DE102023103220A1 - Method for planning an efficient route plan for deliveries and at least semi-autonomous motor vehicles - Google Patents

Abstract

The invention relates to a method for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle (10), in which the route plan is created using an electronic computing device (12), in which successive delivery destinations (14) and associated predetermined delivery time windows (16) for Delivery of respective deliveries are recorded and after a respective delivery destination (14) has been reached, a pending route (18) to the next delivery destination (14) is recalculated, with a travel time required when planning the next route (18) to the next delivery destination (14). (20) is calculated to reach the delivery destination (14) and, depending on the travel time (20), a temporal discrepancy between the calculated travel time (20) and the delivery time window (16) to be reached is calculated as a waiting time (22) or catch-up time (24). during the waiting time (22), the at least partially autonomous motor vehicle (10) being parked in a searched free parking space (24) in the vicinity of the delivery destination (14) to be approached. The invention also relates to such an at least partially autonomous motor vehicle (10).

Description

The invention relates to methods for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle according to the preamble of patent claim 1. The invention also relates to an at least partially autonomous motor vehicle.

In modern supply chain management and logistics, the speed of delivery is an important factor. Efficient and precisely planned delivery has become increasingly important for both retail and industry.

From the U.S. 2019/0346275 A1 already discloses a method for determining a driving guidance policy for a driving between a first location and a second location. The method includes determining targets that include an efficiency target indicative of a desired energy efficiency for the trip and an punctuality target indicative of a desired arrival time at the second location. A driving guidance policy is established based on the targets, the driving guidance policy including recommended actions to be taken along the journey, and each recommended action including a route action and a corresponding speed action.

The object of the invention is to provide a method for planning an efficient route plan and an at least partially autonomous motor vehicle, by means of which delivery time windows for deliveries can be observed particularly efficiently.

This object is achieved by means of a method having the features of patent claim 1 and by means of an at least partially autonomous motor vehicle according to the invention.

Advantageous configurations of the invention can be found in the dependent claims.

A first aspect of the invention relates to a method for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle, in particular using a freight vehicle which exclusively carries out "just-in-time" deliveries, in which the route plan is calculated using an electronic computing device is created in which successive delivery destinations and associated predetermined delivery time windows for delivering respective deliveries are recorded. After a respective delivery destination or delivery location has been reached, a pending route to the next delivery destination is recalculated, with a planned arrival at the next delivery destination being prioritized for the specified delivery time window. This is carried out until the entire route has been processed.

In order to achieve the object of the invention, it is provided according to the invention that, when planning the next route to the next delivery destination, a travel time required to reach the delivery destination is recorded and, depending on the travel time, a time discrepancy between the calculated travel time and the delivery time window to be reached is recorded as a waiting time or catch-up time is calculated. During the waiting time, according to the invention, the at least partially autonomous motor vehicle is parked in a searched free parking space in the vicinity of the delivery destination to be approached. The catch-up time describes the time that the at least partially autonomous motor vehicle needs to make up for lost time in order to reach the delivery time slot on time. The state of the art in the transport of goods by autonomous or at least semi-autonomous motor vehicles is based on the following assumptions, namely that a planner module or the method always wants to choose the shortest way or route and that the optimization when choosing the route between several destinations is time-efficient have to be. According to the invention, however, the procedure is based on the assumption that delivery to a recipient within a specified time window has a higher priority than fuel efficiency or time efficiency. Accordingly, a waiting time must be taken into account, which may arise due to the fact that the delivery process was carried out faster than previously calculated. In order to take the waiting time into account and, for example, not to prevent traffic, the at least partially autonomous motor vehicle is parked in a vicinity of the delivery location, as a result of which energy is also stored particularly efficiently. After the waiting time has expired, the delivery takes place at the correct delivery time window or "just-in-time". Just-in-time (JIT) delivery is an inventory management and logistics strategy whereby the delivery of cargo occurs within a specific delivery time window, minimizing warehousing costs for both the carrier and the recipient. When delivering multiple goods or deliveries in just-in-time mode, a carrier must meet pre-agreed delivery times or delivery windows for all delivery dates for all customers and accommodate multiple loads on a single trip to make each trip more efficient and economical. This could lead to a situation where a regular driving pattern or the shortest route to the next destination would not be preferable, for example when the time between two consecutive deliveries is greater than the time taken by one would require normal driving on the shortest route. In such a situation, a large truck cannot park and wait anywhere, since there is a lack of such parking facilities, especially in urban areas. A human driver would use their practical sense to drive with appropriate behavior or choose an appropriate route in such cases. For at least partially autonomous trucks, it is possible using the method according to the invention to carry out a clearly defined behavior model and route planning in order to cope with such scenarios.

