Patent Description:
Many vehicles comprise environmental detection systems such as radar, Lidar and camera systems which are arranged for object detection, being able to provide a warning to a driver about an object in the path of a vehicle, as well as providing input to vehicle systems such as Adaptive Cruise Control (ACC) and Rear Cross Traffic Avoidance (RCTA) systems, where ACC is a longitudinal distance controller in an ADAS (Advanced Driver Assistant System).

Such environmental detection systems can comprise one or more forward-looking detectors, rearward-looking detectors and sideward-looking detectors of one or more types. Other types of detectors include V2V (vehicle-to-vehicle) and V2X (vehicle-to-anything).

ACC aims to mimic the behavior of a human driver, which represents huge challenges regarding controller design as well as regarding calculation of a desired distance to surrounding objects. The desired distance can be defined as a time gap, which is a time that corresponds to a distance to a preceding object.

<CIT> discloses an ACC system adapted to adjust distance or speed to the vehicle in front dependent on average distance to vehicles in adjacent lanes. <CIT> describes an arrangement for intelligent gap setting for adaptive cruise control involving sensing and environment with a sensor and Adaption indicators determined. <CIT> describes adaptive cruise control involving detecting target objects and a predicted path.

A more accurate mimic of human behavior is, however, desired.

The object of the present disclosure is to provide a vehicle control system that is adapted to adjust distance or speed to the vehicle in front in such a way that a more accurate mimic of human behavior than previously known is obtained in an uncomplicated and reliable manner.

The invention as defined in the independent claims to which reference is directed with preferred features set out in the dependent claims.

With reference to <FIG>, illustrating a first example, there is a road <NUM> with three adjacent lanes 20a, 20b, 20c, a first lane 20a, a second lane 20b and a third lane 20c. An ego vehicle <NUM> is travelling in the second lane 20b, following a preceding target vehicle <NUM>. In this example, the vehicles in the lanes 20a, 20b, 20c are travelling in the same direction.

There is a vehicle control system <NUM> comprising a control unit arrangement <NUM> and at least one sensor arrangement <NUM>, <NUM> that is arranged to be mounted in the ego vehicle <NUM> and is adapted to provide sensor information for the preceding target vehicle <NUM> and surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> separate from the preceding target vehicle <NUM>. In <FIG>, the surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> travel in all lanes 20a, 20b, 20c, and as will be apparent from some of the examples, the surrounding target vehicles travel in at least one of the lanes 20a, 20b, 20c.

The vehicles which are determined to constitute surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> fulfill certain conditions, for example being positioned at a certain distance or distances from the ego vehicle <NUM>, or being within a certain zone <NUM> around the ego vehicle <NUM>, only schematically indicated in <FIG>. The vehicles which are determined to constitute surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> can alternatively fulfill certain conditions with respect to the preceding target vehicle <NUM> instead of the ego vehicle <NUM>.

According to some aspects, the sensor information can be in the form of sensor detection, and the sensor information is provided by means of the sensor arrangement <NUM>, <NUM>. The sensor arrangement <NUM>, <NUM> comprises at least one of radar sensors, Lidar sensors, ultrasonic sensors, camera devices, V2V, vehicle-to-vehicle, devices and V2X, vehicle-to-anything, devices.

The control unit arrangement <NUM> is adapted to control an ego vehicle speed v<NUM> in dependence of the sensor information associated with the preceding target vehicle <NUM> such that an ego distance r<NUM> between the ego vehicle <NUM> and the preceding target vehicle <NUM> is obtained. A time gap ΔT<NUM> is defined as the time for travelling the ego distance r<NUM> at the ego vehicle speed v<NUM>. This means that during the time of the time gap ΔT<NUM>, the ego vehicle travelling at the ego vehicle speed v<NUM> will travel the ego distance r<NUM>.

According to the present disclosure, the control unit arrangement <NUM> is adapted to control the ego vehicle speed v<NUM> in dependence of the sensor information associated with the surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> such that a present time gap ΔT<NUM> is maintained in dependence of the number of detected surrounding target vehicles <NUM>. In the first example, there is a first time gap ΔT<NUM>, a first ego distance r<NUM> and a first vehicle speed v<NUM> as illustrated in <FIG>. In the following at least one of the first time gap ΔT<NUM>, the first ego distance r<NUM> and the first vehicle speed v<NUM> will be further modified.

