Freight Mobility Trends Report 2019

EXECUTIVE SUMMARY

The Freight Mobility Trends Report 2019 reflects the results of the Freight Mobility Trends (FMT) dashboard, measuring freight performance trends between 2017 and 2019.

The Nation’s highways serve a vital role in moving both people and goods. According to the Bureau of Transportation Statistics (BTS), traffic volume increased 17.9 percent between 2000 and 2018, from 2,747 billion to 3,240 billion vehicle miles traveled.¹

Highways are an integral element of the national, multimodal freight transportation system. Goods movement by truck represents 67 percent of the total domestic tonnage. The Freight Analysis Framework estimates freight tonnage will increase about 37 percent between 2018 and 2045.²

Long-haul freight truck traffic is concentrated on major routes connecting population centers, ports, border crossings, and other major hubs of activity. BTS projects that truck travel may increase from 311 million miles per day in 2015 to 488 million miles per day by 2045, a 60 percent increase. With projected growth in travel, the Nation’s highways will continue to experience even greater demand.³

To address this increase in transportation, decision makers should ensure transportation funding is allocated toward projects that provide maximum benefit. To do this, decision makers need information on performance of the transportation system so that they can optimize investments and operational strategies to address congestion and reliability. Decision makers also need to understand the results of improvements to identify whether or not the investment or operational strategy is working as expected. To be able to effectively plan for, improve, and operate the transportation system, there needs to be ways to comprehensively monitor and assess transportation performance and mobility trends.

The Federal Highway Administration’s FMT dashboard provides high-level, national trends in freight mobility and assesses freight movement over a range of locations based on truck travel data:

• Measures of freight mobility at the national, State, regional, or corridor level.
• Freight mobility around major ports, intermodal facilities, and border crossings.
• Identification of freight bottlenecks.

Freight Performance Trends

In general, freight performance between 2017 and 2019 showed the following results:

• Freight performance experienced minimal change over the past few years because overall results are stable.
• Performance worsened slightly between 2017 and 2018 but then improved for 2019.
• Most regions and facilities showed improvement for freight performance in 2019. This is likely being driven by urban area performance.
• Interstates worsened from 2017 to 2019 based on delay per mile (DPM), 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.
  • 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.

The following sections provide results for the different geographic ranges and locations.

National Trends

• At the national level, freight mobility trends had the following results:
• There were slight changes from 2017 to 2019, with some seasonal fluctuations (table 1).
• Freight performance worsened for many locations in 2018 but improved in 2019 (table 1).

Table 1. National Highway System performance by year.

Year	DPM (Truck Hours/Mile)	Total Delay (Annual Truck -Hours)	TTI	PTI	TRI	BI Percent
2019	1,528	656,454,567	1.17	1.61	1.19	30
2018	1,597	716,282,120	1.17	1.62	1.20	31
2017	1,570	696,394,350	1.17	1.61	1.19	30

Key: delay per mile (DPM), travel time index (TTI), planning time index (PTI), truck reliability index (TRI), buffer index (BI)

For specific indicators, the following results show that:

• Freight mobility at the national level worsened slightly from 2017 to 2018 in terms of total delay and truck hours of delay per mile but improved between 2018 and 2019 (figure 1).
• TTI, PTI, and TRI also worsened slightly between 2017 and 2018 but improved slightly between 2018 and 2019 (figure 1).

Figure 2 shows performance for States and regions based on delay per mile:

• States, urban areas, metropolitan planning organizations (MPOs), and freight facility areas (airports, ports, rail intermodal facilities, and border areas) all worsened from 2017 to 2018.
• All improved from 2018 to 2019.

National-Level Urban and Rural Roadways

The performance of urban and rural roadways between 2017 and 2019 shows that (table 2):

• Freight performance worsened more for urban roadways than rural roadways.
• Urban roadways experienced higher levels of congestion or delay and unreliability than rural roadways.
• While most delay was observed on urban roadways, there was slight worsening for both urban and rural roadways from 2017 to 2018.
• Urban roadways showed slight improvements for delay per mile, total delay, PTI, TTI, and BI in 2019.
• Though performing better than urban roadways, rural roadway performance declined from 2017 to 2019.

Table 2. Performance by urban and rural roadways.

