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I think they should ban all drivers who can't parallel park with a maximum of 1 correction, drive a manual transmission, or run a 1:30 or faster at Mission Raceway's road course, but that's just me.
I have no opinion on whether or not we should ban RHD cars having not read the research, if they are truly not more likely to be in an accident, then I would support not banning them. With that said, to suggest that a RHD car is not disadvantaged when making a left turn with a car opposite doing the same is just silly.
-Mark
Its at a total disadvantage but a good responsible driver makes adjustments to their driving habits to accommodate such disadvantages much like SUV drivers do over their car counterparts
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here is the text from the report: (I just used OCR to get it so its not perfect)
Assessment of the ICBC Report Regarding the Safety of Right
Hand Drive Vehicles in BC
Mohua Podder, PhD and Rick White, M.Sc.
Statistical Consulting and Research Laboratory
Department of Statistics
University of British Columbia
6356 Agricultural Road, Vancouver, BC
March 26, 2010
1 Introduction
This report evaluates the analyses done by ICBC in their report titled “The Safety of Right-HandDrive
Vehicles in British Columbia”. The request for the evaluation came from the Imported
Vehicle Owners Association of Canada (IVOAC). The number of right-hand-drive (RHD) vehicles
being imported into Canada over the past few years has been increasing. Imported vehicles over
15 years old are exempt from the requirement of having a manufacturers plate or letter stating
that the vehicle is compliant with the Canadian motor vehicle safety standards. This allows RHD
vehicles to retain their RHD control configuration. The belief is that potential issues related to
these vehicles might lead to a greater accident risk for operators of RHD vehicles and people in
RHD vehicles might be more severely injured than people in LHD vehicles.
ICBC conducted a study in order to assess the safety issues of RHD vehicles in BC and published
a report in early 2008. The main purpose of the study was to compare RHD to LHD vehicles in
terms of their risk of crash involvement and their occupant protection potential. The study applied
three different methodologies to try to answer these questions: a Relative Risk Analysis comparing
RHD and LHD culpable crash rates for the same group of drivers; a Survival Analysis to compare
the time to first culpable crash between drivers of RHD and LHD vehicles; and a Poisson Regression
Analysis to compare the risk of RHD vehicles to a similar group of LHD vehicles and their drivers.
2 Data Issues
The data for all three analyses were obtained from the ICBC crash-claim data. Does this database
accurately reflect all crashes in BC or just those that are reported? Drivers may choose not to
report their crash to avoid an increase in insurance rates because the value of the vehicle is low
or the repair is inexpensive relative to the increased insurance cost, perhaps the driver doesn’t
have the appropriate insurance coverage. If the tendency to not report a crash is related to the
drive configuration of the vehicle, it may introduce a bias in the data that could be reflected in the
analyses.
All three analyses rely on the definition of culpability. A vehicle is culpable in a crash if it is
assigned at least 50% of the responsibility during the claim adjustment process. Is blame assigned
by objective criteria or is there a subjective component? If the assignment of responsibility is
affected by the drive configuration of the cars involved in the crash then all analyses based on this
definition will be inherently biased. The assignment must be based on the circumstances of the
crash only. That means if a LHD car involved in a crash is deemed non-culpable then that status
would not change if that car had been a RHD vehicle.
3 Relative Risk Analysis
The first method used looks at the relative risk of culpable crashes to non-culpable crashes between
RHD and LHD vehicles operated by the same driver. This method compares crashes within drivers
to control for driver differences. All drivers involved in crashes while operating a RHD vehicle
since 2001 were included in the analysis. In addition the principal operators (POs) of these RHD
vehicles, if not already included, were selected to provide a set of drivers not involved in a crash
while driving a RHD vehicle. The complete crash history of each driver since 2001 was used in the
analysis. Each crash was classified as culpable or non-culpable from the target driver’s perspective.
