FIS_SMP2: Fuzzy Inference System 3 (FIS3)

In ngort01/fuzzyMM: Map Matching Using Fuzzy Logic

Description

Fuzzy Inference System used in the Subsequent Map Matching Process at a junction (SMP-2).

Format

frbs object

Details

SMP-2 identifies a new link among the candidate links if the vehicle has crossed a junction. Here you can see the input variables, fuzzy subsets and fuzzy rules used in FIS3. It is usefull to know the variables and how they affect the rule outputs in case you plan to change the range of the fuzzy subsets.

Input variables to this FIS are:

• speed of the vehicle, v (m/s)

• heading error, HE (degrees)

• perpendicular distance to candidate link, PD (m)

• horizontal dilution of precision (HDOP)

• link connectivity

• distance error

The fuzzy subsets of the input variables are:

• high, low, zero

• small, large

• short, long

• good, bad

• indirect, direct

• small2, large2

The corresponding fuzzy rules used in this FIS are:

• If ( v is high) and (HE is small) then (L1 is average)

• If (v is high) and (HE is large) then (L1 is low)

• If (HDOP is good) and (PD is short) then (L1 is average)

• If (HDOP is good) and (PD is long) then (L1 is low)

• If ( HE is small) and (PD is short) then ( L1 is high)

• If ( HE is large) and ( PD is long) then (L1 is low)

• If (The connectivity with the previous link is low) then (The L3 is low)

• If (The connectivity with the previous link is high) then (The L3 is high)

• If (The distance error is low) then (The L3 is high)

• If (The distance error is high) then (The L3 is low)

See Also

get_var_bounds, set_var_bounds

Examples

fis_smp2 <- get_fis("SMP2")
fis_smp2
# Plot membership functions
plotMF(fis_smp2)

ngort01/fuzzyMM documentation built on May 23, 2019, 4:43 p.m.