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From page 117... ... Guide to Truck Activity Data for Emissions Modeling F-1 Appendix F Case Study #6: Truck Activity Analyses from Localized Fleet Telematics Data F.1 Emissions Model Inputs Supported • Starts per vehicle (by hour of day and weekday/weekend) Read the entire page →
From page 118... ... Guide to Truck Activity Data for Emissions Modeling F-2 Table F.1 Summary of Start, Soak Time, and Hotelling Inputs in Case Studies MOVES Input/Data Table User Input or Data Table? StreetLight Case Study #3 Vnomics Case Study #4 Vnomics Case Study #6 Total daily hotelling hours User input (hotelling importer) Read the entire page →
From page 119... ... Guide to Truck Activity Data for Emissions Modeling F-3 In Case Study #4, the project team used data from 300 trucks to develop truck hotelling activity inputs for MOVES. MOVES defines hotelling as "any long period of time that drivers spend in their vehicles during mandated down times during long distance deliveries by tractor/trailer combination heavy-duty trucks." (U.S. Read the entire page →
From page 120... ... Guide to Truck Activity Data for Emissions Modeling F-4 30°F10; more likely to have hotelling activities with engine on in order to keep the cabin warm) and May 2017 (milder air temperature with an average of 50 – 60°F; less likely to need heater) Read the entire page →
From page 121... ... Guide to Truck Activity Data for Emissions Modeling F-5 Figure F.1 Data Bounding Box and County Boundary of Denver, Colorado Map source: Google Maps. Figure F.2 Data Bounding Box and County Boundary of Norfolk, Virginia Map source: Google Maps. Read the entire page →
From page 122... ... Guide to Truck Activity Data for Emissions Modeling F-6 Figure F.3 Number of Trucks in Vnomics Datasets by Vehicle Model Year F.5 Data Processing and Analysis The raw data obtained included a number of data files containing second-by-second time stamp, latitude, longitude, vehicle speed, accelerator pedal position, fuel rate, engine RPM, total distance (vehicle odometer) , and reference torque, as well as the make, model, and year of the vehicle. Read the entire page →
From page 123... ... Guide to Truck Activity Data for Emissions Modeling F-7 The project team applied the following data analysis steps: 1. Removed data files where one or more of the following data fields is missing -- time stamp, latitude, longitude, vehicle speed, and RPM. Read the entire page →
From page 124... ... Guide to Truck Activity Data for Emissions Modeling F-8 F.6 Findings from Sample Data F.6.1 Summary Statistics Table F.4 summarizes the number of vehicles, data files, and trips in the datasets. Observations from this table include: • There are many more trucks in the Denver datasets than in the Norfolk dataset. Read the entire page →
From page 125... ... Guide to Truck Activity Data for Emissions Modeling F-9 Figure F.5 Start Locations for Denver Datasets Background image: Google Earth. Figure F.6 Start Locations for Norfolk Dataset Background image: Google Earth. Read the entire page →
From page 126... ... Guide to Truck Activity Data for Emissions Modeling F-10 F.6.2 Starts per Vehicle To compute starts per truck per hour, the vehicle population needed to be defined. As discussed in Case Study #3, it is not entirely clear what is meant by "vehicle population" for bounded modeling domains when vehicles migrate in and out of the domain over the course of the day. Read the entire page →
