State Farm Dangerous Intersections
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Liberty University *
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600
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Mechanical_engineering
Date
May 11, 2024
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docx
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Uploaded by kgalloway2077
1)
Identify the various constructs and concepts involved in the study.
In this study, the concepts of dangerous intersections and accident severity make up the construct of intersection improvements – i.e., the changes or modifications that should be made to identified intersections in order to reduce future risk of accidents. Further, the concept of State Farm’s market share supports the reliability and comprehensiveness of its data. Although this study occurred decades ago before most vehicles possessed the suite of passive safety features that they do today (e.g., lane keep assist,
blind spot monitoring, etc.), it is still very important to conduct studies on traffic safety on a regular basis. Despite the advancement of passive safety technologies often made standard on modern vehicles, roadway injury is still the 8
th
leading cause of death around the world, as reported by the World Health Organization (Mehdizadeh et al., 2020, p. 1).
2)
What hypothesis might drive the research of one of the cities on the top 10 dangerous intersection list?
As a city included in State Farm’s top 10 most dangerous intersections list, the problem statements are (1) how to improve the intersection’s safety without compromising efficiency of traffic flow and (2) how to fund those improvements without deprioritizing or destabilizing other duties of the city’s
budget. With this in mind, a hypothesis from the city’s perspective would be along the lines of: By implementing certain improvements to intersection(s) identified as high-risk by traffic studies, there will be a reduction in the
number of accidents that occur at the intersection(s). With grants available for such improvements, the burden on the city’s budget will remain immaterial
. While many accidents occur due to human behavior, there are other modern studies that support the idea of studying the safety of roads themselves. This is what Zheng et al. (2021) aimed to achieve in their study on traffic conflicts, which they defined as “an observable situation in which two or more road users approach each other in space and time to such an extent that there is a risk of collision if their movements remain unchanged” (p. 2). They concluded that while the study of traffic conflicts is not without its own issues, it is important to consider traffic conflicts along with crash data (p. 16).
3)
Evaluate the methodology for State Farm’s research.
The methodology of this research has a lot of strengths. First, State Farm’s research in this study has an unarguable focus on improving road safety by identifying and addressing some top problem intersections throughout the United States. As stated in the study, they modeled their research after the likes of the ICBC and AAA, demonstrating their willingness to learn from practices established by leaders in the industry. By offering to cities grants for not just traffic engineering studies, but also for the construction of improvements, State Farm does a great deal to incentivize cities towards participation and corrective action. By publicly releasing the location of the top 10 most dangerous intersections from this study, State
Farm demonstrates transparency while also spreading awareness – thus holding the affected municipalities accountable.
However, weaknesses exist in the limitations of this study. By excluding accidents that occur at road/highway egresses and access ramps, State Farm
may be forming an incomplete image of key safety issues. Further, by only including accidents in which a State-Farm insured driver was at fault, State Farm is not representing the full spectrum of drivers (namely, uninsured drivers who are at fault). State Farm is also not able to capture the population of minor accidents that are resolved between motorists and thus never reported to insurance. I also found the property damage classification index to be a limiting factor – in my opinion, it seems to be too complex in order to be interpreted and/or applied on a consistent basis. Understandably, It can be difficult to obtain a complete and unbiased picture during a study, as evidenced by Ahmed et al.’s (2022) review on global driving and traffic studies. In discussing what may seem like a comprehensive data pool including spot sensors, loop detectors, historical crash data, instrumented vehicles, crash simulators, and microsimulation modeling, the authors stated, “These data sources might not represent the actual driving environment at a trajectory level and might introduce bias due
to their experimental control” (p. 1). These limitations aside, State Farm demonstrates a strong methodology given the time period of the study.
4)
If you were State Farm, how would you address the concerns of
transportation engineers?
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As it may not be difficult to infer, transportation engineers play a pivotal role in road safety. When planning roadway designs, factors such as geometric design, speed control, and flow of traffic are characteristics of top concern with respect to safety (Raheel Shah et al., 2019, p. 202). To alleviate
concerns held by these folks and increase overall willingness to participate, State Farm could offer a long-term, collaborative approach in which the insurer engages engineering teams from the beginning stages of interpreting
data and planning changes all the way through completion of the projects. Throughout the process, State Farm could exercise further due diligence by improving its methodology and offering updated insights with engineering teams as they go. Genesis 2:18 reads, “Then the Lord God said, “It is not good that the man should be alone; I will make him a helper fit for him.” (English Standard Version Bible, 2001). Thus, State Farm would also be demonstrating biblical principles by exercising this level of due diligence.
