The Sinari Blog | Trends in transport and logistics

Reducing Route Driving Time | Sinari

Written by Bernard Augereau | Aug 26, 2026, 9:00:00 AM

Driving time has a direct impact on the cost of a route: fuel, driver hours, and vehicle wear and tear. Reducing it without compromising service levels or violating regulations requires route plans that are both optimized and feasible. This is precisely the role of a route optimization engine—an essential tool for creating truly cost-effective transportation plans.

A powerful and consistent tool for route management

It’s easy to get lost among the features highlighted by TMS software and optimization engines. The key takeaway: this engine—whether offered as an API or natively integrated into the TMS—must be powerful and consistent in managing routes. In particular, it must offer:

  • Detailed mapping: To define a precise route that aligns with customer constraints, the tool must rely on up-to-date maps, ensuring fast routes free of unexpected delays. Pay particular attention to this point when choosing your solution.
  • Data to anticipate traffic: Road freight transport is subject to many uncertainties, including traffic. A good routing engine can manage this constraint and anticipate peak traffic hours, traffic jams, roadwork, and other disruptions that affect delivery times.
  • Accounting for ADR/TMD transport: The transport of hazardous materials is subject to traffic restrictions (certain urban areas and tunnels are off-limits to heavy trucks carrying hazardous goods). The engine must incorporate these restrictions to avoid blocking a delivery—and thus having to reschedule it—which results in longer driving times.
  • Accounting for Low-Emission Zones (LEZs ): There are more than 320 LEZs in Europe, which prohibit the most polluting vehicles from entering—with diesel trucks being specifically targeted. As with ADR regulations, the system must account for these zones to exclude scheduled routes involving vehicles that are not permitted to enter them.
  • Optimizing the grouping of recipients: by analyzing the order pool, the tool groups compatible deliveries into a single route while analyzing their constraints. The number of drivers required decreases, as do driving times, while improving the truck load factor and reducing empty-run miles.
  • Creating more cost-effective routes: the engine automatically incorporates key parameters and actual customer constraints to create the most profitable routes possible. In particular, it reduces costs associated with driving time by optimizing travel time (fewer kilometers, order consolidation, and better anticipation of customer constraints).

Optimized—and, above all, feasible—routes

Thanks to mapping features and other factors (computing power, use of AI), the engine proposes optimized routes (route selection, grouping of recipients, route planning) that are, above all, feasible. It effectively anticipates the constraints and unforeseen issues of each route.

As a result, the driver is not left having to complete an impossible route—the worst-case scenario: detours, delays, or even undelivered orders, which requires rescheduling a delivery and leads to even more driving time.

Route selection isn’t the only factor. A good route plan also takes into account the specific constraints of each customer: choosing the right vehicle (equipment, capacity) and the right driver based on hours already driven, their skills, and any special authorizations (such as an ADR training certificate). Here again, the engine can manage these parameters to minimize driving time as much as possible.

Reducing driving time without violating European social regulations

Reducing driving times only makes sense if the routes remain compliant with the legal framework. Road freight transport is governed by European social regulations (ESR), foremost among which is Regulation (EC) No. 561/2006, supplemented by the Transportation Code. These regulations establish strict rules for drivers of heavy-duty vehicles weighing more than 3.5 metric tons: maximum driving times, break times, and daily and weekly rest periods.

Here are some key points regarding compliance with driving times: a truck driver may not drive for more than 4 hours and 30 minutes continuously without a 45-minute break (which may be split into shorter periods), nor may they drive for more than 9 hours per day (10 hours twice a week), with a standard daily rest period of 11 hours (reduced to 9 hours no more than three times a week) and a standard weekly rest period of 45 hours. For a complete breakdown of driving and rest periods, consult our guide dedicated to European social regulations on driving and rest periods.

A high-performance route optimization engine incorporates these constraints directly into the creation of the transportation plan. It must take into account the hours already worked by each driver (including on-duty time, weekly rest hours, weekly driving hours…), distinguish between short-haul and long-haul profiles (long-haul truckers), and rule out schedules that would result in a violation. The result: a lower risk of exceeding driving time limits, meaning fewer fines and penalties during inspections, as well as better fatigue prevention and improved road safety.

Combined with monitoring via a tachograph or digital tachograph using onboard computing and the driver card, the tool allows for a comparison of planned driving time with actual driving time. The management of driving hours thus becomes a driver of productivity as well as a guarantee of compliance, without having to resort to exemptions every time.

Anticipate, prioritize, and simulate increasingly profitable route plans

An optimization engine helps with planning: for certain industries, it allows the D+1 transport plan to be supplemented with D+2 or D+3 routes, to avoid making multiple trips to the same customer. It also helps the planner better identify priority routes. Depending on the goods and customer constraints, the tool helps the planner choose which orders to process first and reschedule the others. This is no small matter: poor management of priority deliveries leads to the need for chartered freight and spot transport—and thus to additional costs.

The engine goes a step further, as it also serves as a simulation tool. While the planner must work within fixed customer constraints, certain constraints can be lifted and tested through simulations that explore various scenarios: “This customer always receives deliveries in the morning—what if I delivered to them in the afternoon?” What if I had more vehicles authorized to operate in low-emission zones? What if I had more small delivery trucks, or conversely, more semi-trailers? The engine allows you to simulate these scenarios and estimate—backed by consistent data—their impact on route profitability.

When it comes to fleet renewal, these simulations can guide the operator toward a specific type of vehicle. From a scheduling perspective, they can justify relaxing certain time constraints: the identified savings then serve as a basis for discussion with customers to adjust delivery time slots.

FAQ on Reducing Driving Time

How can you reduce driving time on a route? By adjusting several factors simultaneously: choosing the shortest feasible route, grouping compatible orders, reducing empty-run mileage, and better anticipating customer constraints. A route optimization engine automatically balances these parameters.

How can drivers’ driving time be optimized? By assigning routes based on the driving hours each driver has already logged and according to short- or long-distance profiles, so as to make the best use of available time without exceeding regulatory limits.

Is reducing driving time compatible with regulations? Yes . A good engine incorporates driving and rest time rules (Regulation (EC) No. 561/2006) into the creation of the transportation plan, which reduces the risk of violations and penalties while improving profitability.

Conclusion

Reducing driving times isn’t a matter of a single setting, but rather the ability of a tool to simultaneously balance routes, groupings, customer constraints, driving time regulations, and simulation assumptions. It is this combination that transforms unmanaged routes into controlled, compliant, and profitable transportation plans.

Would you also like to reduce driving times on your routes and improve their profitability? The Sinari Optim route optimization engine is designed for just that: Easy to use, it integrates seamlessly into a TMS or ERP system and was developed by a team that understands the specific challenges and constraints of the freight transport industry.

Contact us for more information and a quote tailored to your needs.