After applying several constraints to the data, 359 crashes for RHD and 1204 crashes for LHD
vehicles were identified. Of the 1204 LHD vehicle crashes, 324 were from drivers with RHD vehicle
crashes and 880 were from the RHD PO group, the drivers without a crash while driving a
RHD vehicle. The total number of drivers in each group is not mentioned. A cross tabulation of
culpable/non-culpable crashes versus RHD/LHD vehicle was created. A Chi-squared test of independence
was used to determine if the type of crash was associated with the drive configuration
2of the vehicle. This analysis assumes that all events in the table are independent events not connected
by any other factor whereas here we actually have several 2x2 tables, one for each driver.
The data within each table depends on a specific driver but the tables themselves are independent.
In essence, we have a stratified sample. In order to perform the Pearson’s Chi-squared test for
independence, the stratification is ignored and the individual 2x2 tables are summed across drivers
to make a single 2x2 table. A more appropriate analysis for this type of data would account for the
stratification within the data. A possible analysis method would be the Cochran-Mantel-Haenszel
test.
Another possible concern for this data is if two vehicles involved in the same accident are
included in the data. This is probably a rare event and therefore a minor concern but should
probably be checked. The 2x2 tables for any drivers involved in the same accident would no longer
be independent and the analysis would need to be adjusted accordingly.
4 Survival Analysis
The second method of analysis uses a Cox proportional hazard regression model to compare the
instantaneous crash rate of RHD and LHD vehicles after they are first insured. The response data
is the time to a culpable crash following the initial insurance policy purchase by a PO for each
vehicle. The model has the advantage of including all vehicles even those that never had a culpable
crash over the course of the study. In addition, the model can also include adjustments for other
factors that might modulate the effect. In this analysis data were collected from “all RHD POs
aged 20 years and older at the time of first policy and all vehicles (RHD and LHD) for which
they were listed as POs”. Only culpable crashes were included as an event. Age and gender were
included as adjustments in the final model.
The sampling method described in section 2.2 sounds like a small set of POs was selected for
the analysis, each having been a PO of several vehicles of which at least one was a RHD vehicle.
The description of the analysis in section 3.2 implies a different set of drivers was included. Section
3.2 claims “A total of 23717 drivers were included in the analysis of which 2882 were associated
with RHD vehicles”. This section also describes the results in terms of vehicles. It is not clear who
has been sampled or what is being modeled here. Is it time to first culpable crash of a driver or
vehicle? Are multiple vehicles of the same driver or PO included in the model? Without a clear
description of the sampling scheme or data being collected, it is hard to comment on the methods.
3If the data is time to first culpable crash of a vehicle and several vehicles are associated with
the same PO, a correlation structure is induced into the data which needs to be adjusted for in
the model. Another concern with POs having multiple vehicles is they may split their time at risk
between their vehicles which further complicates the analysis. If we think of POs as a stratification
variable, a stratified Cox model can be applied to deal with some of these issues.
Ignoring the stratification issue, the analysis assumes that each vehicle is at risk at all times
when in fact a vehicle is only at risk when it is being driven. A vehicle driven 5 days a week is
more likely to have a crash than one driven once a week. The crash risk of a vehicle is also affected
by where and when it is driven. A vehicle driven in rush hour on Monday morning probably has a
different risk than one driven on Sunday morning, as would a vehicle driven in downtown Vancouver
compared to one driven in White Rock. Is there a way to guarantee that RHD vehicles are driven
the same amount of time, under the same conditions and locations as LHD vehicles? If not, what
is the affect of these factors on the results?
Age and Gender were included in the model as covariates. It is unclear if the effects presented in
Table 3 are from a model that contains only main effects or one that contains interactions with RHD
vehicles. As main effects, they modulate both the LHD and RHD crash rates. So all statements
pertaining to the effect of age and gender on RHD vehicles apply equally to LHD vehicles. A model
with interaction allows separate age and gender effects to be estimated and compared for the RHD
and LHD vehicles. The report states that the RHD vehicle group contained more males and was
younger. This causes partial confounding between age, gender and RHD vehicles. Confounding
affects the model estimates especially in a model with only main effects. The model estimates
the crash rate to be higher for males and younger drivers. Confounding may cause the model to
attribute some of these effects to RHD vehicles.