5)
If you were State Farm, would you use traffic volume counts as part of the 2003 study? What concerns, other than those expressed by Nepomuceno, do you have?
I would use traffic counts as a means to identify relationships between traffic volume and accident rates. Nepomuceno expresses concerns of low volume roads with few crashes being deprioritized and the effort of processing this extra data. Understandably so, the time and resources needed to process this data would need to be considered. I would also be concerned about the reliability of traffic volume data - yet another aspect
that would require time and resources. In their conclusion on a study of methodology and data uncertainty in road safety analysis, Schlogl and Stutz (2019) advised, “As it is virtually impossible to utterly eliminate uncertainties
from any type of statistical analysis, accident modeling always has to be carried out in due consideration of the limitations imposed by available data themselves” (p. 147). For this reason, description of the raw data used and the efforts which are put in data preparation (including important data processing steps) are a crucial part of any accident prediction model.
References
Ahmed, M. M., Khan, M. N., Das, A., Dadvar, S. E. (2022). Global lessons learned from naturalistic driving studies to advance traffic safety and operation research: A systematic review. Accident Analysis and Prevention, 167
. https://www.sciencedirect.com/science/article/pii/S0001457522000045
English Standard Version Bible. (2001). Bible Gateway. https://www.biblegateway.com/passage/?
search=Genesis+2%3A18&version=ESV
Mehdizadeh, A., Cai, M., Hu, Q., Alamdar Yazdi, M. A., Mohabbati-Kalejahi, N., Vinel, A., Rigdon, S., Davis, K. C., and Megahed, F. M. (2020). A review of data
analytic applications in road traffic safety. Part 1: Descriptive and predictive modeling. Sensors, 20
(4). https://www.mdpi.com/1424-8220/20/4/1107
Raheel Shah, S. A., Ahmad, N., Shen, Y., Kamal, M. A., Basheer, M. A., and Brijs, T. (2019). Relationship between road traffic features and accidents: An application of two-stage decision-making approach for transportation
engineers. Journal of Safety Research, 69
. https://www.sciencedirect.com/science/article/pii/S0022437518301142
Schlogl, M. and Stutz, R. (2019). Methodological considerations with data uncertainty in road safety analysis. Accident Analysis and Prevention, 130
. https://www.sciencedirect.com/science/article/pii/S0001457517300519
Zheng, L., Sayed, T., and Mannering, F. (2021). Modeling traffic conflicts for use in road safety analysis: A review of analytic methods and future directions. Analytic Methods in Accident Research, 29
. https://www.sciencedirect.com/science/article/pii/S2213665720300324
REPLY 1
Hi Austin,
I see your point on the timing of State Farm’s release of the top 10 most dangerous intersections data in relation to the concern of transportation engineers. However, I think it is important that State Farm released this information as early as it did for several reasons. First and foremost is driver safety – if drivers see an intersection that is part of their commute on this list, they are enabled to plan alternate routes and avoid potential future accidents until revisions are built. Second is accountability – both on the part of State Farm and the local transportation engineers. You
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see, State Farm could be viewed as culpable for accidents that occur in the top 10 intersections during the study period if it was found that they had this
data but made no effort to communicate it publicly until later into the study once revision plans were established. By releasing the information when they did, State Farm placed the accountability needed on engineers to ensure their participation and swift resolution to the problem intersections. On the topic of response rates of sample subjects, Yang et al. (2006) acknowledged low response rates as a major weakness in some reviewed literature, thus limiting their reliability and validity (p. 604). While the engineers are not part of any sample in this case, their urgent and willful response to the research problem is still vital to the design of this project. Accountability is a core pillar of the Christian faith, as inferred by Proverbs 27:17, “Iron sharpens iron, and one man sharpens another” (English Standard Version Bible, 2001). In this case, State Farm is imposing accountability – i.e., ‘sharpening’ – the transportation engineers responsible for these areas by putting this data out into the public. While to your point, some public panic and undue stress are possibilities, I believe they are outweighed by the value of individual and group-level accountability. In its inaugural outing, State Farm’s study was bound to carry friction, but both parties can learn from each other in order to make future studies more efficient and less strenuous.
