1. A traffic engineer wishes to understand the traffic characteristics on a stretch of rural highway. The Engineer makes a number of observation of speed and density during a typical weekday. The data collected is indicated in the table below:- Speed (km/h.) 60 52 45 31 23 16 7 Density (veh/km) 18 32 41 65 75 90 115
1. A traffic engineer wishes to understand the traffic characteristics on a stretch of rural highway. The Engineer makes a number of observation of speed and density during a typical weekday. The data collected is indicated in the table below:- Speed (km/h.) 60 52 45 31 23 16 7 Density (veh/km) 18 32 41 65 75 90 115
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Transcribed Image Text:Appendix 1
Linear Regression Analysis
If a dependent variable "y" and an independent variable "x" are related by an estimated linear regression
function, then
y = a + bx
The constants a and b could be determined from the following equations:-
a =
And
b
n
i=1.
//=1 Xi =
y - bx
Σï=1 Xi Yi — (C?=1 ×i)(Cï^=1 Yi)
Σ=1x?_(Σ=1*i)"
2
where n = number of sets of observations
Xi =ith observation for x
yi=ith observation for y

Transcribed Image Text:1. A traffic engineer wishes to understand the traffic characteristics on a stretch of rural highway. The Engineer
makes a number of observation of speed and density during a typical weekday. The data collected is indicated
in the table below:-
Speed (km/h.)
60
52
45
31
23
16
7
(a) The speed at capacity.
(b) The density at maximum flow.
(c) The maximum flow.
Density (veh/km)
18
32
41
The formulae for simple linear regression are given in Appendix 1. Assuming that the flow can be modelled
using Greenberg's equation and using the linear regression formulae, calculate the following:-
(d) The space mean speed.
(e) The jam density.
65
75
90
115
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