In an advantageous embodiment of the invention, it is provided that the waiting time is searched for a free parking space at another location within the route as a stopover. Places are primarily sought in which the waiting time is used as efficiently as possible, for example a charging station for charging at least partially autonomous vehicles.

In a further advantageous embodiment of the invention, it is provided that a less efficient route is planned for the waiting time and/or the speed is adjusted in order to reach the next delivery destination at the desired delivery time. From a large number of routes suggested by means of an arranged navigation system, that one is selected whose arrival time corresponds at least partially with the desired time window. Alternatively, the speed can also be throttled in such a way that the arrival time also corresponds at least partially with the desired time window.

In yet another advantageous embodiment of the invention, provision is made for traffic information to be taken into account when planning the shortest route to the next delivery destination. In the event of increased traffic, the delay tolerance can be taken into account when calculating the arrival time, which means that reaching the desired time window is more accurate, regardless of traffic influences.

Finally, another advantageous embodiment of the invention provides that the electronic computing device uses optimization algorithms to calculate an efficient or shortest route to the next delivery destination in order to reach the next delivery destination in an adjustable time window. This means that in addition to recording traffic information, for example, weather-related influences, times, delivery priorities, working hours, etc. are also included in the calculation, with optimization algorithms being used for the calculation. Alternatively, artificial intelligence can also be used.

A second aspect of the invention relates to an at least partially autonomous motor vehicle with an electronic computing device for carrying out a method for planning an efficient route plan for deliveries using the at least partially autonomous motor vehicle according to the first aspect.

In other words, the at least partially autonomous motor vehicle prepares for successive just-in-time deliveries. After completing a delivery, the route planner calculates alternative routes and the desired speed to reach the next destination at the scheduled time. The at least partially autonomous motor vehicle selects the most suitable route using the method according to the invention, the route and the speed with which the at least partially autonomous motor vehicle reaches the next destination exactly in the planned time window.

First, sequential destination planning is done, and the key requirement for just-in-time delivery is the creation of a sequential delivery schedule, which defines the order in which cargo deliveries are made to each destination. With the help of various optimization methods, an efficient route plan can be created that adheres to the time window for delivery for the individual shipments and at the same time is as fuel- and time-efficient as possible for the delivery vehicle.

• - Parken und Warten an der aktuellen Position:
  • Wenn es erlaubt ist, wird der wenigstens teilautonome Kraftwagen am aktuellen Standort parken und warten, bis der Zeitpunkt erreicht ist, der es dem wenigstens teilautonomen Kraftwagen ermöglicht, den effizientesten Weg zum nächsten Ziel in der geplanten Zeit einzuschlagen. Angenommen, es handelt sich um einen Kundenstandort, ist diese Option möglicherweise nicht immer möglich.
• - Parken und Warten an einer Zwischenstation:
  • Wenn es auf dem Weg zum nächsten Ziel einen Parkplatz gibt, der einen als großes Transportfahrzeug ausgebildeten, wenigstens teilautonomen Kraftwagen aufnehmen kann, dann würde der wenigstens teilautonome Kraftwagen zu dem Parkplatz fahren und dort warten. In städtischen Gebieten könnte es jedoch schwierig sein, einen solchen Parkplatz zu finden.

