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21st Century Operations Using 21st Century Technologies

Freight Mobility Trends Report 2019

SECTION 4: DISCUSSION OF FREIGHT PERFORMANCE TRENDS

The Freight Mobility Trends Report 2019 analyzes national trends in highway freight movement between 2017 and 2019. Key findings are as follows:

  • Freight performance experienced minimal change over the past few years because overall results are stable.
  • Performance worsened slightly for 2018 and improved for 2019.
  • Most regions and facilities showed improvement for freight performance in 2019. This is likely driven by urban area performance.
  • Interstates worsened based on delay per mile, but urban Interstates improved in 2019.
  • NHS arterials improved from 2017 to 2019 based on delay per mile.
  • Urban areas exhibited worse freight performance than rural areas. While rural performance showed a worsening trend between 2017 and 2019, urban roadways saw improvement in 2019.
  • Roadway types also differed in freight performance in that:
    • Interstates had greater delay but tended to be more reliable, with many major urban areas being reliably congested during peak periods.
    • National Highway System (NHS) arterials and freeways off the Interstate tended to have less delay but were less reliable than the Interstate.
    • NHS arterials had more challenges with reliability than other roadways.

Considering specific measures of national-level performance, total freight delay and delay per mile (DPM) showed improvement. The travel time index (TTI) had no change, and the planning time index (PTI) and truck reliability index (TRI) decreased only slightly (figure 56).

Comparison charts of five freight performance measures showing most measures worsened between 2017 and 2018 but generally improved in 2019.

Source: FHWA
Figure 56. Chart. National freight performance from 2018 to 2019.

Performance Results by Location

Trends in highway freight mobility for States and other locations showed more variability on the indicators between 2018 and 2019.

State Performance Results

Figure 57 illustrates how freight performed in each State considering a composite of all indicators for the total delay, delay per mile, TTI, PTI, and TRI from 2018 to 2019. Table 34 and the description following details how states performed as shown in figure 57.

To create the composite score, table 34 was used to determine the number of indicators on which a State improved or worsened, which was turned into an indicator to determine the States that are mostly improving or worsening as shown in the map.

U.S. map of state performance either improving or worsening between 2018 and 2019 showing that central plains and mountain west states generally worsened in performance compared to all other states.

Source: FHWA
Figure 57. Map. State performance for indicators from 2018 to 2019.