According to some aspects, as shown in <FIG> that illustrates a second example, the control unit arrangement <NUM> is adapted to control the ego vehicle speed v<NUM> such that the time gap ΔT<NUM> is decreased with an increased number of detected surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM>. In the second example, there is a second time gap ΔT<NUM>, a second ego distance r<NUM> and a second vehicle speed v<NUM> as illustrated in <FIG>. The vehicle speed, for example the first vehicle speed v<NUM>, is thus controlled to be changed to the second vehicle speed v<NUM> such that a decreased second time gap ΔT<NUM> is obtained when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> has increased, for example compared to the first example.

This means that when the number of surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> increases, the time gap is decreased, and the inventor has become aware of the fact that this behavior mimics human behavior. When the number of surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> increases, a driver tends to decrease the time gap to the vehicle in front of the vehicle.

According to some aspects, as shown in <FIG> that illustrates a third example, the control unit arrangement <NUM> is adapted to control the ego vehicle speed v<NUM> such that the time gap ΔT<NUM> is increased with a decreased number of surrounding detected target vehicles <NUM>. In the third example, there is a third time gap ΔT<NUM>, a third ego distance r<NUM> and a third vehicle speed v<NUM> as illustrated in <FIG>. The vehicle speed, for example the first vehicle speed v<NUM>, is thus controlled to be changed to the third vehicle speed v<NUM> such that an increased third time gap ΔT<NUM> is obtained when the number of detected surrounding target vehicles <NUM> has increased, for example compared to the first example.

This means that when the number of surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> decreases, the time gap is increased, and, correspondingly, the inventor has become aware of the fact that this behavior mimics human behavior. When the number of surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> decreases, a driver tends to increase the time gap to the vehicle in front of the vehicle.

According to some aspects, the ego distance r<NUM> is decreased when the time gap ΔT<NUM> is decreased, and the ego distance r<NUM> is increased when the time gap ΔT<NUM> is increased. In the above examples, when starting from the first example, this means that the first ego distance r<NUM> is decreased to the second ego distance r<NUM> when the first time gap ΔT<NUM> is decreased to the second time gap ΔT<NUM>. Alternatively, the first ego distance r<NUM> is increased to the third ego distance r<NUM> when the first time gap ΔT<NUM> is increased to the third time gap ΔT<NUM>. This means that the second ego distance r<NUM> falls below the third ego distance r<NUM> and the previous ego distance, here the first ego distance r<NUM>. The third ego distance r<NUM> exceeds the previous ego distance, here the first ego distance r<NUM>.

According to some aspects, as shown in <FIG> that illustrates a fourth example, the control unit arrangement <NUM> is adapted to control the time gap ΔT<NUM> in dependence of the ego vehicle speed v<NUM> when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM> is constant such that the time gap ΔT<NUM> is decreased with an increased ego vehicle speed v<NUM>. In the fourth example, there is a fourth time gap ΔT<NUM>, a fourth ego distance r<NUM> and a fourth vehicle speed v<NUM> as illustrated in <FIG>. The time gap, for example the first time gap ΔT<NUM>, is thus controlled to be changed to the decreased fourth time gap ΔT<NUM>, and the vehicle speed, for example the first vehicle speed v<NUM>, is controlled to be changed to the increased fourth vehicle speed v<NUM>. A decreased fourth time gap ΔT<NUM> and an increased fourth vehicle speed v<NUM> are thus obtained compared to the first example when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM> is constant.

According to some aspects, as shown in <FIG> that illustrates a fifth example, the control unit arrangement <NUM> is adapted to control the time gap ΔT<NUM> in dependence of the ego vehicle speed v<NUM> when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM> is constant such that the time gap ΔT<NUM> is increased with a decreased ego vehicle speed v<NUM>. In the fifth example, there is a fifth time gap ΔT<NUM>, a fifth ego distance r<NUM> and a fifth vehicle speed v<NUM> as illustrated in <FIG>. The time gap, for example the first time gap ΔT<NUM>, is thus controlled to be changed to the increased fifth time gap ΔT<NUM>, and the vehicle speed, for example the first vehicle speed v<NUM>, is controlled to be changed to the decreased fifth vehicle speed v<NUM>. An increased fifth time gap ΔT<NUM> and a decreased fifth vehicle speed v<NUM> are thus obtained compared to the first example when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM> is constant.