Year	Geography	DPM (Truck Hours/Mile)	Total Delay (Annual Truck Hours)	TTI	PTI	TRI	BI
2019	Urban	2,947	529,573,837	1.25	1.91	1.28	44
	Rural	508	126,880,730	1.09	1.28	1.10	15
2018	Urban	3,109	589,799,212	1.25	1.93	1.29	45
	Rural	489	126,482,908	1.08	1.26	1.09	14
2017	Urban	3,065	571,631,761	1.25	1.93	1.29	45
	Rural	485	124,762,589	1.08	1.25	1.09	14

Key: delay per mile (DPM), travel time index (TTI), planning time index (PTI), truck reliability index (TRI), buffer index (BI)

Trends by Functional Classification

Different types of performance issues occur for the various roadway types on the National Highway System (NHS) at the national level (figure 3, figure 4, and table 3):

• The Interstate system had greater truck hours of delay, likely due to higher volumes and increased peak-period congestion, but tended to have more reliable travel times.
• Non-Interstate freeways and NHS arterials had lower delay but were less reliable.
• NHS arterials were less reliable than freeways.
• There was minor fluctuation in mobility and reliability indicators for NHS roadways from 2017 to 2019.
  • The PTI decreased for NHS arterials and worsened slightly for Interstates.
  • The TRI improved slightly for NHS arterials and just slightly increased for Interstates.
  • The TTI improved for NHS arterials and slightly increased for Interstates.
  • These fluctuations were minimal but showed a small decline in reliability for the Interstate and a slight improvement in reliability for NHS arterials.
  • These fluctuations were minimal but show a small decline in reliability for the Interstate and a slight improvement in reliability for other NHS arterials.

Table 3. Yearly performance by National Highway System road type.

Year	NHS Road Type	DPM (Truck Hours/Mile)	Total Delay (Annual Truck Hours)	TTI	PTI	TRI	BI Percent
2019	Interstate	2,438	2345,38,841	1.1	1.37	1.15	20
	Freeway	1,633	64,444,025	1.18	1.66	1.23	34
	NHS Arterial	1,216	357,471,701	1.33	2.15	1.28	53
2018	Interstate	2,398	240,104,851	1.1	1.36	1.15	20
	Freeway	1,687	70,483,132	1.17	1.66	1.23	34
	NHS Arterial	1,323	405,694,137	1.34	2.19	1.29	54
2017	Interstate	2,249	220,337,091	1.09	1.34	1.14	19
	Freeway	1,738	71,683,844	1.18	1.66	1.23	34
	NHS Arterial	1,329	404,373,415	1.34	2.20	1.30	54

Key: delay per mile (DPM), travel time index (TTI), planning time index (PTI), truck reliability index (TRI), buffer index (BI)

The following results show national-level performance trends by quarter for roadway type by functional class and area (urban or rural) (figure 5):

• Urban interstates showed much greater delay per mile and seasonal fluctuation.
• National-level and urban NHS arterials improved in delay per mile in 2019, while national-level and urban Interstates and freeways worsened for delay per mile.
• All roadway types except rural showed increases in delay per mile in the second quarter each year.

Freight Performance by State and Region

The Freight Mobility Trends Report 2019 summarizes freight performance by State, urban area, and MPO region.

State-Level Results

Most States had improved or mixed results for freight performance between 2018 and 2019. Figure 6 shows a map of States that represents whether the States worsened or improved by aggregating performance for the indicators of delay per mile, total delay, TTI, PTI, and TRI. Freight performance in the States is scored for the number of measures that improved or worsened. Based on this analysis:

• A few States showed consistent improvements or worsening across all measures.
• States that improved for most indicators include Georgia, Illinois, New York, and South Carolina.
• States that worsened for most indicators include those in the Midwest with Idaho, Nebraska, Oklahoma, and Wyoming worsening more than others. West Virginia was also among States with the worst freight performance from 2018 to 2019.

As shown in figure 6, States that had consistent improvements in most indicators between 2018 and 2019 include:

• 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.

National Performance Measure for Truck Travel Time Reliability

The national performance measure to assess freight movement on the Interstate is the truck travel time reliability (TTTR) index under 23 CFR 490.607. The TTTR index measures the reliability or consistency of truck travel times on the Interstate over the course of a year. The national TTTR index measured over the entire Interstate system increased from 1.36 in 2017 to 1.39 in 2019. Figure 7 shows the percent change in TTTR by State between 2017 and 2019 and the results for each State are in table 4.

