R language - Type III Anova failure on "clmm" ordinal regression model

I am doing a statistical analysis by using Type-III Anova on an ordinal regression model with "clmm" function. My initial code is shown below:

require (ordinal)

require (RVAideMemoire)

require (car)

Risk <- factor (DWQ$Risk_Perception, ordered = T)

RP <- clmm(Risk ~ Location + Consequence + Distraction_Type + Location * Consequence + Location * Distraction_Type + (1|Subject), data = DWQ, link = "probit")

summary(RP)

Anova.clmm (RP, type = 3)

In this regression model, "Risk" is ordinal data from 1 to 5. The three independent variables, Location(5 levels), Distraction_type(2 levels), Consequences(3 levels), are written in non-numeric format. The "clmm" function does support for type-III Anova analysis. However, in this case, the algorithm forces me to use Type II Anova, and the result is also strange (shown below):

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Anova.clmm (RP, type = 3)

Analysis of Deviance Table (Type II tests)

Response: Risk

                           LR Chisq Df Pr(>Chisq)    
Location                      0.00  4  1.0000000    
Consequence                   0.00  2  0.9999998    
Distraction_Type              0.00  1  0.9995538    
Location:Consequence        469.80  8  < 2.2e-16 ***
Location:Distraction_Type    18.56  4  0.0009596 ***

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The value of the Chi-sq test is zero, and p values are not correct. If I change the Anova test to type-II, it seems that everything goes right (shown below):

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Anova.clmm (RP, type = 2)

Analysis of Deviance Table (Type II tests)

Response: Risk

                           LR Chisq Df Pr(>Chisq)    

Location                   3026.47  4  < 2.2e-16 ***

Consequence                  38.20  2  5.063e-09 ***

Distraction_Type           1494.63  1  < 2.2e-16 ***

Location:Consequence        469.80  8  < 2.2e-16 ***

Location:Distraction_Type    18.56  4  0.0009596 ***

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What might be causing this problem?