A real example: The Hume Highway
The Hume Highway in Australia is a good illustration of how truck speed rules work in practice. The road is posted at 110 km/h. A car can travel at that limit without issue. But a 3-axle, 14-pallet rigid truck is classified as a Heavy Rigid (HR) vehicle with a GVM well over 4.5 tonnes, and two rules apply simultaneously:
- Heavy vehicles over 4.5 tonnes GVM are capped at 100km/h under Australian road rules, regardless of the posted speed limit
- That 100 km/h cap applies for the entire route, even on sections of highway where the posted limit is 110 km/h
This is a compound rule, meaning the vehicle type and the road classification interact with each other. The result is a maximum speed that is lower than the sign posted limit, and it applies everywhere on that route.
To see more about Australia's unique delivery landscape and restrictions, read our blog on the topic.
What we tested
To verify how the HERE Routing API handles this, we sent the same segment of the Hume Highway through the API twice: once in car mode, and once in truck mode. The route was 25,066 metres long and got different routes depending on the input:
Car mode: 856 seconds travel time, yielding an effective speed of approximately 105 km/h (base duration 835 seconds, approximately 108 km/h without traffic)
Truck mode: 902 seconds travel time, yielding an effective speed of approximately 100 km/h. The cap was being applied correctly despite the road's 110 km/h posted limit
This confirmed that the API's default truck mode correctly enforces the HR vehicle speed cap. It also confirmed that car mode, as expected, does not apply that cap and will plan routes assuming the full posted speed limit is available.
Why this matters: Safety, accuracy, and realism
Safety first
Routing a truck at car speeds poses a safety issue. If a planner's system assumes a HR truck can travel at 110 km/h on the Hume Highway, drivers may be scheduled into situations where hitting their time windows requires exceeding their legal speed limit. That puts the driver at risk of an infringement, puts other road users at greater risk of a serious crash involving a heavy vehicle, and puts the operator at risk of compliance liability. Speed rules for heavy vehicles exist because physics doesn't negotiate: stopping distances for a loaded rigid truck at 110 km/h are significantly greater than at 100 km/h, and the consequences of a collision at highway speeds are catastrophic.
ETA accuracy
Even a 5-10 km/h speed difference compounds significantly across a long-haul route. On a 500 km Hume Highway run, incorrectly assuming 110 km/h instead of 100 km/h shaves roughly 27 minutes off the modelled travel time. Multiply that across a fleet of vehicles running regional routes daily, and you're building a plan that is systematically too optimistic. The result is missed delivery windows, frustrated customers, drivers under pressure, and planners wondering why their routes never run on time.
The physics of trucks
Trucks accelerate and decelerate very differently from vans or passenger vehicles. A loaded rigid truck merging onto a highway or pulling away from a traffic light takes considerably longer to reach cruising speed in comparison to a car, and requires a much longer braking distance when slowing for a stop. Realistic truck routing accounts for these acceleration and deceleration profiles, producing travel time estimates that reflect how a HR vehicle actually moves through a route rather than how a car would. This matters most in urban and suburban environments, where stop-start conditions dominate and the differences in vehicle dynamics are most pronounced.
The broader complexity
Speed is just one layer. Truck routing also involves road access restrictions (many urban streets are closed to vehicles over a certain length or weight,) bridge height and load limits, turning radius constraints, and loading zone regulations. Each of these rules can vary by state, local council, time of day, and vehicle class. Stacking these constraints correctly, and doing so in real time as routes are optimized across a fleet, requires purpose-built routing logic rather than a generic mapping API call with default settings.
Getting this right isn't an edge case for specialist operators. It's a baseline requirement for any business running HR vehicles on public roads. The Hume Highway experiment is a simple, clean example of a broader principle: The rules governing how a truck can move through the network are genuinely different from the rules governing a car, and your routing engine needs to know the difference.
What this means for route optimization
At Adiona, this kind of thinking is built into how we model routes. We don't treat all vehicles as interchangeable units moving through a network. We apply the correct vehicle class rules, speed caps, and road restrictions for each asset in a fleet, so the routes we produce are ones drivers can actually execute — safely and on time.
If you're running a fleet of HR vehicles and your routing software is treating them like fast cars, you're missing out on accurate ETAs while also building compliance and safety risk into your operations by default, it's a lose-lose outcome. The fix starts with using routing logic that understands what your vehicles actually are.
Test out the Adiona platform completely free for 14 days, to test your actual fleet composition and requirements against Adiona's outputs. Sign up here, we're confident you'll find significant optimizations.