5 Poisson Regression Analysis
In the final analysis, a Poisson Regression model is used to compare the crash rates between RHD
vehicles and a group of similar LHD vehicles. A RHD group consisting of 748 vehicles, was identified
and a LHD group consisting of 8933 vehicles, was selected by model, make, year and body style so
the proportion of vehicles in that group matched the proportions in the RHD group. The response
data is the number of crash-claims in a two year period following the date of a PO’s first policy
with that vehicle. Each crash was classified as injury or material damage only and culpable or
4non-culpable. Covariates considered in the model were gender, age, region (lower mainland or not),
speeding contraventions and non-speeding contraventions.
The main concern of the model is to compare the crash rate between RHD and LHD vehicles.
However matching model-year-style in vehicles does not guarantee that both RHD and LHD vehicles
are exposed to equal amount of driving time or are driven in the same locations or in the same
traffic conditions. The confounding affect of gender and age with RHD vehicle operation also affects
a Poisson regression model in a similar fashion as a Cox model. The distribution and effects for
region and traffic contraventions is not presented in the report.
Another concern with Poisson regression models is overdispersion in the response data. If the
counts are overdispersed than an overdispersed Poisson or Negative Binomial regression model
needs to be fitted otherwise the standard errors of the effects will be underestimated and effect
significance will be overstated. The report does not indicate if overdispersion was checked in the
model.
The analysis is done by vehicle not by driver. The Poisson regression model assumes the data
for each vehicle is independent from each other. However a vehicle can have many drivers and a
driver can operate many vehicles. This may introduce a correlation between the vehicles if the same
driver operated more than one vehicle in the study. If there are many such drivers, the induced
correlation could become an issue for this model as well.
The report says principal operators were also examined to investigate the differences between
RHD and LHD vehicles at the driver level but it doesn’t explain how this is done. Does a RHD
driver always operate a RHD vehicle? If not, how is a crash in a LHD vehicle by a RHD driver
dealt with in the analysis?
6 Summary
There are several issues that could affect the results of the study conducted by ICBC in the report
“The Safety of Right-Hand-Drive Vehicles in British Columbia”. It is possible the conclusion would
remain unchanged even after these issues were resolved but we do not know without actually doing
those analyses.
Reporting a crash to ICBC is not mandatory if an insurance claim is not made. Are the factors
5that affect the tendency to make a claim related to the drive configuration of the vehicle? How is
blame assigned in a crash claim? If blame assignment has a subjective component, is it related to
drive configuration of the vehicle? If either is related to drive configuration then the data contains
a bias that could affect the results of any analysis based on the data and may not reflect the true
risk of a culpable crash of LHD or RHD vehicles in the province as a whole.
In addition to data issues, there are some issues with the analyses themselves. The relative
risk analysis completely ignores the repeated measures within each subject. This analysis is easily
corrected by using a Cochran-Mantel-Haenszel test instead of a Chi-squared test. There is also a
minor issue of some data coming from the same crash but this is probably a rare event and will
have little impact on the results.
The problems with the other two analyses are more subtle and technical. The drive configuration
of the vehicle was not evenly distributed between gender and age. Although the model adjusted for
these factors, imbalance can still affect the estimates in the model. If the data had been matched
on age and gender, the results would be more trustworthy. A stratified or paired analysis might
then be more appropriate in these cases. A More subtle issue is risk exposure. A vehicle is only at
risk of a culpable crash when it is driven. The risk exposure also depends on driving locations and
conditions. A vehicle driven to work every day during rush hour is at greater risk than one driven
once a week on Sunday morning. It is unclear if adequate data can be obtained to adjust for these
factors but they could have a big impact on the results. Drivers using multiple vehicles or vehicles
driven by multiple drivers is another issue. This introduce a correlation into the data that needs
to be taken into account. If there are several such vehicles or drivers in the data and the repeated
measures are properly adjusted for, the results of the analyses could be quite different. Again it is
unclear if such data is available.
Overall, the ICBC report suggests that RHD vehicles and their operators are at a greater risk
than their LHD counterparts but issues with the data and the analyses suggest that further study
is needed. Causation is difficult to establish with observational data. I would caution the use of
the ICBC report as anything more than an indication that further study is needed.
