A METHOD FOR CONTROLLING VEHICLES IN A MISSION ALONG A ROUTE

Abstract

The invention relates to a method for controlling vehicles (V1-V3) in a mission along a route, comprising—selecting at least two progress control value sets (u, tw), each value set comprising a respective value (u1, u2, u3, tw) of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, —determining, for each of the selected progress control value sets, a respective distribution (SoBfut) of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set (u, tw), so that each progress control value set is correlated to a respective distribution (SoBfut) of the vehicles, —identifying, from the selected progress control value sets, based at least partly on the determinations of the distributions (SOBfut), a progress control value set (u, tw) for controlling the at least one of the vehicles, and—controlling the at least one of the vehicles (V1-V3) according to the identified progress control value set (u).

Claims

1. A method for controlling vehicles in a mission along a route by a control unit arranged to communicate wirelessly with each of the vehicles, characterised by: determining, by the control unit, a desired distribution indicative of gaps between two successive vehicles along the route, selecting, by the control unit, at least two progress control value sets, each value set comprising a respective value of a progress control parameter for at least one of the vehicles, wherein each progress control parameter value influences the rate of progress of the respective vehicle, determining, by the control unit, for each of the selected progress control value sets, a respective distribution of the vehicles, if the at least one of the vehicles is controlled based on the respective selected progress control value set, so that each progress control value set is correlated to a respective distribution of the vehicles, wherein at least one of the determined distributions is at a future point in time, identifying, by the control unit, from the selected progress control value sets, the respective distribution which presents the smallest deviation from the desired distribution, and identifying the progress control value set for controlling the at least one of the vehicles, which corresponds to the identified distribution, and controlling the at least one of the vehicles according to the identified progress control value set, wherein the at least one of the vehicles is controlled based on at least one of the selected progress control variable sets, from a first point in time to the future point in time.

2. A method according to claim 1, characterized in that selecting at least two progress control value sets, and determining, for each of the selected progress control value sets, a respective distribution of the vehicles, comprises selecting a progress control value set, determining a distribution of the vehicles, wherein the at least one of the vehicles is controlled based on the selected progress control value set, and repeating once, or a plurality of times, the progress control value set selection and the vehicle distribution determination.

3. A method according to claim 1, characterized in that the progress control value sets are speed value sets, each speed value set comprising a respective speed value for at least one, preferably more than one, of the vehicles, wherein each speed value set is a control vector indicating, for each vehicle, a condition with no speed change, a condition with a positive speed change, or a condition with a negative speed change.

4. A method according to claim 3, characterized in that each speed value set comprises a respective speed value for all of the vehicles.

5. A method according to claim 1, characterized in that in each progress control value set, each progress control parameter value represents a time interval value for a standstill condition of the respective vehicle.

6. A method according to claim 5, characterized in that the method is carried out upon one of the at least one vehicle approaching a designated waiting area along the route.

7. A method according to claim 5, characterized in that one of the progress control value sets includes a progress control parameter value representing a zero standstill time interval of the respective vehicle, and the remaining at least one progress control value set each includes a progress control parameter value representing a standstill condition during a respective predetermined time interval.

8. A method according to claim 7, characterized in that three or more progress control value sets are selected, wherein, in the remaining at least two progress control value sets, the time intervals are different from one progress control value set to another.

9. A method according to claim 5, characterized in that identifying a progress control value set for controlling at least one of the vehicles, comprises identifying, from the selected progress control value sets, a progress control value set based partly the respective standstill time interval for the at least one vehicle.

10. A method according to claim 1, characterized in that the desired distribution of the vehicles is a distribution where the gaps between the vehicles are equal.

11. A method according to claim 1, characterized in that determining a respective distribution of the vehicles comprises determining a respective state of balance indicating, as a function of the respective progress control value set, a respective deviation of the vehicles, from the desired distribution.