Table 34. State performance for Freight Mobility Trends indicators from 2018 to 2019.
State Total Delay 2019 Delta Total Delay DPM 2019 Delta DPM TTI 2019 Delta TTI PTI 2019 Delta PTI TRI 2019 Delta TRI
AK 1,088,353 -133,242 316 -39 1.22 -0.06 1.82 -0.19 1.30 0.00
AL 9,570,542 -1,188,509 1,122 -92 1.11 0.00 1.33 -0.01 1.11 0.00
AR 5,754,862 -142,447 877 -1 1.09 0.01 1.26 0.02 1.09 0.00
AZ 9,131,813 -242,586 1,424 -17 1.13 0.00 1.50 0.00 1.20 0.01
CA 96,454,919 -11,700,575 3,505 -311 1.28 0.00 2.09 -0.03 1.32 0.00
CO 10,798,067 -481,942 1,105 -23 1.24 0.02 1.86 0.06 1.26 0.01
CT 5,858,080 -1,001,583 1,974 -215 1.23 0.00 1.88 0.02 1.30 0.00
DC 1,175,278 -360,487 5,064 -680 1.69 -0.01 3.63 -0.06 1.60 0.00
DE 2,376,084 -512,056 2,794 -373 1.26 0.00 1.88 -0.03 1.27 -0.02
FL 40,424,749 -4,424,493 2,475 -56 1.23 0.01 1.83 0.03 1.24 0.00
GA 25,915,822 -3,352,488 1,872 -162 1.19 -0.01 1.68 -0.03 1.22 -0.02
HI N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
IA 4,491,236 -44,142 470 10 1.09 0.01 1.27 0.02 1.10 0.01
ID 2,609,508 100,581 530 24 1.14 0.02 1.46 0.08 1.14 0.01
IL 31,530,659 -4,610,111 2,029 -207 1.16 -0.01 1.59 -0.04 1.19 -0.01
IN 12,991,522 -781,792 1,502 -4 1.10 0.00 1.33 0.02 1.14 0.02
KS 4,408,031 -149,649 501 4 1.12 0.01 1.37 0.04 1.13 0.01
KY 8,614,799 -513,342 1,330 -51 1.11 0.00 1.35 0.00 1.11 -0.01
LA 15,279,657 -1,240,877 2,520 -131 1.15 0.00 1.53 0.01 1.19 0.01
MA 11,055,254 -1,359,580 1,846 -140 1.30 0.00 2.16 -0.01 1.36 -0.01
MD 16,094,250 -903,101 3,912 -72 1.24 0.00 1.91 0.01 1.32 0.00
ME 2,302,860 -92,369 852 -4 1.13 0.01 1.43 0.02 1.16 0.01
MI 11,849,154 -1,401,960 949 -72 1.15 0.00 1.53 -0.03 1.19 0.01
MN 6,454,011 -721,294 627 -36 1.16 0.00 1.56 0.03 1.22 0.01
MO 13,640,467 -963,476 1,209 -15 1.11 0.00 1.39 0.01 1.14 0.00
MS 5,495,147 -98,495 777 6 1.11 0.01 1.34 0.03 1.10 0.01
MT 2,198,000 -62,200 263 -6 1.16 0.01 1.52 0.03 1.18 0.01
NC 12,397,400 -88,2076 1,118 -3 1.15 0.00 1.52 -0.01 1.17 0.00
ND 1,987,627 58,636 273 18 1.14 0.01 1.47 0.02 1.14 0.00
NE 3,287,506 23,590 444 14 1.11 0.01 1.37 0.03 1.13 0.01
NH 2,333,131 -408,017 1,248 -103 1.22 0.00 1.74 0.01 1.21 -0.01
NJ 13,346,439 -2,430,610 2,283 -312 1.27 0.00 1.93 -0.04 1.27 -0.03
NM 7,184,160 -312,827 1,083 -31 1.14 0.01 1.45 0.02 1.13 0.00
NV 3,850,435 -636,758 755 -105 1.16 -0.01 1.55 -0.05 1.19 0.01
NY 34,524,209 -3,633,211 2,208 -128 1.26 -0.01 1.96 -0.05 1.24 -0.01
OH 19,672,512 -329,842 1,475 62 1.11 0.00 1.36 0.01 1.13 0.01
OK 5,919,502 65,179 698 34 1.10 0.01 1.30 0.03 1.11 0.02
OR 10,479,403 -603,307 1,241 -53 1.17 0.01 1.63 0.02 1.22 0.01
PA 22,319,995 -1,572,425 1,582 -53 1.16 -0.01 1.52 -0.02 1.16 0.00
RI 1,494,226 -138,440 1,286 -60 1.28 0.00 2.03 -0.02 1.29 -0.01
SC 12,124,281 -1,146,883 1,706 -97 1.20 -0.01 1.65 -0.04 1.18 -0.02
SD 1,687,408 -29,383 230 2 1.14 0.00 1.45 0.02 1.15 0.01
TN 20,091,704 -1,517,074 1,948 -64 1.14 0.00 1.47 -0.01 1.16 -0.01
TX 62,024,730 -3,579,270 1,804 -38 1.18 0.00 1.65 0.00 1.21 0.00
UT 17,628,037 -1,487,135 3,474 687 1.20 0.01 1.72 0.03 1.21 0.01
VA 12,505,731 -500,801 1,393 6 1.17 0.00 1.63 -0.01 1.19 -0.01
VT 887,700 -50,337 611 -17 1.16 0.00 1.51 -0.03 1.24 0.05
WA 16,652,468 -1,388,305 1,920 -121 1.24 -0.02 1.92 -0.07 1.28 0.00
WI 10,567,814 -1,210,852 958 -61 1.14 0.00 1.45 -0.02 1.15 -0.01
WV 3,900,015 373,613 1,018 129 1.12 0.01 1.38 0.02 1.12 0.01
WY 2,025,010 290,655 324 49 1.10 0.02 1.33 0.07 1.13 0.05

N/A means not applicable. Key: delay per mile (DPM), travel time index (TTI), planning time index (PTI), truck reliability index (TRI), negative blue text indicates improving measures, red italics indicates worsening measures

Most States improved or had mixed results on the indicators. A few States showed consistent improvements or worsening across all indicators, but many showed improvements in the indicators. The following States had consistent improvements in most indicators between 2018 and 2019:

  • Alabama.
  • Alaska.
  • Arizona.
  • California.
  • Connecticut.
  • Delaware.
  • District of Columbia.
  • Georgia.
  • Illinois.
  • Kentucky.
  • Maryland.
  • Massachusetts.
  • Michigan.
  • Missouri.
  • Nevada.
  • New Hampshire.
  • New Jersey.
  • New Mexico.
  • New York.
  • North Carolina.
  • Pennsylvania.
  • Rhode Island.
  • South Carolina.
  • Tennessee.
  • Texas.
  • Vermont.
  • Virginia.
  • Washington.
  • Wisconsin.

