macroMIDAS: calculates macroscopic traffic variables

In arwasayegh/mdep: midas data extraction and pre-processing

Description

calculates macroscopic traffic variables of average flows, average speeds, average occupancies, and average densities from lane flows and lane speed data and removes all per lane data if cut.macro is set to TRUE. NOTE: Speeds per lane are based on the arithmetic mean of individual vehicles, not the harmonic mean. So average speeds at the end are the time-mean speeds rather than space-mean speed. It is hard to derive space-mean speeds when all we have is arithmetic means especially during congested conditions where speed variance is very high.

Usage

macroMIDAS(x, cut.macro = TRUE, replace.zero.spd = NULL, ..., 
	lane.nr = "Number.of.Lanes", speed.lane = "Speed.Lane",
	spd.method = "weighted",
	flow.cat = "Flow.Category", flow.lane = "Flow.Lane", 
	occ.lane = "Occupancy.Lane", hw.lane = "Headway.Lane")
	

Arguments

x	object of class 'midas' and flow/speed data per lane
cut.macro	logical whether to remove per lane data or not. Default to TRUE
replace.zero.spd	the method to replace zero speeds in each lane. currently only replaceZeroNaMIDAS to replace by NA. Default to NULL
...	additional arguments to replaceZeroSpd()
lane.nr, speed.lane, flow.cat, flow.lane, occ.lane, hw.lane	character. part of the flow per category/flow per lane/speed per lane/occupancy per lane/headway per lane column names which distinguish them from other columns
spd.method	character. method for calculating average speed "weighted" for weighted arithmetic average speed "non-weighted" for arithmetic average speed "harmonic" for approximate harmonic average speed as suggested by Poole and Kotsialos (2012, 2016). Default to "weighted".

Value

midas object with the traffic.data element modified. Macroscopic variable added. average flows over all lanes in vehicles per hour average flows per lane in vehicles per hour per lane average speeds in km per hour average occupancy in percentage average densities over all lanes in vehicles per km average densities per lane in vehicles per km per lane

References

##need to add ref

Examples

## Not run: 
#md is a one .csv data set you've downloaded
ex <- datetimeMIDAS(x = md)
ex <- cutTimeMIDAS(x = ex, start.time = 9, end.time = 10)
ex1 <- macroMIDAS(x = ex , cut.macro = FALSE)
ex2 <- macroMIDAS(x = ex, cut.macro = FALSE, spd.method = "harmonic")
plot(ex1$traffic.data$avg.spd, ex2$traffic.data$avg.spd)
plot(ex1$traffic.data$avg.den, ex2$traffic.data$avg.den)

## End(Not run)

arwasayegh/mdep documentation built on May 20, 2019, 1:27 p.m.