Table 4. Truck travel time reliability index reported by States from 2017 to 2019.

State	Baseline Year TTTR Index (2017 Data)	Year 1 TTTR Index (2018 Data)	Year 2 TTTR Index (2019 Data)	2017–2019 TTTR Index Year Change
Alaska	1.84	1.72	1.79	-3%
Alabama	1.19	1.21	1.22	3%
Arkansas	1.20	1.21	1.21	1%
Arizona	1.18	1.18	1.24	5%
California	1.69	1.72	1.71	1%
Colorado	1.37	1.38	1.45	6%
Connecticut	1.79	1.78	1.81	1%
District of Columbia	3.37	3.33	3.54	5%
Delaware	2.05	1.95	1.91	-7%
Florida	1.43	1.42	1.45	1%
Georgia	1.44	1.43	1.44	0%
Hawaii	2.75	2.92	2.46	-11%
Iowa	1.12	1.14	1.19	6%
Idaho	1.20	1.18	1.20	0%
Illinois	1.30	1.33	1.33	2%
Indiana	1.23	1.21	1.25	2%
Kansas	1.14	1.15	1.18	4%
Kentucky	1.24	1.33	1.24	0%
Louisiana	1.32	1.36	1.35	2%
Massachusetts	1.84	1.89	1.84	0%
Maryland	1.88	1.90	1.86	-1%
Maine	1.23	1.23	1.27	3%
Michigan	1.38	1.40	1.44	4%
Minnesota	1.43	1.45	1.48	3%
Missouri	1.25	1.28	1.30	4%
Mississippi	1.13	1.13	1.14	1%
Montana	1.22	1.22	1.23	1%
North Carolina	1.39	1.41	1.43	3%
North Dakota	1.15	1.15	1.17	2%
Nebraska	1.10	1.12	1.15	5%
New Hampshire	1.35	1.38	1.38	2%
New Jersey	1.82	1.89	1.89	4%
New Mexico	1.13	1.13	1.18	4%
Nevada	1.28	1.27	1.28	0%
New York	1.39	1.43	1.47	6%
Ohio	1.33	1.37	1.36	2%
Oklahoma	1.22	1.21	1.22	0%
Oregon	1.39	1.34	1.37	-1%
Pennsylvania	1.35	1.39	1.36	1%
Rhode Island	1.72	1.79	1.79	4%
South Carolina	1.34	1.36	1.33	-1%
South Dakota	1.14	1.16	1.19	4%
Tennessee	1.35	1.37	1.35	0%
Texas	1.40	1.43	1.44	3%
Utah	1.21	1.20	1.25	3%
Virginia	1.48	1.58	1.55	5%
Vermont	1.69	1.68	1.75	4%
Washington	1.63	1.61	1.54	-6%
Wisconsin	1.16	1.26	1.24	7%
West Virginia	1.21	1.27	1.29	7%
Wyoming	1.19	1.18	1.21	2%

Key: truck travel time reliability (TTTR)

Urban Areas

Figure 8 shows the delay per mile for the urban areas throughout the United States. Delay per mile appears highest in areas such as the Northeast, California, and coastal Louisiana.

Metropolitan Planning Organization Areas

Figure 9 shows the performance of MPO areas for delay per mile in 2019. Similar to urban areas, MPO areas reflect higher delay per mile in areas such as the Northeast, California, and coastal Louisiana. Because MPO regions include some rural counties, the delay per mile results may appear lower.

Figure 10 shows the comparison of delay per mile for States, urban areas, and MPO areas by quarter. Urban areas exhibit higher delay per mile than MPO areas, but the trend is the same for all three. All three show increases in the second quarter of each year. Urban performance appears to drive overall performance.

National Freight Highway Bottlenecks

The FMT was used to identify major freight highway bottlenecks and congested corridors based on annual truck hours of delay per mile.

Figure 11 shows the top 100 Interstate bottlenecks and congested corridors in the United States in 2019. Of the 100 bottlenecks mapped, table 5 lists the top 25 with the greatest truck hours of delay per mile. These NHS locations have high truck volumes and congestion that present a significant cost to Interstate freight flows.