Furthermore, an interim route planning takes place, in which, as soon as a delivery has taken place, the at least partially autonomous motor vehicle recalculates the route in order to reach the next destination within the previously agreed delivery time window. If the at least partially autonomous motor vehicle can reach the destination in the planned delivery time window using the most efficient or shortest route, then it chooses this route with the help of the available optimization algorithms. However, if it turns out that the most efficient way would lead to reaching the destination before the planned delivery window, then this would be a violation of the just-in-time delivery model, which is why the at least semi-autonomous motor vehicle chooses one of the following three options:

• - Parking and waiting at the current position:
  • If allowed, the at least semi-autonomous vehicle will park at the current location and wait until the time is reached that allows the at least semi-autonomous vehicle to take the most efficient route to the next destination in the scheduled time gen. Assuming it is a customer site, this option may not always be possible.
• - Parking and waiting at an intermediate station:
  • If there is a parking space on the way to the next destination that can accommodate an at least partially autonomous motor vehicle configured as a large transport vehicle, then the at least partially autonomous motor vehicle would drive to the parking space and wait there. However, in urban areas it might be difficult to find such a parking space.

Finally, a less efficient route and/or speed is selected, in which case the at least semi-autonomous vehicle chooses a route that is not the shortest or most efficient, but this route would allow the next destination to be reached within the specified delivery time window. This could also mean that the semi-autonomous vehicle has to drive slower than normal to reach the delivery window. When calculating the time required, the method also takes possible traffic congestion into account.

Thus, this method allows certain real limitations to be taken into account when planning a route. What is particularly advantageous here is that this method enables at least semi-autonomous motor vehicles to make just-in-time deliveries, especially if the shortest route to each destination does not match the delivery schedules. In addition, this method enables at least semi-autonomous vehicles to choose suitable routes if it is not possible to wait near the delivery location.

In summary, the method enables optimized route planning for the scheduled delivery of goods by autonomous or at least partially autonomous vehicles.

Further advantages, features and details of the invention result from the following description of a preferred exemplary embodiment and from the drawings. The features and combinations of features mentioned above in the description and the features and combinations of features mentioned below in the description of the figures and/or shown alone in the figures can be used not only in the combination specified in each case, but also in other combinations or on their own, without going beyond the scope of the leave invention.

• 1 ein Bilddiagramm zur Veranschaulichung eines Verfahrens zur Planung eines effizienten Routenplans für Lieferungen mittels eines wenigstens teilautonomen Kraftwagens; und
• 2 ein weiteres Bilddiagramm zur Veranschaulichung von benötigten Verfahrensschritten für das erfindungsgemäße Verfahren.

show:

• 1 an image diagram to illustrate a method for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle; and
• 2 another image diagram to illustrate the required method steps for the method according to the invention.

In the figures, identical and functionally identical elements are provided with the same reference symbols.

1 shows a diagram to illustrate a method for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle 10. The route plan is created using an electronic computing device 12, in which successive delivery destinations 14a, 14b and associated predetermined delivery time windows 16 for delivering respective deliveries are recorded . After reaching a respective delivery destination 14a, 14b, a recalculation of an upcoming route 18 to the next delivery destination 14b is calculated, in which 1 three different routes 18a, 18b, 18c are calculated with respective different distances. The distance of a first route 18a is 130 km as an example, the distance of a second route 18b is 100 km as an example and the distance of a third route 18c is 150 km as an example. It is provided according to the invention that when planning the next route 18a, 18b, 18c from a first delivery destination 14a to the next delivery destination 14b, a travel time 20 required to reach the delivery destination 14b is calculated. Depending on the travel time 20, a temporal discrepancy between the calculated travel time 20 and the delivery time window 16 to be reached is calculated as a waiting time 22 or catch-up time 24. During the waiting time 22, the at least partially autonomous motor vehicle 10 is parked in a searched free parking space 24 in the vicinity of the delivery destination 14b to be approached. The catch-up time 24 is therefore the time that the at least partially autonomous motor vehicle 10 has to catch up in order to deliver on time. To bridge the waiting time 22, the free parking space 24 is also searched for at a location within one of the routes 18a, 18, 18c as an intermediate stop. Here it is provided that depending on the delivery time window 16, one of the routes 18a, 18b, 18c is selected. Should a waiting time 22 nevertheless be calculated for each route 18a, 18b, 18c, then that route which has the shortest waiting time 22, for example, is selected.