12. A method according to claim 5, characterized in that identifying a progress control value set for controlling at least one of the vehicles, comprises identifying a progress control value set which minimises a function which is a linear combination of the deviation from the desired distribution and the standstill time.

13. A method according to claim 1, characterized in that the mission is a circulating mission.

14. A method according to claim 1, characterized by repeating after a predetermined time interval the steps of selecting progress control value sets, determining a respective vehicle distribution, identifying a progress control value set for controlling the at least one of the vehicles, and controlling the at least one of the vehicles according to the identified progress control value set.

15. A computer program comprising program code means for performing the steps of claim 1 when said program is run on a computer, or a group of computers.

16. A computer readable medium carrying a computer program comprising program code means for performing the steps of claim 1 when said program product is run on a computer, or a group of computers.

17. A control unit, or a group of control units, configured to perform the steps of the method according to claim 1.

18. A vehicle comprising a control unit according to claim 17.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0048] With reference to the appended drawings, below follows a more detailed description of embodiments of the invention cited as examples.

[0049] In the drawings:

[0050] FIG. 1 is a schematic view of three vehicles in a circulating mission.

[0051] FIG. 2 is a diagram depicting steps in a method according to an embodiment of the invention.

[0052] FIG. 3 shows two pairs of diagrams, each depicting vehicle positions and gaps between vehicles in FIG. 1.

[0053] FIG. 4 is a diagram depicting steps in a method according to a general embodiment of the invention.

[0054] FIG. 5 is a diagram depicting steps in a method according to an alternative embodiment of the invention.

[0055] FIG. 6 is a diagram for explaining certain parameters used in the method of FIG. 5.

[0056] FIG. 7 shows diagrams of parameters, as functions of time, in a simulation, using the method described with reference to FIG. 5 and FIG. 6.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION

[0057] FIG. 1 depicts schematically a fleet of heavy-duty vehicles V1, V2, V3 in a circulating mission. In this example, the vehicles are in the form of trucks. However, the vehicles may be of any type suitable for the particular mission. For example, the vehicles may be delivery vans, buses, mining trucks, or cars. In this example, there are three vehicles in the fleet, but there could in principle be any number of vehicles in the fleet.

[0058] The circulating mission involves driving on a route R, from a start and end position S/E, to one or more action positions, in this example three action positions wp1, wp2, wp3, herein also referred to as waypoints, at separate locations, and then back to the start and end position S/E. The route could be in any type of environment, such as urban, rural, or mining. A movement of a vehicle from the start and end position S/E, via the action positions wp1, wp2, wp3, and back to the start and end position S/E, is herein referred to as a cycle.

[0059] The mission could involve one or more activities at each of the action positions wp1-wp3, for example delivery or pick-up of goods or people. It is understood that the mission could involve any number of action positions. The mission could also involve one or more activities at the start and end position S/E, for example fuelling and/or charging of batteries of the vehicles.

[0060] In alternative embodiments, the mission could be, as opposed to circulating, extend from a start position to an end position at a location which is different from that of the start position.

[0061] A control unit CU is arranged to carry out steps of an embodiment of a method according to the invention. The control unit could be a part of a control center for controlling the vehicle fleet. The control unit CU is arranged to communicate wirelessly with each of the vehicles V1-V3.

[0062] The control unit CU may be arranged to receive information from the vehicles, e.g. regarding their positions, and speeds. The control unit may also be arranged to send control commands to the vehicles. In some embodiments, the vehicles are driverless, and control devices (not shown) in the vehicles, which are arranged to control operational devices of the vehicles, such as engines, motors, brakes and steering, may be arranged to read the control commands from the control unit CU. In other embodiments, the vehicles may be arranged to display control commands from the control unit CU, to drivers of the vehicles.

[0063] In some embodiments, the control unit CU could be located on one of the vehicles, or parts of the control unit CU could be distributed on a plurality of the vehicles.