Table 5. Top 25 generalized bottleneck corridors with the greatest truck hours of delay per mile.
Note: The full list of the top 100 can be found in Appendix B.

Rank	Road	Urban Area	State
1	I-95/I-295	New York–Newark	New York/New Jersey
2	I-90/I-94	Chicago	Illinois
3	I-605	Los Angeles–Long Beach	California
4	I-35	Austin	Texas
5	I-610	Houston	Texas
6	I-678	New York–Newark	New York
7	I-405	Los Angeles–Long Beach	California
8	I-290	Chicago	Illinois
9	I-69	Houston	Texas
10	I-278	New York–Newark	New York/New Jersey
11	I-24	Nashville-Davidson	Tennessee
12	I-10	Los Angeles–Long Beach	California
13	I-710	Los Angeles–Long Beach	California
14	I-45	Houston	Texas
15	I-680	San Francisco–Oakland	California
16	I-495	New York–Newark	New York/New Jersey
17	I-5	Seattle-Takoma	Washington
18	I-5	Los Angeles–Long Beach	California
19	I-76	Philadelphia	Pennsylvania
20	I-87	New York–Newark	New York/New Jersey
21	I-105	Los Angeles–Long Beach	California
22	I-75/I-85	Atlanta	Georgia
23	I-10	New Orleans	Louisiana
24	I-10	Lake Charles	Louisiana
25	I-210	Los Angeles–Long Beach	California

Freight Facilities

The FMT was also used to assess mobility on the NHS accessing intermodal locations like airports, ports, intermodal rail facilities, and borders. As shown in figure 12 and figure 13, highways accessing these freight facilities had the following results:

• NHS routes surrounding airports and port areas had the highest mobility challenges. This is likely because these locations tend to be within large urban areas.
• NHS routes surrounding rail intermodal facilities and border areas had lower delay. Rail intermodal facilities are usually sited in less populated areas outside urban boundaries for improved truck access. Most border crossing areas tend to be located in smaller urban areas, and mobility challenges are localized at the crossing.
• In terms of travel time and reliability indicators, highways accessing ports and airports had the highest PTI, closely followed by border areas.
• Airports, ports, and border areas were higher on the three indicators than rail intermodal facilities. This may be due in part to some rail intermodal facilities being located outside major urban areas, whereas major ports and large airports are typically in urban areas.
• Border areas may reflect the delays as a result of border crossing traffic at those locations.

Figure 14 shows the percent change for delay per mile for NHS routes accessing facilities from 2017 to 2018 and 2018 to 2019, with the following results:

• Conditions worsened in 2018 for access to airports and ports.
• All locations improved in 2019.

Figure 15 shows the quarterly comparison of access to freight facilities, with the following results:

• Airports, ports, and rail intermodal areas showed similar trends of increasing delay per mile and second quarter increases in each year.
• Border areas showed a decrease in delay per mile over the years.

Figure 16 shows delay per mile for NHS routes surrounding airports, intermodal rail facilities, ports, and borders. The larger circle sizes reflect greater delay per mile.

Findings for NHS routes surrounding freight facilities include:

• Access to airports in Anchorage, AK, Houston, TX, Chicago, IL, and Los Angeles, CA, improved in 2019. Access to other airports such as Denver, CO, and Ontario, CA, worsened.
• Access to rail intermodal facilities in Shreveport, LA, Elkhart, IN, Jacksonville, FL, and Atlanta, GA, showed improvements in 2019.
• Ports that showed access improvements for 2019 are Duluth, MN, Huntington, (WV) Tri-State, New Orleans, LA, Saint Louis, MO, and Pittsburgh, PA. Those with noticeable worsening access are Baltimore, MD, Chicago, IL, and southern Louisiana.
• Most border areas improved from 2017 to 2019.

Conclusion

The Freight Mobility Trends analysis yields helpful information to aid understanding of dynamics in freight demand on the national transportation system. Increasing demand on the freight transportation system highlights the importance of 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” (Dallas/ Fort Worth, Houston, and San Antonio) and 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 NHS, the 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 MPOs around megaregions can also help support integration of transportation planning with economic development.

This increased demand on the transportation system calls for decision makers to ensure limited public funding is allocated toward projects that provide the maximum benefit. For the U.S. Department of Transportation (USDOT), State DOTs, and MPOs to plan for, improve, and operate the transportation system more effectively, 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.