Annual ESALs from a Truck Count (Truck Factor)

A truck factor is the sum of the load equivalency factors of every axle on a truck: steer, drives, trailer axles, all of them, added up. Multiply it by how many trucks pass in a year and you have the year's ESALs. That is the whole of this page's arithmetic, and the interest is entirely in the factor.

A truck factor is a property of the load, not of the truck. A five-axle semi at 80,000 lb — 12,000 on the steer, 34,000 on each tandem — carries a tabulated factor of about 2.4 ESALs. The same truck running empty is worth something like 0.2, because the load exponent makes an unladen trip almost free. So a corridor's truck factor moves with its commodity mix, with how full the trucks are, and with the ratio of loaded to empty running. A quarry road and a parcel-freight corridor can carry identical truck counts and differ by a factor of five in ESALs.

Do not build a truck factor by summing per-axle fourth powers. Do it to that same 80,000 lb semi and each 34,000 lb tandem comes out at $2 \times (17/18)^4 = 1.59$ instead of the tabulated 1.10, and the truck totals about 3.38 instead of 2.4 — 40% high. That error then propagates untouched through the design-lane split, through the growth factor, and into the thickness. The cause is the one described on the equivalency-factor page: the power form describes a single axle, and the two axles of a tandem share one deflection basin.

Count the trucks properly. AADTT means FHWA vehicle classes 4 through 13 — buses, single-unit trucks and combination trucks — and not pickups, vans or cars. The FHWA Traffic Monitoring Guide (2022, Appendix F), a US Government publication in the public domain, sets out how the counting and classification are meant to be done, including how to expand short counts to annual averages and how to handle seasonal variation. A truck count that has quietly swept in light commercial vehicles will produce a fleet truck factor below 0.15, which is a diagnostic in itself: a fleet of genuine combination trucks does not average that low unless most of it is running empty.

And the best source by a long way is a weigh-in-motion station on the road itself. WIM gives you the actual axle-load distribution rather than a class average, which lets you compute the truck factor instead of borrowing one — and this input is, in most designs, the single largest source of error. A state average, a national default, or a factor lifted from a "similar" corridor are all stand-ins for a measurement. If a project can afford one measurement, this is the one to make. Where WIM data exists, compute the factor separately by vehicle class and weight the classes by the counts, because a single-unit dump truck and a five-axle combination differ by several times and a corridor's mix changes with its economy.