6
here is the text from the report: (I just used OCR to get it so its not perfect)
Assessment of the ICBC Report Regarding the Safety of Right
Hand Drive Vehicles in BC
Mohua Podder, PhD and Rick White, M.Sc.
Statistical Consulting and Research Laboratory
Department of Statistics
University of British Columbia
6356 Agricultural Road, Vancouver, BC
March 26, 2010
1 Introduction
This report evaluates the analyses done by ICBC in their report titled “The Safety of Right-HandDrive
Vehicles in British Columbia”. The request for the evaluation came from the Imported
Vehicle Owners Association of Canada (IVOAC). The number of right-hand-drive (RHD) vehicles
being imported into Canada over the past few years has been increasing. Imported vehicles over
15 years old are exempt from the requirement of having a manufacturers plate or letter stating
that the vehicle is compliant with the Canadian motor vehicle safety standards. This allows RHD
vehicles to retain their RHD control configuration. The belief is that potential issues related to
these vehicles might lead to a greater accident risk for operators of RHD vehicles and people in
RHD vehicles might be more severely injured than people in LHD vehicles.
ICBC conducted a study in order to assess the safety issues of RHD vehicles in BC and published
a report in early 2008. The main purpose of the study was to compare RHD to LHD vehicles in
terms of their risk of crash involvement and their occupant protection potential. The study applied
three different methodologies to try to answer these questions: a Relative Risk Analysis comparing
RHD and LHD culpable crash rates for the same group of drivers; a Survival Analysis to compare
the time to first culpable crash between drivers of RHD and LHD vehicles; and a Poisson Regression
Analysis to compare the risk of RHD vehicles to a similar group of LHD vehicles and their drivers.
2 Data Issues
The data for all three analyses were obtained from the ICBC crash-claim data. Does this database
accurately reflect all crashes in BC or just those that are reported? Drivers may choose not to
report their crash to avoid an increase in insurance rates because the value of the vehicle is low
or the repair is inexpensive relative to the increased insurance cost, perhaps the driver doesn’t
have the appropriate insurance coverage. If the tendency to not report a crash is related to the
drive configuration of the vehicle, it may introduce a bias in the data that could be reflected in the
analyses.
All three analyses rely on the definition of culpability. A vehicle is culpable in a crash if it is
assigned at least 50% of the responsibility during the claim adjustment process. Is blame assigned
by objective criteria or is there a subjective component? If the assignment of responsibility is
affected by the drive configuration of the cars involved in the crash then all analyses based on this
definition will be inherently biased. The assignment must be based on the circumstances of the
crash only. That means if a LHD car involved in a crash is deemed non-culpable then that status
would not change if that car had been a RHD vehicle.
3 Relative Risk Analysis
The first method used looks at the relative risk of culpable crashes to non-culpable crashes between
RHD and LHD vehicles operated by the same driver. This method compares crashes within drivers
to control for driver differences. All drivers involved in crashes while operating a RHD vehicle
since 2001 were included in the analysis. In addition the principal operators (POs) of these RHD
vehicles, if not already included, were selected to provide a set of drivers not involved in a crash
while driving a RHD vehicle. The complete crash history of each driver since 2001 was used in the
analysis. Each crash was classified as culpable or non-culpable from the target driver’s perspective.
After applying several constraints to the data, 359 crashes for RHD and 1204 crashes for LHD
vehicles were identified. Of the 1204 LHD vehicle crashes, 324 were from drivers with RHD vehicle
crashes and 880 were from the RHD PO group, the drivers without a crash while driving a
RHD vehicle. The total number of drivers in each group is not mentioned. A cross tabulation of
culpable/non-culpable crashes versus RHD/LHD vehicle was created. A Chi-squared test of independence
was used to determine if the type of crash was associated with the drive configuration
2of the vehicle. This analysis assumes that all events in the table are independent events not connected
by any other factor whereas here we actually have several 2x2 tables, one for each driver.
The data within each table depends on a specific driver but the tables themselves are independent.