To bridge the waiting time 22, for example, a less efficient route 18a, 18b, 18c is planned and/or the speed of the at least partially autonomous motor vehicle 10 is adjusted, as a result of which reaching the delivery time window 16 is prioritized. It is also possible to capture traffic information and into the to be taken into account when planning the next route 18a, 18b, 18c to the next delivery destination 14b. Finally, it is also possible to use the electronic computing device 12 to apply optimization algorithms to calculate an efficient or shortest route 18a, 18b, 18c to the next delivery destination 14b in order to reach the next delivery destination 14b in the delivery time window 16. It is also possible, for example, to select the route 18a, 18b, 18c with the longest waiting time 22 in order to use the waiting time 22 as the loading time for loading the at least partially autonomous motor vehicle. Other options are also possible.

2 shows another image diagram, namely a flow chart, to illustrate the required method steps for the method according to the invention.

After a start 26 of the method, an input 28 of the delivery destinations 14a, 14b and the respective delivery time window 16 is required. A first calculation 30 of an efficient route plan for deliveries using the at least partially autonomous motor vehicle 10 is calculated using the input 28 . A first query 32 follows, in which it is queried whether it is possible for the shortest route 18b to reach the next delivery destination 14b within the desired delivery time window 16 . If yes (YES), then a selection 34 is made in which the shortest route 18b to the next delivery destination 14 is selected. A delivery 36 of the delivery and thus an end 38 of the delivery then take place.

If there is a no (NO) in the first query 32, a second query 40 takes place, in which it is queried whether during the waiting time 22 the at least partially autonomous motor vehicle 10 can be parked in a searched free parking space 24 in the vicinity of the delivery destination 14b to be approached. If yes (YES), the at least partially autonomous motor vehicle 10 is parked and the waiting time 22 is bridged. A selection 34 is then also made here, in which the shortest route 18b to the next delivery destination 14 is selected. The delivery 36 and thus the end 38 of the delivery then take place.

If there is another No (NO), this time in the second query 40, a third query 44 takes place, in which it is queried whether the free parking space 24 at a location within the route 18b can be used as a stopover to bridge the waiting time 22 can. If yes (YES), the stopover is stored in order to bridge the waiting time 22 at the given point in time, then the selection 34 is also made here, in which the shortest route 18b to the next delivery destination 14 is selected. The delivery 36 and thus the end 38 of the delivery then take place.

If there is another no (NO), this time in the third query 44, the second calculation 48 takes place, in which the route 18a, 18c that is not the shortest can be selected, but which allows the at least partially autonomous motor vehicle 10 to reach the delivery time window 16 in good time. In order to make this possible, a third calculation 50 is also carried out, in which a speed adjustment for reaching the delivery destination 14b is calculated. The delivery 36 and thus the end 38 of the delivery then take place.

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• US 2019/0346275 A1 [0003]

Claims (6)

Method for planning an efficient route plan for deliveries using an at least partially autonomous motor vehicle (10), in which the route plan is created using an electronic computing device (12), in which successive delivery destinations (14) and associated predefined delivery time windows (16) for delivering respective deliveries are recorded and after a respective delivery destination (14) has been reached, a pending route (18) to the next delivery destination (14) is recalculated, characterized in that when planning the next route (18) to the next delivery destination (14), a required travel time ( 20) is calculated to reach the delivery destination (14) and, depending on the travel time (20), a temporal discrepancy between the calculated travel time (20) and the delivery time window (16) to be reached is calculated as a waiting time (22) or catch-up time (24). , wherein during the waiting time (22) the at least partially autonomous motor vehicle (10) is parked in a searched free parking space (24) in the vicinity of the delivery destination (14) to be approached. procedure after claim 1 , characterized in that to bridge the waiting time (22) the free parking space (24) is searched for at a location within the route (18) as an intermediate stop. procedure after claim 1 or 2 , characterized in that to bridge the waiting time (22) a less efficient route (18) is planned and/or the speed of the at least partially autonomous motor vehicle (10) is adjusted. Method according to one of the preceding claims, characterized in that traffic information is recorded and taken into account when planning the next route (18) to the next delivery destination (14). Method according to one of the preceding claims, characterized in that optimization algorithms for calculating an efficient or shortest route (18) to the next delivery destination (14) are used by means of the electronic computing device (12) in order to get the next delivery destination (14) in the delivery time window (16) to reach. At least semi-autonomous motor vehicle (10) with an electronic computing device (12) for carrying out a method for planning an efficient route plan for deliveries using the at least semi-autonomous motor vehicle (10) according to a preceding one Claims 1 until 5 .

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