In this manner, control of the time gap is provided in a manner that mimics human behavior also in the case where the number of detected surrounding target vehicles is constant.

According to some aspects, the ego distance r<NUM> is increased when the time gap ΔT<NUM> is decreased, and the ego distance r<NUM> is decreased when the time gap ΔT<NUM> is increased.

In the above fourth and fifth examples, when starting from the first example, this means that the first ego distance r<NUM> is increased to the fourth ego distance r<NUM> when the first time gap ΔT<NUM> is decreased to the fourth time gap ΔT<NUM>. Alternatively, first ego distance r<NUM> is decreased to the fifth ego distance r<NUM> when the first time gap ΔT<NUM> increased to the fifth time gap ΔT<NUM>. This means that the fourth ego distance r<NUM> exceeds the fourth ego distance r<NUM> and the previous ego distance, here the first ego distance r<NUM>.

The present disclosure thus utilizes a calculation of a desired distance based on sensor information and is not dependent on a priori, static optimization/tuning which is the common solution today. The sensor information comprises the number of fused objects surrounding the host vehicle, where a fused object for example is an object that is classified as a truck, a car or a motorcycle where the states are confirmed with high confidence. The number of fused objects can according to some aspects be determined by means of a fused object counter as will be discussed later with reference to <FIG>.

According to some aspects, an increased scenario ego vehicle speed leads to higher distance and lower time gap, and an increased number of fused objects around the host vehicle, in particular constituted by surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, for a given speed, leads to lower ego distance and lower time gap.

The time gap increases exponentially for speeds below <NUM>-<NUM>/s. Thus, the time gap is a more useful property for distance control in ACC at higher ego vehicle speeds. Therefore, according to some aspects, for lower speeds such as for example below <NUM>-<NUM>/s, use distance as controller state, for higher speeds use time gap.

By means of the present disclosure, an uncomplicated and intuitive automatic time gap (ATG) function is obtained, improving the experience for the average/casual ACC user.

According to some aspects, the comfort level experienced by a user in view of the ego distance depend on the actual scenario, where more surrounding target vehicles leads to a shorter ego distance, and where a higher host speed leads to a longer ego distance. It shall be noted that a longer ego distance does not necessarily lead to an increased time gap.

In the examples presented there are first to fifth ego vehicle speed, time gap and ego distance, where the numbering relates to the different scenarios and not to a special order. A changed vehicle speed, time gap and/or ego distance can be changed from any previous scenario, and even from an initial scenario or other scenario that is not comprised in the scenarios described.

With reference to <FIG>, the present disclosure also relates to a method in a vehicle control system <NUM> that comprises a control unit arrangement <NUM> and at least one sensor arrangement <NUM>, <NUM>. The method comprises providing S100 sensor information for one preceding target vehicle <NUM> and surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> separate from the preceding target vehicle <NUM>, and controlling S200 an ego vehicle speed v<NUM> in dependence of the sensor information associated with the preceding target vehicle <NUM> such that an ego distance r<NUM> between the ego vehicle <NUM> and the preceding target vehicle <NUM> obtained. A time gap ΔT<NUM> is defined as the time for travelling the ego distance at the ego vehicle speed v<NUM>. The method further comprises controlling S300 the ego vehicle speed v<NUM> in dependence of the sensor information associated with the surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM> such that a present time gap ΔT<NUM> is maintained in dependence of the number of detected surrounding target vehicles <NUM>.

According to some aspects, the method comprises controlling S400 the ego vehicle speed v<NUM> such that the time gap ΔT<NUM> is decreased with an increased number of detected surrounding target vehicles <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and controlling S500 the ego vehicle speed v<NUM> such that the time gap ΔT<NUM> is increased with a decreased number of surrounding detected target vehicles <NUM>.

According to some aspects, the method comprises decreasing S600 the ego distance r<NUM> when the time gap ΔT<NUM> is decreased, and increasing S700 the ego distance r<NUM> when the time gap ΔT<NUM> is increased.

