This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Traffic Flow Models TTE 4004 9/28/11 Recap Traffic Stream Parameters Flow, q Speed, u Density, k = = n i i s t n l u 1 1 n i = i h n q = 1 n i = i s n k = 1 n u u n i = i t 1 = q = n t t l u s = &amp; k = n l Recap  Relationships q = uk Traffic Flow Example Assume you are observing traffic in a single lane of a highway at a specific location. You measure the average headway and average spacing of vehicles as 3 seconds and 150 ft, respectively. Calculate the flow, average speed, and density of the traffic stream in this lane. h avg = 3 sec q = 1/3 = 0.333 veh/sec Flow = 0.333 3600 = 1200 veh/hr/ln h q = 1 Traffic Flow Example  Flow Traffic Flow Example  Density s avg = 150 ft K = 1/150 = 0.00667 veh/ft K = 0.00667 5280 = 35.2 veh/mi/ln s k = 1 Traffic Flow Example  Speed q = ku u = q/k u = 1200/35.2 = 34.09 mi/hr Introduction Macroscopic relationships and analyses are very valuable, but A considerable amount of traffic analysis occurs at the microscopic level In particular, we often are interested in the elapsed time between the arrival of successive vehicles (i.e., time headway) Introduction The simplest approach to modeling vehicle arrivals is to assume a uniform spacing This results in a deterministic, uniform arrival patternin other words, there is a constant time headway between all vehicles However, this assumption is usually unrealistic, as vehicle arrivals typically follow a random process Thus, a model that represents a random arrival process is usually needed Introduction...
View
Full Document
 Fall '08
 Staff
 Normal Distribution, Probability theory, λt, traffic flow, Poisson Example

Click to edit the document details