[0064] It is understood that the control unit CU comprise a computer. It is further understood that the control unit CU may be arranged to carry out an embodiment of the method according to the invention, by means of a computer program.

[0065] The distribution of vehicles along the route R is herein also referred to a state of balance SoB of the vehicles. The state of balance could be defined as the difference between the maximum gap between two successive vehicles and the minimum gap between two successive vehicles. I.e.

SoB(t)=max(gap(t))−min(gap(t))  (1)

[0066] Preferably, the gaps are time gaps. However, it is alternatively possible that the gaps are spatial gaps, e.g. distances along the route R.

[0067] Reference is made also to FIG. 2. Embodiments of a method according to the invention comprises determining S1 a desired distribution of the vehicles along the route R. In embodiments, the desired distribution is a distribution where the gaps between the vehicles are equal.

[0068] The positions posi(t) of the vehicles along the route R are determined S2. The speeds of the vehicles may be determined, or set, as reference target speeds vref. The reference target speeds may be predetermined. The respective reference target speed may depend on the position along the route. The reference target speeds may be the same for all vehicles, for any given position along the route. Thus, at any give moment in time, the reference target speed may be different from one vehicle to another.

[0069] From the determined vehicle positions posi(t), a deviation from the desired vehicle distribution is established S3. In other words, the state of balance SoB(t) is determined with equation (1) above. In the example in FIG. 1, the gap between two of the vehicles V1, V2 is too small, and this gap is the minimum gap in equation (1).

[0070] As a first step to reduce the deviation from the desired vehicle distribution, a progress control value set in the form of a speed value set u is selected S4. The speed value set comprises a respective speed value for a plurality of the vehicles, preferably for all of the vehicles. Thus, the respective speed value influences the rate of progress of the respective vehicle. At least one, or some, of the speed value is a speed change value, or an absolute speed value, which is different from the determined or set speed, e.g. the reference target speed vref, of the respective vehicle. In this example, the speed value set is a control vector u indicating, for each vehicle V1-V3, a condition with no speed change 0, a condition with a positive speed change 1, or a condition with a negative speed change −1.

[0071] A position of the respective vehicle, as a result of the respective speed change given by the respective speed value of the speed value set u, can be expressed as

pos.sub.i(t.sub.fut)=pos.sub.i(t)+dt.Math.(v.sub.ref(t)+ε.sub.i)  (2)

[0072] where v.sub.ref is the reference target speed for the vehicle. In this example, the reference target speed is the same for all vehicles, for any given position along the route R. The term ε.sub.i is the speed change given by multiplying the respective speed value ui of the speed value set, with a unit speed change value dv.sub.max. The unit speed change value dv.sub.max may be predetermined. It should be noted that the unit speed change value may depend on the position along the route. The unit speed change value dv.sub.max may be a maximum allowed change of the reference target speed v.sup.ref. The speed change ε.sub.i may be seen as a “disturbance” speed deviation. The purpose of the speed change ε.sub.i is to reduce the gap imbalance SoB. Where the future state of balance is calculated as the minimum gap between the vehicles, reducing the gap imbalance may involve increasing the minimum gap. Thus, a speed change vector may be determined as

ε=dv.sub.max.Math.u  (3)

[0073] where each value u1, u2, u3 in u is either −1, 0, or 1.

[0074] Based on the positions posi(t) of the vehicles, a distribution SoBfut of the vehicles, at a future point in time t+dt, if the vehicles are controlled based on the selected speed value set u, is determined S5. This may be done as follows:

SoB.sub.fut=SoB(t.sub.fut)=max(gap(t.sub.fut))−min(qap(t.sub.fut))  (4)

[0075] where

gap.sub.i(t+dt)=|pos.sub.i+1(t.sub.fut)−pos.sub.i(t.sub.fut)|  (5)

t.sub.fut=t+dt  (6)

[0076] Thus, determining a distribution SoBfut of the vehicles V1-V3, may comprise determining the distribution of the vehicles, if the plurality of the vehicles is controlled based on the selected speed value set u, from a first point in time t to the future point in time t+dt. Thereby a deviation of the vehicles, at the future point in time t+dt, from the desired distribution may be determined.

