffic Flow

Tasuku Takagi

(Professor Emeritus) Tohoku University, Sendai, Japan.

DOI: 10.4236/cn.2014.62008                

Abstract

Basing upon the Weber-Fechner Law with respect to the stimulus (distance-headway) to the vehicle driver and the driver’s sensation (speed), the characteristic speed V_β is defined, which is the critical vehicles flow speed just before going to congestion in road traffic flow. From the information of real time measurement of traffic flow speed (V) and time-headway (T) at the specific positions along the road, the value of V_β is calculated and used for forecasting the flow. Discussed is how to use each V_β to forecast the congestion. The CN system devoted to the management of road traffic flow is proposed. The idea may contribute not only to easing the traffic flow but also to optimizing it to get high efficient traffic flow.

Keywords

CN for Road Network, Characteristic Speed, Critical Speed, Road Traffic Optimization

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Takagi, T. (2011) Scientific Study of Road Traffic Flow. LAP LAMBERT Academic Publishing, GmbH & Co. KG, Saarbrucken, Deutschland.
[2]	Lippi, M., Bertini, M. and Frasconi, P. (2013) Short-Term Traffic Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning. IEEE Trans. on Intelligent Transportation Systems, 14. http://dx.doi.org/10.1109/TITS.2013.2247040
[3]	Heidelberger, M. (2004) Nature From Within, Chap. 6 (Psychophysics: Measuring the Mental).
[4]	Maor, E. Can Perceptions Can Be Quantified? In: E the Story of a Number. Princeton University Press (first printing in 1994), Princeton.