Bus arrivals independent random variables

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SUMMARY

Bus arrivals are commonly modeled as independent random variables, often utilizing the Poisson distribution. This approach is based on the assumption of no correlation between individual bus arrivals. However, the Poisson distribution may not accurately represent vehicle traffic, particularly for scheduled bus services. It is more effective in scenarios such as emergency ward arrivals during peak hours, as detailed in the referenced paper.

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  • Understanding of Poisson distribution and its applications
  • Knowledge of random variables and their independence
  • Familiarity with statistical modeling in transportation
  • Basic concepts of traffic flow theory
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  • Research the limitations of the Poisson distribution in modeling bus arrivals
  • Explore alternative statistical models for vehicle traffic analysis
  • Study the relationship between scheduled services and random arrival patterns
  • Examine case studies on emergency ward arrival patterns using Poisson processes
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Mark J.
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Hi.
Why in all literature bus arrivals are referred as independent random variables (Poisson as well)?
Is there any reference where there is some math explanation except intuitive approach which of course tell that there is no correlation between 2 bus arrivals?
Best regards
 
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Mark J. said:
Hi.
Why in all literature bus arrivals are referred as independent random variables (Poisson as well)?
Is there any reference where there is some math explanation except intuitive approach which of course tell that there is no correlation between 2 bus arrivals?
Best regards

The Poisson distribution is not a good model for vehicle traffic in general, and I wouldn't expect to be very good for scheduled bus service even though the schedule is often just a suggestion. It does work well in a number of applications including time between emergency ward arrivals during high traffic hours.

http://cs.ucsb.edu/~ravenben/classes/276/papers/pf95.pdf
 
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