According to some aspects, the method comprises controlling S800 the time gap ΔT<NUM>, ΔT<NUM> in dependence of the ego vehicle speed v<NUM>, v<NUM> when the number of detected surrounding target vehicles <NUM>, <NUM>, <NUM> is constant. This is enabled by means of the method that further comprises decreasing S810 the time gap ΔT<NUM> with an increased ego vehicle speed v<NUM> and increasing S820 the time gap ΔT<NUM> with a decreased ego vehicle speed v<NUM>.

According to some aspects, the method comprises increasing the ego distance r<NUM> when the time gap ΔT<NUM> is decreased, and decreasing the ego distance r<NUM> when the time gap ΔT<NUM> is increased.

The method above is described in steps that can be taken in any suitable manner in order to obtain the desired result according to the present disclosure.

The present disclosure relies on an objective analysis of the surroundings, and not on a subjective distance calibration. The present disclosure relies on an uncomplicated setup, and does not require machine-learning or other complicated features.

This is for example illustrated in <FIG> that schematically discloses an illustration of a setup according to some aspects of the present disclosure. Information <NUM> related to surrounding traffic is provided by the sensor arrangement <NUM>, <NUM> and is input to a fused object counter <NUM>, and the number of surrounding objects <NUM> is output from the fused object counter <NUM>. The number of surrounding objects <NUM> and the ego vehicle speed <NUM> are input into an automatic time gap algorithm <NUM> that comprises a 2D look-up table <NUM> from which first time gap values <NUM> are output, where the time gap values <NUM> relate to the preceding target vehicle <NUM> according to the above and are determined by the time gap algorithm <NUM> in dependence of the input number of surrounding objects <NUM> and the input ego vehicle speed <NUM>. With the relevant inputs, the 2D look-up table <NUM> can be used for determining a desired ego distance, time gap and ego vehicle speed.

The 2D look-up table <NUM> can for example be derived by first obtaining off-line data values that form a relatively large data set. This data set is analyzed and the distances between objects are calculated.

According to some further aspects, and as indicated with dashed boxes <NUM>, <NUM> in <FIG>, the 2D look-up table is supplemented with a dynamic adjustment algorithm <NUM> where on-line values are calculated dynamically. These resulting values <NUM> are used to adjust the off-line first time gap values <NUM> to adjust for actual traffic conditions. The principle for this calculation is that the dynamic adjustment algorithm <NUM> uses the number of surrounding objects <NUM> and the ego vehicle speed <NUM> as input as well as the off-line first time gap values <NUM>. This enables the dynamic adjustment algorithm <NUM> to perform real-time calculation of a difference between the off-line first time gap values <NUM> and the actual distances. This difference <NUM>, a single value, is then stored and input to an adjustment arrangement <NUM> together with the off-line first time gap values <NUM> such that adjusted second time gap values <NUM> are output from the adjustment arrangement <NUM>.

According to some aspects, the control unit arrangement <NUM> is adapted to control the ego vehicle speed within certain limits, for example additionally in dependence at least one of time to collision (TTC) data, the ego vehicle speed falling below a certain threshold value, and other functions such as overtaking and automatic lane changes.

Therefore, according to some further aspects, for relatively low speeds down to complete standstill, the automatic time gap algorithm <NUM> has to be disabled and a separate distance calculation has to be active. This is to ensure a consistent stop distance that is defined in absolute distance, and not in time-distance that corresponds to a time gap. Correspondingly, the automatic time gap algorithm <NUM> can according to some aspects also be disabled for special cases/modes like ACC Overtake, Lane change Assist, driver override etc..

Furthermore, user settings like Drive Mode, ECO ACC and ACC environmental conditions can also impact on the desired time gap apart from the automatic time gap calculation. All of this encapsulation, disabling or modification of the algorithm output is handled by an arbitrator arrangement <NUM> that is indicated with dashed lines in <FIG>. The adjusted second time gap values <NUM> and arbitration time gap values <NUM> are input into the arbitrator arrangement <NUM>, and calculated third time gap values <NUM> are output as final results.

According to some aspects, all necessary input data are available from an existing vehicle system, such as an ADAS system.