[0077] FIG. 3 shows, in the two upper diagrams, an example in which the vehicles are evenly positioned. The consequence is equal gaps and a low, or zero, state of balance SoB. In the example in the two lower diagrams, the gaps are not even distributed, the results is a relatively high value of the state of balance SOB. The method evaluates the future consequence of a control action using the speed value set U.

[0078] The steps of selecting S4 a speed value set u, and determining a future distribution SoBfut of the vehicles, with the selected speed value set, is repeated S6 a plurality of times X. At each repetition, a selection of a different speed value set u is made, resulting in a different future distribution SoBfut. The number X of repetitions may be predetermined.

[0079] Thereby, a plurality of speed value sets u is obtained, each correlated to a respective distribution SoBfut of the vehicles, at the future point in time t+dt. The future distributions SoBfut, to which the speed value sets u are correlated, are compared to each other. The future state of balance value minSoBfut which represents the smallest deviation from a distribution where the gaps between the vehicles are equal, is identified. This is the future state of balance which has the lowest value at the calculation according to expression (4) above. The speed value set u which is correlated to the future state of balance value minSoBfut, which represents the smallest deviation from a distribution where the gaps between the vehicles are equal, is identified for controlling the speeds of the vehicles. The speeds of the vehicles V1-V3 are then controlled S7 according to the identified speed value set u.

[0080] In the example described above there is a finite number of possible combinations for the speed value set u. In the initial speed value set selection S4, and in each repetition S6 of selecting a speed value set u, one of these combinations could be selected. The repetition S6 could be terminated when all combinations have been used for a respective state of balance SoB determination. In alternative embodiments, the speed value set u could be selected randomly in the initial speed value set selection S4, and at each repetition.

[0081] The method for identifying a speed value set u for controlling the vehicles, to reduce the distribution imbalance, may be repeated within suitable time intervals, which may be predetermined, such as every 1-10 minute.

[0082] The example above comprises repeating the speed value set selection and the vehicle distribution determination. However, in some embodiments, a plurality of speed value sets may be selected in parallel processes. Also, in some embodiments, the future vehicle distribution determination, for each of the selected speed value sets, may be done in parallel processes.

[0083] Referring to FIG. 4, a general embodiment of the invention will be described. A method for controlling vehicles V1-V3 (FIG. 1) in a mission along a route, comprises the following steps. The positions of the vehicles along the route are determined S2. A plurality of progress control variable sets is selected S4, each progress control variable set comprising a respective progress control variable value related to the rate of progress of a respective of a plurality of the vehicles, wherein the selected progress control variable sets are different from each other. The method further comprises determining S5, for each of the selected progress control variable sets, and based on the determined positions of the vehicles, a respective distribution of the vehicles, at a future point in time, if the plurality of the vehicles is controlled based on the respective selected progress control variable set, so as to obtain a plurality of progress control variable sets, each correlated to a respective distribution of the vehicles, at the future point in time. It should be noted that the step S4 of selecting progress control variable sets does not necessarily have to be finalized, before the step S5 of determining, for each of the selected progress control variable sets, a respective distribution of the vehicles, is commenced. The distributions, to which the progress control variable sets are correlated, are compared, and the progresses of the vehicles are controlled S7 according to a progress control variable set identified based on the comparison.

