Adaptive cruise control for motor vehicles

Abstract

A method for adaptive cruise control of a motor vehicle (1) when approaching an unregulated intersection (2), wherein the motor vehicle (1) comprises an environment sensor (3), in particular an ADAS sensor, for capturing environment data of the motor vehicle, wherein during the approach of the motor vehicle (1) to the unregulated intersection (2) environment data of the motor vehicle are received, based on the environment data of the motor vehicle (1) and the current position of the motor vehicle (1) a geometric calculation of a field of view (4) of the environment sensor (3) in the direction towards the unregulated intersection (2) is performed, wherein from the field of view (4) and an expected target path (5) of the motor vehicle (1) a speed plan (v p ) of the motor vehicle (1) on the expected target path (5) is calculated, wherein the speed (v) of the motor vehicle (1) is adjusted in accordance with the speed plan (v p ).

Description

Technical Field

[0001] This invention relates to a method for adaptive cruise control (ACC) of a motor vehicle when it approaches an uncontrolled intersection. Background Technology

[0002] As is well known, modern vehicles can feature ADAS personalization. Existing driver assistance systems (Advanced Driver Assistance Systems, ADAS) offer a range of predefined driving modes that drivers can manually select and adjust. This allows drivers to influence the behavior of automated driving functions and driving modes.

[0003] Context-dependent ADAS systems are also known: modern ADAS systems take into account a variety of driving situations. They react, for example, to vehicles ahead, consider upcoming curves, and interpret steering wheel inputs to adjust speed in features such as adaptive cruise control (ACC).

[0004] Adaptive longitudinal control for cornering can also be used in modern vehicles. Modern ADAS systems for longitudinal control, such as ACC, adapt themselves to cornering by decelerating to an appropriate speed. This adaptation is typically based on cornering data obtained by sensors inside the vehicle, particularly cameras, and can also utilize map information provided by Electronic Horizons based on standard or high-resolution GPS maps.

[0005] Modern ADAS systems can also improve intersection safety. Depending on the sensor configuration, ACC and its associated emergency functions enhance safety at intersections by identifying oncoming and lateral approaching vehicles. These systems can warn drivers of potential collisions and, in some cases, introduce emergency braking to prevent a collision. Such collision avoidance systems are particularly advantageous at unregulated intersections.

[0006] However, modern ADAS systems also have some drawbacks, such as in terms of sensor dependence and associated costs: the performance of existing adaptive cruise control (ACC) and collision avoidance systems depends heavily on the available sensor equipment and the visibility range of sensors at intersections. To improve the performance of more reliably identifying approaching vehicles (oncoming vehicles, vehicles from the left or right), more and higher-quality sensors must be installed, which increases costs. Furthermore, more advanced recognition algorithms are needed to more accurately identify situations and avoid false alarms, which could lead to unnecessary emergency braking.

[0007] Even the most advanced sensors cannot overcome limited visibility conditions at intersections, such as those caused by buildings, other vehicles, or other obstacles. These obstacles can hinder the identification of oncoming vehicles, especially those approaching from the left or right. Summary of the Invention

[0008] The purpose of this invention is to provide a method for adaptive cruise control of a motor vehicle when it approaches an uncontrolled intersection. This method can reliably avoid collisions in the intersection area, enabling the motor vehicle to move forward quickly, and at the same time, it contributes to the cost-effective production of the motor vehicle.

[0009] This objective is achieved through a method for adaptive cruise control of a motor vehicle as it approaches an uncontrolled intersection, wherein the motor vehicle includes ambient sensors, particularly ADAS sensors, for capturing data about the vehicle's surroundings. During the approach to the uncontrolled intersection, the ambient data is received, and geometric calculations are performed on the field of view of the ambient sensors in the direction toward the uncontrolled intersection based on the ambient data and the vehicle's current position. A speed plan for the motor vehicle on the expected target path is calculated based on the field of view and the vehicle's anticipated target path, and the speed of the motor vehicle is controlled according to the speed plan.

[0010] According to the present invention, when approaching an uncontrolled intersection, i.e., in a motor vehicle that is not required to stop according to traffic signals before entering a collision or danger zone, the speed of the motor vehicle is adjusted, particularly by reducing the speed, based on the field of view of the vehicle's sensors. The field of view of the environmental sensors is geometrically determined because it takes into account environmental data provided by the environmental sensors, particularly identifiable obstacles in the field of view, and the position of the motor vehicle relative to these obstacles. Based on the geometrically determined field of view of the sensors, the expected speed of the motor vehicle on a planned path in the direction of a target path—which may include entering and exiting the uncontrolled intersection—is adjusted.

