摘要: |
The Fatality Analysis Reporting System database shows that, in stark contrast to the 34-
percent decline in non-motorcyclist crash–related fatalities, motorcyclist crash–related fatalities
were up 86 percent with only three year-to-year declines since 1997, while non-motorcyclist
crash–related fatalities had 13 year-to-year declines since 1997. At the national level, the rate of
motorcyclist fatalities per vehicle mile traveled is 29 times higher than the rate among passenger
car occupants, with overall injury rates approximately five times higher among motorcyclists than
passenger car occupants. Given the frequency of motorcycle crashes and their staggering toll in
terms of loss of life and economic costs across Region 6, there is an urgent need to continue to
work diligently toward driving the frequency of these crashes toward zero. The purpose of this
research is to perform a comprehensive evaluation of crash and operational data to understand
the complex nature of motorcycle crashes in Texas through construction of a motorcycle crash
database and a multi-year analysis of these data in with an emphasis on the prevention of fatal
and incapacitating injury crashes in Region 6. This includes compilation of motorcycle crash
reports in the target area, calculation of crash counts and rates, and identifying road segments
and intersections with highly concentrated motorcycle crashes and the unsafe actions that are
contributing to such crashes. The crash data analysis will include detailed review of the crash
narratives and diagrams as part of the crash database building process to help elucidate the true
causes of the crashes. The evaluation will include operational and physical characteristics of the
crash locations, severity of injuries, environmental conditions, characteristics of motorcyclists, and
road users behaviors as well as the common characteristics of the built environment that
contribute to unsafe actions and conditions. The outcomes of such analysis can be actionable
measures to reduce fatalities and injuries resulting from crashes that involve motorcycles and to
develop regional and state mitigation targets. Moreover, the economic downturn resulting from
COVID-19 pandemic led to a significant drop in travel demand and motorcyclist/driver’s exposure
to collisions but studies suggested that it had a differential impact on different road users. For
example, research on previous economic recessions suggests that these conditions affect the
mental wellbeing of people and consequently their behavior on the road. COVID-19 pandemic
effects in terms of motorists’ behavior, the unusually lower traffic volumes, and road safety in
general are currently unknown, as the unprecedented nature and severity of this pandemic do not
resemble anything seen before. Several research questions may arise on the potential
motorcyclist/driver- and environment-related factors associated with COVID-19 pandemic that
may affect traffic safety during and well after the pandemic. This study will also include an in-depth
analysis aiming at pinpointing variables that may have affected road safety involving
motorcycles during the pandemic. In order to provide an efficient and quick solution to the
problem, the research team aims to carry out the tasks outlined below:
1. The research team will first undertake a thorough review of published literature on
motorcycle safety countermeasures, a review of Intelligent Transportation System
(ITS) and other advanced technologies for motorcycles and other vehicles, an analysis
of motorcycle crash and injury data, and a statewide survey of transportation officials.
Available past research and reports of a related nature, from Texas, Region 6, across
the nation, and internationally, will be reviewed.
2. The research team will compile operational and safety data from sources such as the
Texas Crash Records Information System (CRIS), the national Fatality Analysis and
Reporting System (FARS), which has far more specialized detail on motorcycle
crashes, Texas Department of State Health Services records, and crash narratives as
well as site visits.
3. The research team will use data mining to examine space-time indicators that may
reveal information about the correlation between motorcycle crashes and traffic volumes, common characteristics of the built environment that contribute to unsafe
actions and conditions, and other factors.
4. The research team will use different data collection techniques to understand road
user’s behavior and review crash narratives and diagrams. These observations will
not only be helpful in the analysis of risk factors, but also provide a framework that
guides decision-making throughout the entire process, from identifying a problem to
implementing a countermeasure.
5. The research team will employ three categories of statistical analytical approaches:
descriptive measures, analytical statistics produced by statistical models, and
geospatial plotting and related measures. |