[0084] Reference is made to FIG. 5. In a further embodiment of the invention, the context is similar to that of the embodiment described with reference to FIG. 1-FIG. 3. Thus, as depicted in FIG. 1, a fleet of heavy-duty vehicles V1, V2, V3 are in a circulating mission, involving driving on a route R, from a start and end position S/E, to three action positions wp1, wp2, wp3, and then back to the start and end position S/E. A control unit CU, arranged to communicate wirelessly with each of the vehicles V1-V3, is arranged to carry out steps of a method according to the further embodiment of the invention. The control unit CU is arranged to receive information from the vehicles, e.g. regarding their positions, and speeds, and the control unit is arranged to send control commands to the vehicles.

[0085] Similar to the embodiment in FIG. 1-FIG. 3, the state of balance SoB(t), i.e. the deviation from the desired vehicle distribution, is defined as the difference between the maximum gap between two successive vehicles and the minimum gap between two successive vehicles, i.e. as expressed by equation (1) above. Preferably, the gaps are time gaps.

[0086] As can be seen in FIG. 5, the method comprises determining S1 a desired distribution of the vehicles along the route R, i.e. a distribution where the gaps between the vehicles are equal. Further, the positions posi(t) of the vehicles along the route R are determined S2.

[0087] As depicted in FIG. 1, a third of the vehicles V3 is approaching a third of the action positions wp3. The third action position includes a waiting area. Thereupon, the following steps are performed:

[0088] A plurality of progress control variable sets are selected S4. In this embodiment, each progress control value set, comprises only one value, herein referred to as a progress control parameter value. The progress control parameter value represents, or is, a time interval value t.sub.w for a standstill condition of the third vehicle V3. Thereby, the progress control value set indicates whether the third vehicle V3 will, in the subsequent vehicle distribution determination, enter a time limited standstill condition. The value also indicates the duration t.sub.w, of the standstill condition. Such a standstill condition may be effected by the vehicle waiting for said duration t.sub.w. Such waiting may be done in the waiting area wp3. In this example, the selected progress control parameter values t.sub.w, are 0, 1, 2, 4, 8, 16, and 32 seconds.

[0089] Reference is made also to FIG. 6, for examples of terms used herein. An active mission time t.sub.nw is understood as a time during which the third vehicle V3 is in a mission, and not controlled to wait. The active mission time t.sub.nw is equal to an actual mission time t.sub.miss if the vehicle is not controlled to wait. A consequence of a control of the third vehicle V3, at a point in time t.sub.wp3 to wait for a time interval t.sub.w is indicated by the dashed line in FIG. 6. A no wait cycle time t.sub.ondoxp is the expected maximum value of the active mission time t.sub.nw, i.e. the time of a cycle of the third vehicle V3, when the vehicle is not controlled to wait.

[0090] Based on the positions of the vehicles V1-V3, a respective distribution of the vehicles is determined S5, for each of the selected progress control parameter values t.sub.nw, if said third vehicle V3 is controlled based on the respective selected progress control parameter values t.sub.w, so that each progress control parameter value t.sub.w is correlated to a respective distribution of the vehicles V1-V3.

[0091] Each vehicle distribution is defined as a future state of balance soB.sub.fut. The respective distribution may be a vector with values that may represent gaps between pars of vehicles. Each distribution may be into a scalar value, in the form of the respective state of balance. In this example, the future state of balance is defined as follows:

SoB.sub.fut=SoB(t+t.sub.w)=max(gap(t+t.sub.w))−min+(gap(t.sub.w))  (7)

[0092] where gap is a vector with elements defined as

[00001]$\begin{array}{cc}{\mathrm{gap}}_i\left(t+t_w\right)=\{\begin{array}{cc}.Math.t_{\mathrm{nwsi}+1}\left(t+t_w\right)-t_{\mathrm{nswi}}\left(t+t_w\right).Math.& \left(t_{\mathrm{mwsi}}\left(t+t_w\right)\ne \max \left(t_{\mathrm{nws}}\right)\right)\\ t_{\mathrm{endexp}}-t_{\mathrm{mwsi}}\left(t+t_w\right)+\min \left(t_{\mathrm{mws}}\right)& \left(t_{\mathrm{mwsi}}\left(t+t_w\right)=\max \left(t_{\mathrm{nws}}\right)\right)\end{array}& \left(8\right)\end{array}$

[0093] where t.sub.nws is a sorted vector, with an ascending order, including the active mission times t.sub.nw of the vehicles V1-V3.