<FIG> schematically illustrates a control unit arrangement <NUM> according to aspects of the present disclosure. It is appreciated that the above described methods and techniques may be realized in hardware. This hardware is then arranged to perform the methods, whereby the same advantages and effects are obtained as have been discussed above.

Processing circuitry <NUM> is provided using any combination of one or more of a suitable central processing unit (CPU), multiprocessor, microcontroller, digital signal processor (DSP), etc., capable of executing software instructions stored in a computer program product, e.g. in the form of a storage medium <NUM>. The processing circuitry <NUM> may further be provided as at least one application specific integrated circuit (ASIC), or field programmable gate array (FPGA).

Particularly, the processing circuitry <NUM> is configured to cause the control unit arrangement <NUM> to perform a set of operations, or steps, for example the methods described above. For example, the storage medium <NUM> may store the set of operations, and the processing circuitry <NUM> may be configured to retrieve the set of operations from the storage medium <NUM> to cause the control unit arrangement <NUM> to perform the set of operations. According to some aspects, the processing circuitry <NUM> is arranged to execute the automatic time gap algorithm <NUM>.

The control unit arrangement <NUM> may further comprise a communications interface <NUM> for communications with at least one external device. As such the communication interface <NUM> may comprise one or more transmitters and receivers, comprising analogue and digital components and a suitable number ports for wireline or wireless communication.

The processing circuitry <NUM> controls the general operation of the control unit arrangement <NUM>, e.g. by sending data and control signals to the communication interface <NUM> and the storage medium <NUM>, by receiving data and reports from the communication interface <NUM>, and by retrieving data and instructions from the storage medium <NUM>. Other components, as well as the related functionality, of the unit are omitted in order not to obscure the concepts presented herein.

<FIG> schematically illustrates a computer program product <NUM> comprising a computer program <NUM> according to the disclosure above, and a computer readable storage medium <NUM> on which the computer program <NUM> is stored.

The present disclosure is not limited to the examples described above, but may vary freely within the scope of the appended claims. For example, the control unit arrangement <NUM> is adapted to control the ego vehicle speed in any suitable manner as is well-known in the art. The control unit arrangement <NUM> may comprise one control unit or several control units that are integrated or separated.

For example, all different examples provided may be combined in any suitable manner.

Claim 1:
A vehicle control system (<NUM>) comprising a control unit arrangement (<NUM>) and at least one sensor arrangement (<NUM>, <NUM>) that is arranged to be mounted in an ego vehicle (<NUM>), where the sensor arrangement (<NUM>, <NUM>) is adapted to provide sensor information for one preceding target vehicle (<NUM>) and surrounding target vehicles (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>) separate from the preceding target vehicle (<NUM>), where the control unit arrangement (<NUM>) is adapted to control an ego vehicle speed (v<NUM>) in dependence of the sensor information associated with the preceding target vehicle (<NUM>) such that an ego distance (r<NUM>) between the ego vehicle (<NUM>) and the preceding target vehicle (<NUM>) is obtained, where a time gap (ΔT<NUM>) is defined as the time for travelling the ego distance (r<NUM>) at the ego vehicle speed (v<NUM>), wherein the control unit arrangement (<NUM>) is adapted to control the ego vehicle speed (v<NUM>) in dependence of the sensor information associated with the surrounding target vehicles (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>) such that a present time gap (ΔT<NUM>) is maintained in dependence of the number of detected surrounding target vehicles (<NUM>); wherein the control unit arrangement (<NUM>) is adapted to control the ego vehicle speed (v<NUM>, v<NUM>) such that the time gap (ΔT<NUM>) is decreased with an increased number of detected surrounding target vehicles (<NUM>, <NUM>, <NUM>, <NUM>, <NUM>), and such that the time gap (ΔT<NUM>) is increased with a decreased number of surrounding detected target vehicles (<NUM>); characterised in that the control unit arrangement (<NUM>) is adapted to control the time gap (ΔT<NUM>, ΔT<NUM>) in dependence of the ego vehicle speed (v<NUM>, v<NUM>) when the number of detected surrounding target vehicles (<NUM>, <NUM>, <NUM>) is constant such that the time gap (ΔT<NUM>) is decreased with an increased ego vehicle speed (v<NUM>) and such that the time gap (ΔT<NUM>) is increased with a decreased ego vehicle speed (v<NUM>).