Name
Abstract | ||
|---|---|---|
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 start-up 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 is 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 |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1109/91.811247 | IEEE T. Fuzzy Systems |
Keywords | Field | DocType |
traffic light,efficiency,new electrosensitive traffic light,tod signal,electrosensitive traffic light control,optimal traffic signal cycle,traffic handling,increasing traffic,fuzzy logic,traffic control,traffic signal,electrosensitive traffic light,traffic condition,signalling,fixed time interval signal,fuzzy control,road traffic,conventional traffic light,electric signal unit,vehicle waiting time,spill back,fuzzy neural nets,fuzzy neural network,fuel consumption,neural networks,computer simulation,fuzzy systems,cost function,indexing terms | Traffic signal,Control theory,Simulation,Floating car data,Fuzzy logic,Real-time computing,Fuel efficiency,Traffic congestion reconstruction with Kerner's three-phase theory,Fuzzy control system,Artificial neural network,Traffic conditions,Mathematics | Journal |
Volume | Issue | ISSN |
7 | 6 | 1063-6706 |
Citations | PageRank | References |
3 | 1.05 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yon-Sik Hong | 1 | 3 | 1.05 |
| HyunSoo Jin | 2 | 5 | 2.09 |
| Chongkug Park | 3 | 31 | 4.49 |