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In the past, when there were few vehicles on the roads, the time-of-day (TOD) traffic signal worked very well. The TOD signal operates on a preset signal-cycling scheme independent of traffic conditions. It cycles on the basis of the number of average passenger cars to the memory device of an electric signal unit. Today, with the increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end-lag time. A 30 to 45% efficiency in traffic handling is lost, as well as added fuel costs, since it is not optimized for today's traffic condition. To solve this problem, an electrosensitive traffic light using neural fuzzy logic will be investigated. This scheme uses an electrosensitive traffic light control, which changes signal based on the passing vehicle's weight, length, and passing area. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signal since the average waiting time, average vehicle speed, and fuel consumption will be improved.Abstract-We remark on an error in the above paper. The purpose of this note is to present the correct formulas for partial derivatives of fuzzy integral-based neural nodes with respect to densities of Sugeno measures.Index Terms-Fuzzy integral, fuzzy measure.