The following States had worsening performance in most indicators between 2018 and 2019:

  • Colorado.
  • Idaho.
  • Iowa.
  • Kansas.
  • Maine.
  • Mississippi.
  • Montana.
  • Nebraska.
  • North Dakota.
  • Ohio.
  • Oklahoma.
  • Oregon.
  • South Dakota.
  • Utah.
  • West Virginia.
  • Wyoming.

The following States were neutral for performance meaning that there was improvement for two indicators, worsening for two indicators, and no change for one indicator.

  • Arkansas.
  • Florida.
  • Indiana.
  • Louisiana.
  • Minnesota.

Note that data for Hawaii are not available for 2019.

Table 34 shows the percent change from 2018 for indicators of the total delay, delay per mile, TTI, PTI, and TRI. Blue values (with a minus sign) indicate improving conditions; red italics indicate worsening conditions.

Combined Location Analysis

Throughout this report, delay per mile is the primary ranking measure because it captures the full extent of the congestion problem by capturing truck volume and roadway performance, and delay per mile is normalized by segment length. Considering delay per mile, an overall finding is that the freight locations assessed mostly have similar delay per mile performance patterns over the three-year period except for rural roadways, which show little fluctuation, as shown in figure 58. For all locations except rural freeways and NHS arterials, there appears to be an increase in delay in the second quarter each year. This delay is more pronounced for some of the modal locations like airports, ports, intermodal rail facilities, and urban Interstates. Additionally, locations such as airports, border areas, intermodal rail areas, and urban Interstates show a sharp decrease in delay per mile in the fourth quarter of 2019. This may be related to declines in 2019 for manufacturing and freight shipments.11,12

Multiple line chart of quarterly delay per mile from 2017 to 2019 for all NHS road types by urban/rural classification, states, urban areas, MPOs, the National Highway Freight Network, the Strategic Highway Network, airports, border areas, intermodal rail facilities, and ports.

Source: FHWA
Note: Delay per mile is scaled in order to show multiple location types and their quarterly delay per mile trends.

Figure 58. Graph. Combined delay per mile quarterly analysis by freight facility.

Regional Performance Results (States, Urban Areas, and Metropolitan Planning Organization Areas)

While figure 58 depicts the quarterly performance for delay per mile for the range of locations in the report, figure 59 shows the location types and the percent that worsened or improved. States, urban areas, and Metropolitan Planning Organization (MPO) areas all worsened from 2017 to 2018 but improved from 2018 to 2019.

First set of two pie charts of improving or worsening delay per mile for state freight performance where 61 percent were worsening between 2017 and 2018 and 73 percent were improving from 2018 to 2019. Second set of pie charts of delay per mile for MPO areas where 58 percent worsened between 2017 to 2018 and 60 percent worsened between 2018 and 2019. Third set of pie charts of delay per mile for urban areas where 55 percent worsened between 2017 to 2018 and 76 percent worsened between 2018 and 2019.

Source: FHWA
Figure 59. Pie charts. Location performance of delay per mile from 2017 to 2018 and 2018 to 2019.

Freight Facilities

For NHS routes surrounding facilities, airports and port areas have the highest mobility challenges because these locations tend to be within urban areas. As the national freight statistics reported by the Bureau of Transportation Statistics (BTS) indicate, these facilities are seeing a rise of goods movement, which will mean more trucks in an already congested urban environment. Alternatively, border crossing areas tend to be located in smaller urban areas, and rail intermodal facilities are usually located in less populated areas outside urban boundaries; mobility challenges are localized at the facility.

Figure 60 shows the percent change of delay per mile for the areas our freight facilities. All locations improved from 2018 to 2019.

