```
#' @title `segment` NDS ping data by adding a trip or shift ID column.
#'
#' @description This function segments NDS ping data to shifts and trips
#' @param speed Real time speed of the ping
#' @param threhold The threshold you want to separate the ping (in minutes). It is recommended to use 30 minutes to separate into trips, and 8*60 minutes to separate into shifts.
#' @param time_diff The time difference between the nearest two pings.
#' @keywords ping
#' @keywords threshold
#' @keywords trip
#' @keywords shift
#' @export
#' @examples segment(dat$speed, 30, d$time_diff)
segment = function(speed, threshold, time_diff, driver) {
orginal_speed = d[,speed]
d1 = d %>%
.[time_diff >= threshold, speed := 0] %>% # 1. Replace large jumps between two !0 speed
.[,.(ping_time, speed, time_diff),.(driver, rleid(speed != 0))] %>%
.[,rleid1 := rleid] %>%
.[,sum_speed := sum(speed), rleid] %>%
.[sum_speed != 0, rleid1 := {rleid1[1] = rleid1[1] - 1L;rleid1}, rleid]
# 2. Mark continuous states (driving or stopping) with "rleid1"
# 3. Length of each state "d2"
g_0 <- d1[,.(N = .N, sumdiff = sum(time_diff), sum_speed = sum_speed[1]), .(driver, rleid)]
g_r <- d1[,.(sumdiff_r = sum(time_diff)), .(driver, rleid1)] %>%
.[,.(driver, rleid = rleid1, sumdiff_r)]
d2 = g_r[g_0, on = c("driver", "rleid")]
d2$sumdiff_r[is.na(d2$sumdiff_r)] = d2[is.na(sumdiff_r),sumdiff]
# 4. Recode 0 speed but the length < threshold to non-zero
d3 = d2 %>%
.[,row_id := sequence(.N),driver] %>%
.[(sum_speed == 0) & (sumdiff_r < threshold) & (row_id != 1), sum_speed := 666] %>%
.[,trip_id := ifelse(sum_speed > 0, 1, 0)] %>%
.[,trip_id1 := cumsum(trip_id), driver] %>%
.[,.(trip_id, new_id = rleid(trip_id), N),driver] %>%
.[,.(trip_id = trip_id[1], N = sum(N)), .(driver, new_id)]
# 5. Index moving trips
d3 %>%
.[,new_id1 := cumsum(trip_id), driver] %>%
.[,new_id1 := ifelse(trip_id == 0, 0, new_id1)]
id = d3[,rep(new_id1, N)]
# 6. Replace leading non-zero speed with the following trip id
jump_speed = which(id == 0 & orginal_speed != 0)
id[jump_speed] = id[jump_speed + 1]
return(id)
}
segment = function(speed, threshold, time_diff, driver) {
orginal_speed = speed
d1 = d %>%
.[time_diff >= threshold, speed := 0] %>% # 1. Replace large jumps between two !0 speed
.[,.(ping_time, speed, time_diff),.(driver, rleid(speed != 0))] %>%
.[,rleid1 := rleid] %>%
.[,sum_speed := sum(speed), rleid] %>%
.[sum_speed != 0, rleid1 := {rleid1[1] = rleid1[1] - 1L;rleid1}, rleid]
# 2. Mark continuous states (driving or stopping) with "rleid1"
# 3. Length of each state "d2"
g_0 <- d1[,.(N = .N, sumdiff = sum(time_diff), sum_speed = sum_speed[1]), .(driver, rleid)]
g_r <- d1[,.(sumdiff_r = sum(time_diff)), .(driver, rleid1)] %>%
.[,.(driver, rleid = rleid1, sumdiff_r)]
d2 = g_r[g_0, on = c("driver", "rleid")]
d2$sumdiff_r[is.na(d2$sumdiff_r)] = d2[is.na(sumdiff_r),sumdiff]
# 4. Recode 0 speed but the length < threshold to non-zero
d3 = d2 %>%
.[,row_id := sequence(.N),driver] %>%
.[(sum_speed == 0) & (sumdiff_r < threshold) & (row_id != 1), sum_speed := 666] %>%
.[,trip_id := ifelse(sum_speed > 0, 1, 0)] %>%
.[,trip_id1 := cumsum(trip_id), driver] %>%
.[,.(trip_id, new_id = rleid(trip_id), N),driver] %>%
.[,.(trip_id = trip_id[1], N = sum(N)), .(driver, new_id)]
# 5. Index moving trips
d3 %>%
.[,new_id1 := cumsum(trip_id), driver] %>%
.[,new_id1 := ifelse(trip_id == 0, 0, new_id1)]
id = d3[,rep(new_id1, N)]
# 6. Replace leading non-zero speed with the following trip id
jump_speed = which(id == 0 & orginal_speed != 0)
id[jump_speed] = id[jump_speed + 1]
return(id)
}
```

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