In essence, we have a stratified sample. In order to perform the Pearson’s Chi-squared test for
independence, the stratification is ignored and the individual 2x2 tables are summed across drivers
to make a single 2x2 table. A more appropriate analysis for this type of data would account for the
stratification within the data. A possible analysis method would be the Cochran-Mantel-Haenszel
test.
Another possible concern for this data is if two vehicles involved in the same accident are
included in the data. This is probably a rare event and therefore a minor concern but should
probably be checked. The 2x2 tables for any drivers involved in the same accident would no longer
be independent and the analysis would need to be adjusted accordingly.
4 Survival Analysis
The second method of analysis uses a Cox proportional hazard regression model to compare the
instantaneous crash rate of RHD and LHD vehicles after they are first insured. The response data
is the time to a culpable crash following the initial insurance policy purchase by a PO for each
vehicle. The model has the advantage of including all vehicles even those that never had a culpable
crash over the course of the study. In addition, the model can also include adjustments for other
factors that might modulate the effect. In this analysis data were collected from “all RHD POs
aged 20 years and older at the time of first policy and all vehicles (RHD and LHD) for which
they were listed as POs”. Only culpable crashes were included as an event. Age and gender were
included as adjustments in the final model.
The sampling method described in section 2.2 sounds like a small set of POs was selected for
the analysis, each having been a PO of several vehicles of which at least one was a RHD vehicle.
The description of the analysis in section 3.2 implies a different set of drivers was included. Section
3.2 claims “A total of 23717 drivers were included in the analysis of which 2882 were associated
with RHD vehicles”. This section also describes the results in terms of vehicles. It is not clear who
has been sampled or what is being modeled here. Is it time to first culpable crash of a driver or
vehicle? Are multiple vehicles of the same driver or PO included in the model? Without a clear
description of the sampling scheme or data being collected, it is hard to comment on the methods.
3If the data is time to first culpable crash of a vehicle and several vehicles are associated with
the same PO, a correlation structure is induced into the data which needs to be adjusted for in
the model. Another concern with POs having multiple vehicles is they may split their time at risk
between their vehicles which further complicates the analysis. If we think of POs as a stratification
variable, a stratified Cox model can be applied to deal with some of these issues.
Ignoring the stratification issue, the analysis assumes that each vehicle is at risk at all times
when in fact a vehicle is only at risk when it is being driven. A vehicle driven 5 days a week is
more likely to have a crash than one driven once a week. The crash risk of a vehicle is also affected
by where and when it is driven. A vehicle driven in rush hour on Monday morning probably has a
different risk than one driven on Sunday morning, as would a vehicle driven in downtown Vancouver
compared to one driven in White Rock. Is there a way to guarantee that RHD vehicles are driven
the same amount of time, under the same conditions and locations as LHD vehicles? If not, what
is the affect of these factors on the results?
Age and Gender were included in the model as covariates. It is unclear if the effects presented in
Table 3 are from a model that contains only main effects or one that contains interactions with RHD
vehicles. As main effects, they modulate both the LHD and RHD crash rates. So all statements
pertaining to the effect of age and gender on RHD vehicles apply equally to LHD vehicles. A model
with interaction allows separate age and gender effects to be estimated and compared for the RHD
and LHD vehicles. The report states that the RHD vehicle group contained more males and was
younger. This causes partial confounding between age, gender and RHD vehicles. Confounding
affects the model estimates especially in a model with only main effects. The model estimates
the crash rate to be higher for males and younger drivers. Confounding may cause the model to
attribute some of these effects to RHD vehicles.
5 Poisson Regression Analysis
In the final analysis, a Poisson Regression model is used to compare the crash rates between RHD
vehicles and a group of similar LHD vehicles. A RHD group consisting of 748 vehicles, was identified
and a LHD group consisting of 8933 vehicles, was selected by model, make, year and body style so
the proportion of vehicles in that group matched the proportions in the RHD group. The response
data is the number of crash-claims in a two year period following the date of a PO’s first policy
with that vehicle. Each crash was classified as injury or material damage only and culpable or
4non-culpable. Covariates considered in the model were gender, age, region (lower mainland or not),
speeding contraventions and non-speeding contraventions.
The main concern of the model is to compare the crash rate between RHD and LHD vehicles.