Bar chart of the percent change in delay per mile for the four freight facility types in 2018 and 2019 showing border areas with the most dramatic improvement in both years while airports and ports worsened between 2017 and 2018.

Source: FHWA
Figure 60. Graph. Percent change of delay per mile for facilities from 2017 to 2018 and 2018 to 2019.

Conclusion

The Freight Mobility Trends (FMT) analysis yields helpful information to aid understanding of dynamics in freight demand on the national transportation system. Increasing demand on the freight transportation system calls for investments in system capacity and operational strategies to address congestion, reliability, and intermodal connectivity. This report highlights challenges and opportunities where improvements can be achieved through a range of suggested strategies.

Demands on the Interstate System from the higher truck and passenger vehicle volumes is evident in the significant amount of delay seen by the data in major urban areas. These freight bottlenecks not only impact mobility, but also have adverse environmental and congestion impacts on local communities. Major freight bottlenecks and congested corridors on the Interstate System tend to be concentrated in megaregions, with Los Angeles, New York, Chicago, Atlanta, San Francisco, and the “Texas-Triangle” having the greatest number of major bottlenecks. While the top 100 freight bottlenecks and congested corridors only make up a little more than 1 percent of the Interstate System, these locations account for 21 percent of total Interstate System truck delay. This underscores the need for targeted, data-driven transportation investments to address congestion and increase the efficiency of freight movements around major centers of industry and trade.

While the Interstate System tends to be more reliable than other parts of the National Highway System (NHS), the Truck Travel Time Reliability (TTTR) index shows a decline in reliability on the Interstate System from year to year, indicating this reliability is gradually worsening as congestion continues to grow. Transportation System Management and Operations (TSMO) initiatives, such as integrated corridor management, managed lanes, work zone management, traffic incident management, and travel demand management, can leverage operational strategies and technologies to optimize existing capacity under the growing demand placed on the Interstate System.

The data show that arterials tend to have more challenges with reliability than other roadways. Upon leaving the Interstate System, freight must travel through congested arterials mixed with traffic interacting with the local street system, further impacting first and last-mile travel to major destinations. This highlights the need for comprehensive management of the system through coordinated planning by State, regional, and local transportation agencies as well as arterial management tools such as traffic signal optimization and access management.

Urban areas tend to have worse freight performance than rural areas in terms of congestion, delay, and unreliability. However, the data also show that rural roadway performance declined from 2017 to 2019. This shows that the impact of growth in travel demand is not just limited to urban areas, but also affects the performance in rural areas. Seasonal fluctuations can be seen in the performance indicators for many States. TSMO initiatives, such as road weather management and incident response, are key to managing these impacts on the rural freight transportation system.

Intermodal connections from highways to ports, rail, and airports are key to an efficient intermodal freight transportation system. The data show that NHS routes surrounding airports and port areas also show mobility challenges. An emphasis on improving intermodal connections to freight facilities is critical to improving access to these major trade gateways and the multimodal freight transportation system's performance.

Freight truck traffic is concentrated on major routes connecting population centers, ports, border crossings, and other major activity hubs. Corridor coalitions and similar coordination between States will continue to address common needs for safe and efficient freight mobility along key corridors supporting economic development. Coordination between States and Metropolitan Planning Organizations (MPOs) around megaregions can also help support integration of transportation planning with economic development.

Increased demand on the transportation system requires decision makers to ensure limited public funding is allocated toward projects that provide the maximum benefit. For United States Department of Transportation (USDOT), State Departments of Transportation (DOTs), and MPOs to effectively plan for, improve, and operate the transportation system, there need to be ways to comprehensively monitor and assess transportation performance and mobility trends. This report provides information that can support national, state, and regional freight transportation planning, programing, and investments. States and MPOs are taking a variety of approaches to address freight mobility based upon local factors. USDOT can support these efforts through the National Freight Strategic Plan, promoting multimodal and operational solutions through programs such as the National Highway Freight Program, and considering freight mobility needs in Federal grant funding through programs such as the Infrastructure for Rebuilding America (INFRA) and other discretionary grant programs.

Highways are an integral element of the national, multimodal freight transportation system. The Nation’s highways serve a vital role in moving both people and goods. Continuous freight mobility measurement will provide important information that can be used in conjunction with other economic and infrastructure condition indicators to understand how to keep freight moving throughout the Nation. This report provides information on the performance of the freight system and insights into needs for planning and coordinating investments to support freight efficiencies.

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