From page 127... ... Guide to Truck Activity Data for Emissions Modeling F-11 combination short-haul trucks. It is obvious that the numbers of starts per vehicle derived from Vnomics data are much lower. Read the entire page →
From page 128... ... Guide to Truck Activity Data for Emissions Modeling F-12 Figure F.9 Starts per Truck (Heavy-Duty) by Hour of Day during Weekend F.6.3 Start Operating Mode The start operating mode input for MOVES is in the form of a two-dimensional distribution of the number of starts by hour of day and soak period. Read the entire page →
From page 129... ... Guide to Truck Activity Data for Emissions Modeling F-13 Figure F.10 Start Operating Mode Distributions for Denver during Weekday for January and May 2017 Figure F.11 shows the comparison of start operating mode distributions during weekdays between Denver and Norfolk. The distribution for Denver is based on the data for both months combined, and thus, has a very similar pattern to those shown in Figure F.10. Read the entire page →
From page 130... ... Guide to Truck Activity Data for Emissions Modeling F-14 Figure F.11 Start Operating Mode Distributions during Weekday Figure F.12 Start Operating Mode Distributions during Weekend Soak Period 3 18 45 75 105 240 540 720 Sum 20.4 47.9 13.1 5.7 3.2 7.6 1.1 1.0 100 Hour 1 0.0 0 0 0 0 0 0 0 0.0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0.3 0.0 0.1 0.0 0.0 0 0.0 0.0 0.0 5 0.3 0.1 0 0.1 0.0 0.1 0.1 0 0 6 0.8 0.2 0.2 0.1 0.1 0.1 0.2 0 0 7 1.4 0.3 0.6 0.2 0.1 0.1 0.1 0.1 0 8 2.4 0.5 1.1 0.4 0.2 0.1 0.1 0.1 0.0 9 5.7 0.7 2.8 0.8 0.4 0.2 0.6 0.2 0.0 10 8.5 1.3 3.8 1.1 0.6 0.3 1.1 0.4 0.0 11 10.5 1.8 5.1 1.0 0.6 0.3 1.3 0.3 0 12 11.5 2.4 5.5 1.3 0.5 0.4 1.4 0.1 0.0 13 11.8 2.3 6.2 1.5 0.5 0.3 0.9 0.1 0.0 14 11.6 2.2 6.3 1.4 0.6 0.4 0.7 0 0.0 15 11.2 2.5 5.6 1.6 0.6 0.3 0.6 0 0.1 16 10.2 2.3 4.7 1.5 0.8 0.5 0.3 0.0 0.1 17 6.7 1.6 3.1 1.2 0.5 0.1 0.1 0 0.1 18 3.3 0.9 1.6 0.5 0.1 0 0.0 0 0.1 19 1.4 0.4 0.5 0.2 0.1 0 0 0 0.2 20 0.7 0.3 0.3 0.1 0.0 0 0 0 0.1 21 0.4 0.2 0.1 0 0.0 0 0 0 0.0 22 0.4 0.1 0.2 0.1 0.0 0.0 0 0 0.0 23 0.4 0.2 0.1 0.1 0.0 0 0 0 0 24 0.1 0.0 0.1 0 0 0 0 0 0.0 Sum 100 100 Denver/Weekday Soak Period 3 18 45 75 105 240 540 720 Sum 19.7 43.3 14.0 5.7 4.4 9.2 0.4 3.3 100 Hour 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 7 0.2 0 0 0 0 0 0 0.2 0 8 0.4 0 0 0 0 0.2 0.2 0 0 9 2.9 0 2.1 0.4 0.2 0 0.2 0 0 10 10.9 2.3 5.4 0.6 0.4 0.6 1.5 0.2 0 11 14.6 3.6 6.7 1.0 0.8 0 2.5 0 0 12 13.0 2.3 6.1 1.7 0.8 0.8 1.1 0 0.2 13 11.7 2.5 5.2 1.7 0.6 0.8 1.0 0 0 14 10.9 1.3 5.7 1.9 0.2 0.8 1.0 0 0 15 10.2 2.1 4.0 1.7 0.8 0.4 0.6 0 0.6 16 7.5 1.9 3.4 1.3 0.2 0.2 0 0 0.4 17 5.4 1.3 1.9 0.8 0.2 0 0.2 0 1.0 18 1.9 0 0.8 0.4 0 0.2 0 0 0.6 19 4.0 0.4 1.0 1.0 0.4 0.2 0.6 0 0.6 20 1.9 0 0.4 0.8 0.2 0.4 0.2 0 0 21 1.5 0.6 0 0.4 0.6 0 0 0 0 22 2.1 0.8 0.2 0.4 0.6 0 0.2 0 0 23 1.0 0.6 0.4 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 Sum 100 100 Norfolk/Weekday Soak Period 3 18 45 75 105 240 540 720 Sum 25.0 25.0 0 0 0 0 25.0 25.0 100 Hour 1 25.0 25.0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 5 25.0 0 25.0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 10 25.0 0 0 0 0 0 0 0 25.0 11 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 23 25.0 0 0 0 0 0 0 25.0 0 24 0 0 0 0 0 0 0 0 0 Sum 100 100 Denver/Weekend Soak Period 3 18 45 75 105 240 540 720 Sum 0 0 0 0 0 0 0 0 0 Hour 1 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 7 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 11 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 13 0 0 0 0 0 0 0 0 0 14 0 0 0 0 0 0 0 0 0 15 0 0 0 0 0 0 0 0 0 16 0 0 0 0 0 0 0 0 0 17 0 0 0 0 0 0 0 0 0 18 0 0 0 0 0 0 0 0 0 19 0 0 0 0 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 21 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 Sum 0 0 Norfolk/Weekend Read the entire page →