However matching model-year-style in vehicles does not guarantee that both RHD and LHD vehicles
are exposed to equal amount of driving time or are driven in the same locations or in the same
traffic conditions. The confounding affect of gender and age with RHD vehicle operation also affects
a Poisson regression model in a similar fashion as a Cox model. The distribution and effects for
region and traffic contraventions is not presented in the report.
Another concern with Poisson regression models is overdispersion in the response data. If the
counts are overdispersed than an overdispersed Poisson or Negative Binomial regression model
needs to be fitted otherwise the standard errors of the effects will be underestimated and effect
significance will be overstated. The report does not indicate if overdispersion was checked in the
model.
The analysis is done by vehicle not by driver. The Poisson regression model assumes the data
for each vehicle is independent from each other. However a vehicle can have many drivers and a
driver can operate many vehicles. This may introduce a correlation between the vehicles if the same
driver operated more than one vehicle in the study. If there are many such drivers, the induced
correlation could become an issue for this model as well.
The report says principal operators were also examined to investigate the differences between
RHD and LHD vehicles at the driver level but it doesn’t explain how this is done. Does a RHD
driver always operate a RHD vehicle? If not, how is a crash in a LHD vehicle by a RHD driver
dealt with in the analysis?
6 Summary
There are several issues that could affect the results of the study conducted by ICBC in the report
“The Safety of Right-Hand-Drive Vehicles in British Columbia”. It is possible the conclusion would
remain unchanged even after these issues were resolved but we do not know without actually doing
those analyses.
Reporting a crash to ICBC is not mandatory if an insurance claim is not made. Are the factors
5that affect the tendency to make a claim related to the drive configuration of the vehicle? How is
blame assigned in a crash claim? If blame assignment has a subjective component, is it related to
drive configuration of the vehicle? If either is related to drive configuration then the data contains
a bias that could affect the results of any analysis based on the data and may not reflect the true
risk of a culpable crash of LHD or RHD vehicles in the province as a whole.
In addition to data issues, there are some issues with the analyses themselves. The relative
risk analysis completely ignores the repeated measures within each subject. This analysis is easily
corrected by using a Cochran-Mantel-Haenszel test instead of a Chi-squared test. There is also a
minor issue of some data coming from the same crash but this is probably a rare event and will
have little impact on the results.
The problems with the other two analyses are more subtle and technical. The drive configuration
of the vehicle was not evenly distributed between gender and age. Although the model adjusted for
these factors, imbalance can still affect the estimates in the model. If the data had been matched
on age and gender, the results would be more trustworthy. A stratified or paired analysis might
then be more appropriate in these cases. A More subtle issue is risk exposure. A vehicle is only at
risk of a culpable crash when it is driven. The risk exposure also depends on driving locations and
conditions. A vehicle driven to work every day during rush hour is at greater risk than one driven
once a week on Sunday morning. It is unclear if adequate data can be obtained to adjust for these
factors but they could have a big impact on the results. Drivers using multiple vehicles or vehicles
driven by multiple drivers is another issue. This introduce a correlation into the data that needs
to be taken into account. If there are several such vehicles or drivers in the data and the repeated
measures are properly adjusted for, the results of the analyses could be quite different. Again it is
unclear if such data is available.
Overall, the ICBC report suggests that RHD vehicles and their operators are at a greater risk
than their LHD counterparts but issues with the data and the analyses suggest that further study
is needed. Causation is difficult to establish with observational data. I would caution the use of
the ICBC report as anything more than an indication that further study is needed.
6
reminds me of my friends uncle who works for GM as a sales guy
"why the hell are people buying imports (japanese and european lhd cars), theyre hurting the god damn economy!! taking jobs away from hard working canadians!! YOU SHOULD BUY A DOMESTIC, IMPORTS SHOULD STAY WHERE THEY CAME FROM."
this guy cant be reasoned with, ive tried. getting the same vibe from this amy person
reminds me of my friends uncle who works for GM as a sales guy
"why the hell are people buying imports (japanese and european lhd cars), theyre hurting the god damn economy!! taking jobs away from hard working canadians!! YOU SHOULD BUY A DOMESTIC, IMPORTS SHOULD STAY WHERE THEY CAME FROM."
this guy cant be reasoned with, ive tried. getting the same vibe from this amy person
I also work at gm and we have on average 150 appointments a week for recalls only. Quality made vehicles for sure.
