| Title: | FHWA TPM Score Calculation Functions |
|---|---|
| Description: | Contains functions for calculating the Federal Highway Administration (FHWA) Transportation Performance Management (TPM) performance measures. Currently, the package provides methods for the System Reliability and Freight (PM3) performance measures calculated from travel time data provided by The National Performance Management Research Data Set (NPMRDS), including Level of Travel Time Reliability (LOTTR), Truck Travel Time Reliability (TTTR), and Peak Hour Excessive Delay (PHED) metric scores for calculating statewide reliability performance measures. Implements <https://www.fhwa.dot.gov/tpm/guidance/pm3_hpms.pdf>. |
| Authors: | Mark Egge [aut, cre] |
| Maintainer: | Mark Egge <[email protected]> |
| License: | Mozilla Public License Version 2.0 |
| Version: | 2.0.2 |
| Built: | 2024-11-09 05:23:00 UTC |
| Source: | https://github.com/markegge/fhwa_pm3 |
This dataset provides a crosswalk between state names, postal codes, and FIPS codes. Used by the hpms() function. The variables are as follows:
fips_lookupfips_lookup
A data frame with 56rows and 4 variables:
state name (e.g. 'Alabama')
two character state postal code (e.g. 'AL')
Census Bureau FIPS Code (e.g. 1)
capitalized state name (e.g. 'ALAMABA')
Generate an HPMS submission file in accordance with HPMS Field Manual Supplemental Guidance Requires the scores from score() to be run with verbose = TRUE The reporting year is based on the TMC_Identification year (e.g. use 2021 TMC network for 2021 reporting in 2022) Writes the resulting file to hpms_year.txt
hpms( file, tmc_identification, lottr_scores, tttr_scores, phed_scores = NULL, occ_fac = 1.7 )hpms( file, tmc_identification, lottr_scores, tttr_scores, phed_scores = NULL, occ_fac = 1.7 )
file |
Output file name. This is the HPMS submittal file. |
tmc_identification |
Path to TMC_Identification.csv file provided by RITIS with travel time download |
lottr_scores |
A data.table of LOTTR scores produced using |
tttr_scores |
A data.table of TTTR scores produced using |
phed_scores |
A data.table of of PHED scores produced using |
occ_fac |
Occupancy factor. Default = 1.7 |
No return value, writes file to disk
## Not run: lottr_scores <- lottr("data/All_Vehicles/al_tt_seconds.csv", verbose = TRUE) tttr_scores <- tttr("data/Trucks/aldot_2019_trucks.csv", verbose = TRUE) phed_scores <- phed("Readings.csv", "TMC_Identification.csv", speed_limits = fread("speed_limits.csv"), urban_code = 56139, pm_peak = 3, population = 52898) hpms("hpms_2020.txt", "TMC_Identification.csv", lottr_scores, tttr_scores, phed_scores) ## End(Not run)## Not run: lottr_scores <- lottr("data/All_Vehicles/al_tt_seconds.csv", verbose = TRUE) tttr_scores <- tttr("data/Trucks/aldot_2019_trucks.csv", verbose = TRUE) phed_scores <- phed("Readings.csv", "TMC_Identification.csv", speed_limits = fread("speed_limits.csv"), urban_code = 56139, pm_peak = 3, population = 52898) hpms("hpms_2020.txt", "TMC_Identification.csv", lottr_scores, tttr_scores, phed_scores) ## End(Not run)
Calculate LOTTR given a RITIS NPMRDS export of travel time data. Data is passed in as the path to the csv containing the travel time readings.\ Travel time units must be seconds and averaging should be 15 minutes.
lottr(travel_time_readings = NULL, monthly = FALSE, verbose = FALSE)lottr(travel_time_readings = NULL, monthly = FALSE, verbose = FALSE)
travel_time_readings |
path to RITIS export CSV with 15-minute average readings for all vehicles |
monthly |
TRUE or FALSE specifies if the results should be aggregated by month. If FALSE scores will be computed by TMC for all data in the input file. |
verbose |
Provide diagnostic output and return all calculated values (necessary for |
A data.table of LOTTR scores by TMC
## Not run: lottr("data/All_Vehicles/Readings.csv") lottr("data/All_Vehicles/Readings.csv", monthly = TRUE) ## End(Not run)## Not run: lottr("data/All_Vehicles/Readings.csv") lottr("data/All_Vehicles/Readings.csv", monthly = TRUE) ## End(Not run)
Calculate the CMAQ Traffic Congestion Measure in accordance with
FHWA General Guidance and Step-by-Step Metric Calculation Procedures for National Performance Measures for Congestion, Reliability, and Freight, and CMAQ Traffic Congestion
Requires the speed limits for all TMC segments. Other parameters are optional
and (with defaults supplied from FHWA's guidance). Uses the same travel time readings
file as score(..., metric = "LOTTR"). Outputs annual hours of delay.