[0094] Thus, determining a distribution SoBfut of the vehicles V1-V3, may comprise determining the distribution of the vehicles, if the plurality of the vehicles is controlled based on the selected progress control parameter values t.sub.w, from a first point in time t to the future point in time t+t.sub.w. As indicated above, one of the selected progress control parameter values t.sub.w is zero, 0, and therefore, the distribution of the vehicles, based on this progress control parameter value, is the vehicle distribution at the first point in time, or the present time.

[0095] Thereby, a plurality of progress control parameter values are obtained, each correlated to a respective distribution SoBfut of the vehicles, at the future point in time t+t.sub.w. The distributions SoBfut, to which the progress control parameter values are correlated, are compared to each other, while taking the respective standstill time under consideration. More specifically, the method comprises identifying S601 a progress control parameter value for controlling the third vehicle V3. This progress control parameter value is identified based partly on the comparison of the distributions, and partly on the respective standstill time interval for the third vehicle V3.

[0096] More specifically, a progress control parameter value is identified, which minimises a function which is dependent on the deviation from the desired distribution, and the standstill time. By minimising said function, a balance is provided between moving towards the desired distribution of the vehicles, and minimising the loss of productivity, due to the standstill condition of the third vehicle V3.

[0097] In this example, said function to be minimised is as follows:

cost(t.sub.w)=t.sub.w+ε(u)  (9)

[0098] where

ε(u)=SoB.sub.fut.Math.ksob  (10)

[0099] An alternative function could be as follows:

[00002]$\begin{array}{cc}\mathrm{cost}\left(t_w\right)=t_w+\mathrm{.Math.}\left({\mathrm{SoB}}_{\mathrm{nw}}\right).Math.{\mathrm{SoB}}_{\mathrm{fut}}\left(t_w\right).Math.\mathrm{ksob}\mathrm{where}& \left(11\right)\\ \mathrm{.Math.}\left({\mathrm{SoB}}_{\mathrm{nw}}\right)=\{\begin{array}{cc}0& \left(.Math.{\mathrm{SoB}}_{\mathrm{nw}}-{\mathrm{SoB}}_{\mathrm{tar}}.Math.<{\mathrm{SoB}}_{\mathrm{devmax}}\right)\\ 1& \left(\mathrm{else}\right)\end{array}& \left(12\right)\end{array}$

[0100] where SoBtar is a desired state of balance, SoBdevmax is a limit for the state of balance, below which the vehicle is not controlled to wait, and

SoB.sub.nw=SoB(t.sub.w=0)  (13)

[0101] It follows from these functions that the third vehicle V3 shall be controlled to wait a relatively short time, or to not wait at all, where the state of balance is relatively close to the desired state of balance. However, the third vehicle V3 may be controlled to wait a relatively long time, where the state of balance is relatively far from the desired state of balance.

[0102] The third vehicle is then controlled S7 according to the identified progress control parameter value.

[0103] Reference is made to FIG. 7. The plots in this figure depict parameters in a simulation done by one of the inventors, using the method described with reference to FIG. 5 and FIG. 6. The simulation includes three vehicles. As can be seen, initially the distribution between vehicles is poorly balanced. After approximately 5 minutes a reasonably good balance is achieved. In this example, the selected progress control parameter values t.sub.w, i.e. the standstill time intervals, are the same as in the example above, i.e. 0, 1, 2, 4, 8, 16, and 32 seconds.

[0104] It is to be understood that the present invention is not limited to the embodiments described above and illustrated in the drawings; rather, the skilled person will recognize that many changes and modifications may be made within the scope of the appended claims.