ID 83497
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Ahmad, Saifizul Abdullah University of MaLaya
Content Type
Thesis or Dissertation
This study attempts to explore empirically how gross vehicle weight (GVW) will affect
traffic flow characteristics in both free-flow and vehicle following situations. The success
of the study is highly dependent on the empirical data provided by the traffic datacollection
Currently, many kinds of systems or devices are available which measure or monitor or
enforce traffic dedicatedly. The use of these dedicated or nonintegrated systems or
devices in traffic data-collection or monitoring and traffic enforcement is useful in certain
application, especially when only dedicated parameter is considered.
However, these devices may have limited measurement capabilities and unsuitable for
this study, where the devices are incapable of simultaneously measuring all essential
traffic and vehicle parameters such as speed, headway as well as weight in real-time. The
use of these dedicated devices for this study will result in data inconsistency and
incomprehensive measurable traffic parameters.
Thus, a comprehensive and continuous traffic data-collection system based on weigh-inmotion
technology has been developed and installed at one of the federal roads in
Malaysia for study purposes. The developed system is capable of simultaneously and
continuously measuring large sample and all essential traffic and vehicle parameters in
real-time. It also uses the minimum number of sensors necessary to provide the maximum
number of various traffic and vehicle parameters.
Statistical analysis was then performed to the collected data to quantify that the gross
vehicle weight can have a significant effect in traffic flow characteristics in both free
flow and following situations. The results lead to explore the driver behavior in
controlling the vehicle from two different perspective: driver’s visual input and vehicle
dynamics capability.
The first empirical analysis results showed that statistically for each type of heavy vehicle,
there was a significant relationship between free flow speed of a heavy vehicle and its
GVW. Specifically, the results suggest that the mean and variance of free flow speed
decrease with an increase GVW by the amount unrelated to size and shape for all GVW
range. Then, based on the 85th percentile principle, this study proposed a new concept for
setting differential speed limit for heavy vehicle by incorporating GVW where a different
speed limit is imposed to the heavy vehicle according to its GVW.
The second empirical analysis results showed that how GVW of following vehicle and
size of leading vehicle will affect the driver behavior in controlling their speed under
different compositions of leader-follower pairs in a car-following situation. The main
findings of this study are when we incorporate the vehicle dynamic’s capability in a carfollowing
situation, the GVW of following vehicle and the size of leading vehicle were
significant sources of variation in following vehicle speed and relative speed, and their
interaction influence the driver behavior in controlling the speed.The third study investigated empirically how different composition of leader-follower
pairs will affect time headway with the focus on following vehicle (FV) GVW and
leading vehicle (LV) size. The results from statistical analysis were quite revealing in
terms of quantifying that the GVW of FV and the class of LV were a significant source of
variation in time headway. Based on these empirical results, the study suggests a
preferred minimum headway model from driver perspective incorporating heavy vehicle
size and GVW. The proposed model also suggests the selection of the optimum value of
preferred minimum headway based on percentile value if human reaction time, public
support and traffic flow interference are to be considered.
Based on these empirical analyses, it can be concluded that, the main findings of this
study are when we incorporate the vehicle dynamics capability in a traffic flow study, the
gross vehicle weight should be considered as one of the variable of interests to obtain
more rational results.
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Doctor of Engineering