phed( travel_time_readings, tmc_identification, speed_limits, urban_code = NA, pm_peak = 3, avo_cars = 1.7, avo_trucks = 1, avo_buses = 10.7, moy_factor = moy_factor_default, dow_factor = dow_factor_default, hod_profile = hod_profile_default, population = NA )phed( travel_time_readings, tmc_identification, speed_limits, urban_code = NA, pm_peak = 3, avo_cars = 1.7, avo_trucks = 1, avo_buses = 10.7, moy_factor = moy_factor_default, dow_factor = dow_factor_default, hod_profile = hod_profile_default, population = NA )
travel_time_readings |
path to readings CSV with 15-minute travel time observations for all vehicles exported from RITIS. |
tmc_identification |
Path to TMC_Identification.csv file provided by RITIS with travel time download. |
speed_limits |
a data.frame-like object with speed limits for all TMCs with format tmc,speed_limit |
urban_code |
optional vector of one (or more) urban_code values. if specified, filters TMCs to the relevant urban_code |
pm_peak |
3 or 4. Peak Period is defined as weekdays from 6 am to 10 am and either 3 pm to 7 pm (3) or 4 pm to 8 pm (4) |
avo_cars |
Average vehicle occupancy for passenger vehicles |
avo_trucks |
Average vehicle occupancy for freight trucks |
avo_buses |
Average vehicle occupancy for buses |
moy_factor |
Month of year traffic adjustment factors for freeways and non-freeway facilities in format month,freeway,non_freeway 1, 0.99, 0.98 ... 12, 1.01, 1.00 |
dow_factor |
Day of week adjustment factors. Monday (2) through Friday (6). Format: day,freeway,non_freeway 2, 1.05, 1.05 ... 6, 1.1, 1.1 |
hod_profile |
Hourly traffic percentages for peak hours. Non-directional. Format: hour,freeway,non_freeway 6,0.045,0.050 ... 18,0.052,0.048 |
population |
Optional population value. If provided, function will print PHED value |
Annual hours of peak hour excessive delay per capita
## Not run: phed(travel_time_readings = "npmrds/all_vehicles_2021/Readings.csv", tmc_identification = "npmrds/all_vehicles_2021/TMC_Identification.csv", speed_limits = fread("birmingham_tmc_speed_limits.csv"), urban_code = 7786, pm_peak = 3, output_file_name = "phed_2021.csv", avo_cars = 1.62, avo_trucks = 1.0, avo_buses = 5.1, moy_factor = fread("birmingham_moy_factors.csv"), dow_factor = fread("birmingham_dow_factors.csv"), hod_profile = fread("birmingham_hod_profile.csv"), population = 752898) ## End(Not run)## Not run: phed(travel_time_readings = "npmrds/all_vehicles_2021/Readings.csv", tmc_identification = "npmrds/all_vehicles_2021/TMC_Identification.csv", speed_limits = fread("birmingham_tmc_speed_limits.csv"), urban_code = 7786, pm_peak = 3, output_file_name = "phed_2021.csv", avo_cars = 1.62, avo_trucks = 1.0, avo_buses = 5.1, moy_factor = fread("birmingham_moy_factors.csv"), dow_factor = fread("birmingham_dow_factors.csv"), hod_profile = fread("birmingham_hod_profile.csv"), population = 752898) ## End(Not run)
Calculate LOTTR / TTTR given a RITIS NPMRDS export of travel time data. Data is passed in as the path to the csv containing the travel time readings. input file must have header and format: tmc_code,measurement_tstamp,travel_time_seconds e.g. > tmc_code,measurement_tstamp,travel_time_seconds > 116-04379,2019-01-01 00:00:00,44.78 > 116-04379,2019-01-01 00:15:00,46.69
score(input_file = NULL, metric, monthly = FALSE, verbose = FALSE)score(input_file = NULL, metric, monthly = FALSE, verbose = FALSE)
input_file |
Path to file containing travel time readings |
metric |
"LOTTR" or "TTTR" |
monthly |
TRUE or FALSE specifies if the results should be aggregated by month. If FALSE scores will be computed by TMC for all data in the input file. |
verbose |
Provide diagnostic output and return all calculated values |
A data.table of LOTTR/TTTR scores by TMC
This package will provides functions needed to calculate PM3 System Reliability and Freight and CMAQ Congestion Federal TPM Performance measures
Note: if your state has a large amount of data, you may encounter a "Error: vector memory exhausted (limit reached?)" error. See this StackOverflow post on resolving: https://stackoverflow.com/questions/51295402/r-on-macos-error-vector-memory-exhausted-limit-reached
The functions
lottr calculated LOTTR metric scores for TMC segments
tttr calculates TTTR metric scores for TMC segments
phed calculates PHED metric scores for TMC segments
hpms generates an HPMS submission file in pipe delimited format
Calculate TTTR given a RITIS NPMRDS export of travel time data. Data is passed in as the path to the csv containing the travel time readings.\ Travel time units must be seconds and averaging should be 15 minutes.
tttr(travel_time_readings = NULL, monthly = FALSE, verbose = FALSE)tttr(travel_time_readings = NULL, monthly = FALSE, verbose = FALSE)
travel_time_readings |
path to RITIS export CSV with 15-minute average readings for trucks |
monthly |
TRUE or FALSE specifies if the results should be aggregated by month. If FALSE scores will be computed by TMC for all data in the input file. |
verbose |
Provide diagnostic output and return all calculated values (necessary for |
A data.table of TTTR scores by TMC
## Not run: tttr("data/Trucks/Readings.csv") tttr("data/Trucks/Readings.csv", monthly = TRUE) ## End(Not run)## Not run: tttr("data/Trucks/Readings.csv") tttr("data/Trucks/Readings.csv", monthly = TRUE) ## End(Not run)