From page 131... ... Guide to Truck Activity Data for Emissions Modeling F-15 F.6.4 Off-Network Idling This subsection presents the results of off-network idling activities inside the county boundary. Figure F.13 shows a comparison of the percent distributions of idling duration in Denver County between January 2017 and May 2017. Read the entire page →
From page 132... ... Guide to Truck Activity Data for Emissions Modeling F-16 result in having a higher fraction of short soak events as evident in Figure F.16 for Denver County and Figure F.17for Norfolk County. Figure F.14 Off-Network Idling Events during Weekday Figure F.15 Trip Starts versus File Starts per Truck by Hour of Day during Weekday 69 15 12 3 1 0 0 0 0 55 28 12 5 0 1 0 1 0 0 10 20 30 40 50 60 70 80 5-10 10-15 15-30 30-45 45-60 60-90 90-120 120-180 180+ % of Events Idling Duration (min) Read the entire page →
From page 133... ... Guide to Truck Activity Data for Emissions Modeling F-17 Figure F.16 Trip Starts (Left) versus File Starts (Right) Read the entire page →
From page 134... ... Guide to Truck Activity Data for Emissions Modeling F-18 In terms of off-network activities, vehicle speed data (such as from GPS) can be used to identify off-network parking events, which are defined in this case study as truck activity where the second-by-second speed values are lower than 5 mph for a period of at least 5 minutes. Read the entire page →
From page 135... ... Guide to Truck Activity Data for Emissions Modeling F-19 Figure F.18 Off-Network Idling and Parking Events inside Denver County Figure F.19 Off-Network Idling and Parking Events inside Norfolk County 1441 319 240 55 13 5 0 1 0 1641 521 431 127 26 11 1 1 0 0 400 800 1200 1600 2000 5-10 10-15 15-30 30-45 45-60 60-90 90-120 120-180 180+ Count Duration (min) Idling (total = 2,074) Read the entire page →
From page 136... ... Guide to Truck Activity Data for Emissions Modeling F-20 F.6.6 On-Network Idling On-network idling was investigated to help inform future MOVES model development. The entire Denver/Norfolk Vnomics dataset was used in this analysis. Read the entire page →
From page 137... ... Guide to Truck Activity Data for Emissions Modeling F-21 F.6.8 Summary of Findings This case study builds on Case Study #4 by analyzing additional fleet telematics data from Vnomics. The geographic areas and time periods of the new datasets were strategically chosen to allow for comparison with the results of StreetLight data analysis in Case Study #3 and for examination of seasonal differences in truck activity patterns. Read the entire page →
From page 138... ... Guide to Truck Activity Data for Emissions Modeling F-22 • The ratio of engine-on to key-on duration during off-network parking is 0.62 – 0.65 for the three datasets. This factor could be used to estimate the duration of engine-on and the amount of off-network idling based on the key-on duration as calculated from other truck activity datasets with only GPS data. Read the entire page →

From page 117...

... Guide to Truck Activity Data for Emissions Modeling F-1 Appendix F Case Study #6: Truck Activity Analyses from Localized Fleet Telematics Data F.1 Emissions Model Inputs Supported • Starts per vehicle (by hour of day and weekday/weekend)