I agree with you that while traffic volume count data may be helpful, it cannot be primarily relied on due to its limitations. As highlighted by
Abdulhafedh (2017), there are a number of non-intrusive traffic count data collection methods that leverage technology such as passive and/or active infra-red sensors, passive magnetic sensors, microwave radar sensors, ultrasonic/passive acoustic sensors, and video image detection (pp. 209 -
210). However, the time and money needed to leverage such data collection
methods would have drug out the length of this study and therefore delayed potentially life-saving improvements to these intersections. Due to these unfortunate limitations, traffic count data must be used sparingly in this case
if at all.
References
Abdulhafedh, A. (2017). Road traffic crash data: An overview on sources, problems, and collection methods. Journal of Transportation Technologies, 7
. https://www.scirp.org/journal/paperinformation?paperid=75975
Yang, Z., Wang, X., and Su, C. (2006). A review of research methodologies in international business. International Business Review, 15
. https://www.sciencedirect.com/science/article/pii/S0969593106000850
REPLY 2
Hi Calvin,
You make a good point on speed as a factor in traffic safety at these intersections. As concluded by Wang et al. (2013) in their review of literature
on road safety, factors such as speed, congestion, and curvature of roadways
need to be researched further since findings from existing literature are inconclusive (p. 272). Given the inclusion of roadway curvature as an inconclusive factor in road safety, I would counter your solution of speed enforcement with a change in the intersections to implement speed reduction by design – that is, making it virtually impossible to exceed speed limits by changing the curvature of roadways approaching intersections or replacing intersections altogether with traffic circles, often referred to as roundabouts. Proverbs 11:14 reads, “Where there is no guidance, a people falls, but in an abundance of counselors there is safety” (English Standard Version Bible, 2001). In my experiences as both a driver who commutes to work 5+ days per week and as a 911 dispatcher who regularly encounters motor vehicle accidents, calls of reckless drivers, and traffic stops conducted by deputies for speeding, I believe that speed limit signs and stoplight cameras are too easy to ignore on both a conscious and subconscious level. However, by changing the design of the roadway itself, engineers can build intersections where drivers are coerced into traveling at safe speeds without sacrificing the time it takes to get from point a to point b in a commute by increasing efficiency in the flow of traffic.
I agree with you on the topic of addressing engineer’s concerns. In their conclusion on a study of global road accident rates, Goniewicz et al. (2016) highlighted the importance of cooperation between politicians, experts, and professionals in order to systematically improve roadway safety
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around the globe (p. 437). To this end, it is crucial that morale for cooperation between State Farm and state/local level governments and engineering teams remains high until the problem is addressed. To your point, I can see the benefit of splitting the project into phases and completing the phases in order of priority (i.e., the ones that will provide the most safety enhancement first). In the Kelly Blue Book / NetConversions case we did an assignment on in this course, they had the advantage of collecting data from a control sample and an experimental sample simultaneously using a website script override method that presented experimental site changes to select users at random. In this case, State Farm and engineering teams don’t have that luxury. Instead, they may benefit from implementing one change – or phase - at a time in order to isolate data by individual changes. While the tradeoff for this is more time allowed for statistically unsafe intersections to see potentially more accidents, it could ultimately lead to a safer design in the end.
References
English Standard Version Bible. (2001). Bible Gateway. https://www.biblegateway.com/passage/?
search=Proverbs+11%3A14&version=ESV
Goniewicz, K., Goniewicz, M., Pawlowski, W., & Fiedor, P. (2016). Road accident rates: Strategies and programmes for improving road traffic safety. European Journal of Trauma and Emergency Surgery, 42
. https://link.springer.com/article/10.1007/s00068-015-0544-6
Wang, C., Quddus, M., & Ison, S. (2013). The effect of traffic and road characteristics on road safety: A review and future research direction. Safety Science, 57
. https://www.sciencedirect.com/science/article/pii/S092575351300060X