With all the rules they have already I'm surprised they even still let RHD vehicles be driven here. These days any added risk is usually met by just banning it. In reality it's the easiest option, there's so few people that drive them here that no one's going to give a shit except the small minority who's voices might get a two minute segment on the news.
to be fair, 50% of those are toyota ECM from the vibe
not alot here-- they've been mostly malibus, cobalts, cadillac has a tiny recall for torquing a tie rod nut back on, a few trucks here and there and impalas
reminds me of my friends uncle who works for GM as a sales guy
"why the hell are people buying imports (japanese and european lhd cars), theyre hurting the god damn economy!! taking jobs away from hard working canadians!! YOU SHOULD BUY A DOMESTIC, IMPORTS SHOULD STAY WHERE THEY CAME FROM."
this guy cant be reasoned with, ive tried. getting the same vibe from this amy person
I can't stand people who say that kind of ignorant shit, especially when most Japanese "imports" are made in Canada/USA by domestic workers...
Is right hand drive that bad?
Isn't it more dangerous to drive beater with bad brakes/tires than a car with right hand drive?
I would say ban poorly maintained vehicles.
Also when you talk about accidents, what's the biggest cause?
DUI, texting, retarded old farts driving, dumb teenagers driving, street racing, doing burnouts, running red lights, making illegal turns, changing lane without shoulder check, poor physical condition(eye sight/hearing), etc...
It's NOT the car, it's the driver that is causing accidents the most.
In Japan, it's much harder to get a driver's license. Typically the training cost is $3000-$4000. They take driving more seriously and you can't ask your parents or buddies that are age of 25 to take you out for a driving lesson.
Same as Germany, you must be trained by professional driving instructor that is approved by government.
lol at pages 2 and 3:
tl;dr:
1) underscore posts valid argument
2) invisiblesoul fails underscore and posts his own valid argument
3) underscore fails invisiblescore
4) repeat steps 1-3
summary of the summary from CA_FTW's post:
- The problems with the other two analyses are more subtle and technical. The drive configuration of the vehicle was not evenly distributed between gender and age.
- Although the model adjusted for these factors, imbalance can still affect the estimates in the model. If the data had been matched on age and gender, the results would be more trustworthy.
- Overall, the ICBC report suggests that RHD vehicles and their operators are at a greater risk than their LHD counterparts but issues with the data and the analyses suggest that further study is needed. Causation is difficult to establish with observational data. I would caution the use of the ICBC report as anything more than an indication that further study is needed.
I don't know why they even bother banning them.. Just give let ICBC insure them base on their accident rates.. If they get into more accidents, then let the rate reflect the risk.
I don't know why they even bother banning them.. Just give let ICBC insure them base on their accident rates.. If they get into more accidents, then let the rate reflect the risk.
This. ICBC has demonstrated in the past that they care more about profits over safe driving and collision prevention (hello, Chinese DL controversy) to the point that they are willing to go toe-to-toe with the RCMP over it.
I don't see why the RHD situation is any different.
Oh wait, the lower value of RHD cars and scarce availability of replacement parts...
Is right hand drive that bad?
Isn't it more dangerous to drive beater with bad brakes/tires than a car with right hand drive?
I would say ban poorly maintained vehicles.
Also when you talk about accidents, what's the biggest cause?
DUI, texting, retarded old farts driving, dumb teenagers driving, street racing, doing burnouts, running red lights, making illegal turns, changing lane without shoulder check, poor physical condition(eye sight/hearing), etc...
It's NOT the car, it's the driver that is causing accidents the most.
In Japan, it's much harder to get a driver's license. Typically the training cost is $3000-$4000. They take driving more seriously and you can't ask your parents or buddies that are age of 25 to take you out for a driving lesson.
Same as Germany, you must be trained by professional driving instructor that is approved by government.
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what a boring bitch
