Subject | Computer Technology | Pages | 1 | Style | APA |
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Question
A response paper on state farm
From the State Farm: Dangerous Intersections case, answer the following questions:
Identify the various constructs and concepts involved in the study.
What hypothesis might drive the research of one of the cities on the top 10 dangerous intersection list?
Evaluate the methodology for State Farm’s research.
If you were State Farm, how would you address the concerns of transportation engineers?
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?
Answer
Identify the various constructs and concepts involved in the study
Whereas constructs extend to actual case, concepts touch on both actual and potential cases (Dwaraki et al., 2019)
Constructs: To rethink and re-do the roads and intersections. This could involve creating a traffic light at the four way stop. Alternatively, it could be proper to a dd a stop sign at the intersections that lack them.
Concepts: the company spends or looses more money at the interceptions with more accident occurrences.
What hypothesis might drive the research of one of the cities on the top 10 dangerous intersection list?
A hypothesis to achieve the above would involve choosing a particular interception and analyzing the number of claims that arise from such interception. After successfully choosing such interception, the next stage involves obtaining information from the police and the farm to establish what happened and how they can prevent the same. This enables relevant authorities to take adequate measures from a point of knowledge and understanding rather than speculations.
Evaluate the methodology for State Farm’s research
State farm is involved in a study to unearth and understand the causes and reasons from the increased number of accidents in certain intersections that makes the company to lose huge amounts of money. They believe such understanding would help in reducing such amounts and increase the company`s profitability. Accordingly, in insurance firms, the more the accidents, the more the claims they receive and thus the lesser the profits that they make (Zhang et al., 2017). As such, they believe it is prudent for them to address the issue of accidents in particular areas and intersections and consequently reduce the number of claims. To achieve the same, they collect information from the police and police records, geometric profile of the hot spots and traffic reports which they believe are useful in unearthing the root causes of accidents in those particular spots. As soon as they collect such information, they are sure to do a case-by-case analysis of the intersection to determine whatever they can do to eradicate or significantly reduce the number of accidents that take place in the said hot spots. Accordingly, the police records have the history of accidents that take in the said spot both in figures and facts (Zhang et al., 2017). The police records therefore become imperative in analyzing the causes and reasons why such intersections are notorious at causing accidents. Traffic records also have firsthand information about the accidents in the said intersection and therefore a useful source of information and how to reduce accidents.
If you were State Farm, how would you address the concerns of transportation engineers?
Helping and addressing the concerns of transportation engineers require in-depth analysis of the situation by collecting information from all relevant sources. The police usually have well-researched information about accidents and therefore they would be imperative in helping me understand the situation at the intersections (Li et al., 2018). This is because they collect information from both victims and witnesses. Consequently, the police report would help me to understand the transporters problem before coming up with a solution. Similarly, I would seek expert opinion on the same. Such opinion could be from engineers with long experience on such problems. Also, it would be imperative and important to seek opinion from the transport engineers themselves to understand what the problem could be because they have first-hand information and experience about the said problem. I would then form a committee of experts that would bring all stakeholders to highlight and collect information about the accidents to come up with an advisory on how such problem could come to an end. After receiving the report, I would help the engineers by implementing it to the letter.
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 not use traffic volume counts because it has several disadvantages and shortcomings. First, the method is not practicable and bring several issues especially when traffic is high (Kumar and Kumar, 2018). One of the issues is the fact that has probability of losing count during the day or whenever there is an increased traffic flow and thus it becomes unreliable. Accordingly, the issue at hand requires serious and reliable technology or any other method that would give accurate findings, which traffic volume count fall short of. It brings several eras which if acted upon, might produce undesirable results (Kumar and Kumar, 2018). Given the above, using traffic volume count would not be the best strategy for solving the issues that state farm intends to solve.
Similarly, traffic volume count would not be effective because it becomes ineffective during bad weather. In most instances, automobiles are prone to accidents during bad weather and that is the time when the traffic volume count should give accurate feedback but it becomes unreliable (Kumar and Kumar, 2018). This denies the experts the necessary information they would use to solve the problem. As such, relying on traffic volume count, with all the shortcomings makes it ineffective. Sometime it become difficult to crosscheck and verify the feedback that comes from the traffic volume count (Kumar and Kumar, 2018). With such, ascertaining the accuracy of information that comes from it becomes almost impossible and therefore unreliable.
References
Dwaraki, A., Freedman, R., Zilberstein, S., & Wolf, T. (2019, February). Using natural language constructs and concepts to aid network management. In 2019 international conference on computing, networking and communications (ICNC) (pp. 802-808). IEEE.
Kumar, V., & Kumar, N. (2018). Study of Design Traffic Signal.
Li, Y., Yamamoto, T., & Zhang, G. (2018). Understanding factors associated with misclassification of fatigue-related accidents in police record. Journal of safety research, 64, 155-162.
Zhang, H., Xu, L., Cheng, X., Chen, W., & Zhao, X. (2017, September). Big data research on driving behavior model and auto insurance pricing factors based on UBI. In International Conference On Signal And Information Processing, Networking And Computers (pp. 404-411). Springer, Singapore.