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Figure 7: Road network with six intersections. Figure 6: Video screen shot of traffic flow at a signalized intersection in Bandung City, Indonesia.

Figure 7 Road network with six intersections. Figure 6: Video screen shot of traffic flow at a signalized intersection in Bandung City, Indonesia.

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velocity by using four-step rules, i.e. acceleration, distance adjustment, randomization, and vehicles movement [9]. Figure 1: Illustration of change lane rules of vehicles.
velocity by using four-step rules, i.e. acceleration, distance adjustment, randomization, and vehicles movement [9]. Figure 1: Illustration of change lane rules of vehicles.
Table 1: Fuzzy rules. In this study, there are two fuzzy inference system input variables. The first is the number of vehicles on the road arm being addressed to be given the green signal. The second is the total number of vehicles on three other road arms which lined up to be given the green signal. The next process of fuzzy inference system method is fuzzyfication, inference, and defuzzyfication until crisp value of green light duration is produced in each signalized intersection. See [4] for more comprehensive review.
Table 1: Fuzzy rules. In this study, there are two fuzzy inference system input variables. The first is the number of vehicles on the road arm being addressed to be given the green signal. The second is the total number of vehicles on three other road arms which lined up to be given the green signal. The next process of fuzzy inference system method is fuzzyfication, inference, and defuzzyfication until crisp value of green light duration is produced in each signalized intersection. See [4] for more comprehensive review.
Figure 3: Membership function of green light duration. Figure 2: Membership function of the number of vehicles.
Figure 3: Membership function of green light duration. Figure 2: Membership function of the number of vehicles.
V, is used as number of vehicle membership function boundaries and V2 is used as green light duration membership function boundaries. Because the number of vehicle value must be discrete, then V, matrix become discrete values:
V, is used as number of vehicle membership function boundaries and V2 is used as green light duration membership function boundaries. Because the number of vehicle value must be discrete, then V, matrix become discrete values:
Figure 5: Simulation process using cellular automata and fuzzy inference system.
Figure 5: Simulation process using cellular automata and fuzzy inference system.
Figure 4: Simulation scenario of cellular automata and fuzzy inference system.
Figure 4: Simulation scenario of cellular automata and fuzzy inference system.
Table 2: Fixed time of green signal based on historica data of observation for six signalized intersection in Bandung City, Indonesia. Fixed time green signal from historical data at six signalized intersections are summarized in Table 2. Data from this table are then used as initial
Table 2: Fixed time of green signal based on historica data of observation for six signalized intersection in Bandung City, Indonesia. Fixed time green signal from historical data at six signalized intersections are summarized in Table 2. Data from this table are then used as initial
Table 3: Delay time average obtained from simulation. The performance of delay time average from FIS and fixed time scheme can be measured by level of service (LoS) criteria [15]. LoS is used to give a category for delay time. The LoS consists of
Table 3: Delay time average obtained from simulation. The performance of delay time average from FIS and fixed time scheme can be measured by level of service (LoS) criteria [15]. LoS is used to give a category for delay time. The LoS consists of
Table 4: Level of Service Criteria Table 5 until Table 10 reveals optimal timing of green signal using FIS scheme for six signalized intersections in Bandung city. The simu ation is running for 10 cycles. From these tables, it can be seen that all signalized intersections have faster green duration compared to fixed time Table 2. It is also can be observed that isted in in each cycle, the green light duration is changed adjusting with number of vehicles. From these resul s, it can be said that by adjusting the green light duration with the number of incoming and outgoing vehicles, the delay time is faster than without optimization so that traffic congestion at signalized intersection can be reduced.
Table 4: Level of Service Criteria Table 5 until Table 10 reveals optimal timing of green signal using FIS scheme for six signalized intersections in Bandung city. The simu ation is running for 10 cycles. From these tables, it can be seen that all signalized intersections have faster green duration compared to fixed time Table 2. It is also can be observed that isted in in each cycle, the green light duration is changed adjusting with number of vehicles. From these resul s, it can be said that by adjusting the green light duration with the number of incoming and outgoing vehicles, the delay time is faster than without optimization so that traffic congestion at signalized intersection can be reduced.
Table 6: Optimal timing of green signal using fuzzy inference system (FIS) at Soekarno Hatta Street — Buah Batu Street. Table 7: Optimal timing of green signal using fuzzy inference system (FIS) at Buah Batu Street — Pelajar Pejuang Street.
Table 6: Optimal timing of green signal using fuzzy inference system (FIS) at Soekarno Hatta Street — Buah Batu Street. Table 7: Optimal timing of green signal using fuzzy inference system (FIS) at Buah Batu Street — Pelajar Pejuang Street.
Table 5: Optimal timing of green signal using fuzzy inference system (FIS) at Soekarno Hatta Street — Ibrahim Adjie Street.
Table 5: Optimal timing of green signal using fuzzy inference system (FIS) at Soekarno Hatta Street — Ibrahim Adjie Street.
Table 8: Optimal timing of green signal using fuzzy inference system (FIS) at Pelajar Pejuang Street - Gatot Subroto Street. Table 9: Optimal timing of green signal using fuzzy inference system (FIS) at Gatot Subroto Street — Ibrahim Adjie Street.
Table 8: Optimal timing of green signal using fuzzy inference system (FIS) at Pelajar Pejuang Street - Gatot Subroto Street. Table 9: Optimal timing of green signal using fuzzy inference system (FIS) at Gatot Subroto Street — Ibrahim Adjie Street.
Table 10: Optimal timing of green signal using fuzzy inference system (FIS) at Terusan Buah Batu Street — Buah Batu Exit Toll Gate.
Table 10: Optimal timing of green signal using fuzzy inference system (FIS) at Terusan Buah Batu Street — Buah Batu Exit Toll Gate.
Related topics:
Traffic Signal ControlFuzzy Inference System
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