[0011] An "uncontrolled intersection" is an intersection where traffic is not regulated by light signals, particularly traffic signals, or warning signals. Uncontrolled intersections are classified as coequal or non-coequal. Intersections with traffic signs relating to right-of-way are considered non-coequal. The method according to the invention relates to both coequal and non-coequal uncontrolled intersections.

[0012] Currently, uncontrolled intersections are not adequately considered in existing speed planning processes used for longitudinal assist systems (such as ACC). Human drivers typically slow down at uncontrolled intersections to assess the presence of other vehicles. Based on this assessment, the driver decides whether to further decelerate, perhaps until coming to a stop, or whether to accelerate and enter the intersection. Complete stopping at the entrance point of an uncontrolled intersection is not mandatory, unlike at intersections regulated by stop signs.

[0013] This driver behavior is simulated in the method according to the invention, namely, selecting an appropriate speed to enter the intersection based on visibility conditions at the intersection. The visibility range is determined at least in part by the geometric characteristics of the intersection (such as road width, intersection angle, and visual static obstacles) and by information, for example, that can be obtained from GPS maps and electronic horizon concepts connected thereto or from in-vehicle sensors (such as cameras and radar).

[0014] According to the invention, an appropriate speed is determined when entering an intersection, particularly close to a so-called "stopping point," wherein the unfavorable situation where sensor information is unavailable is preferably also taken into account.

[0015] According to the present invention, visibility in adaptive cruise control (ACC) of a motor vehicle can be taken into account in this way. The ACC system can systematically consider the influence of visibility in speed adaptation. The speed assistance system according to the present invention simulates the natural driving behavior of humans driving slower when approaching an uncontrolled intersection with limited visibility. The deceleration phase at the uncontrolled intersection is customized according to the specific properties of the intersection, such as visibility.

[0016] Approach to an intersection depends on specific visibility conditions in particular individual cases. Improved adaptive behavior occurs during approach to intersections with limited visibility.

[0017] The solution according to the invention is a novel method for achieving safe and human-like speed control at unregulated intersections in longitudinal assistance systems (e.g., adaptive cruise control (ACC) for motor vehicles). This method preferably uses GPS map data and in-vehicle sensors to deduce the intersection geometry and planned maneuvers, calculates the geometric field of view considering the intersection geometry and potential obstacles, and achieves predictive deceleration to an appropriate speed until reaching a specific "decision point" where the sensor's field of view is sufficient to identify other vehicles to avoid a collision. Therefore, the vehicle can maintain its entry speed into the intersection, or even accelerate, or reduce its speed less, avoiding unnecessary conservative stops without impairing cross-traffic. Driving time and energy consumption can be reduced, safety is improved due to appropriate speed selection, and human-like driving behavior can be achieved.

[0018] Furthermore, the following advantages can be achieved in this way:

[0019] - Enhanced safety: By calculating visibility and planning speed to ensure the vehicle can always stop safely within sight, the system reduces the risk of collisions with unseen objects or vehicles.

[0020] - Improved efficiency: The ability to identify decision points where vehicles can no longer slow down and to rely on sensors to avoid collisions enables smoother and more efficient navigation through intersections, thereby avoiding unnecessary stops and delays.

[0021] - Human-like behavior: The system simulates human driving behavior by adapting the vehicle's speed to visibility conditions and intersection geometry, resulting in a more natural and predictable driving experience.

[0022] - Enhanced comfort: Cruise control and planning in the closed-loop control loop enable adaptive cruise control (ACC), which enhances driving comfort at unregulated intersections.

[0023] - Versatility: The solution can be applied to various intersection types and scenarios, including right-turn maneuvers at T-junctions with right-of-way signs, making it a universal approach for different driving conditions.

[0024] - Predictive planning: This system improves overall traffic safety without relying on expensive sensors by ensuring that vehicles are prepared for unexpected situations through predictive planning and worst-case assumptions.

[0025] - Integration with existing technologies: The system preferably uses data from GPS maps, electronic horizons, cloud-based APIs and / or in-vehicle sensors to achieve seamless integration with existing navigation and sensor technologies.

[0026] - Shorter travel time: By avoiding unnecessary stops and optimizing vehicle speed based on real-time conditions, this solution can help reduce total travel time and improve traffic flow.

[0027] The improvements of the invention are described in detail in the dependent claims, the specification, and the drawings.

[0028] Preferably, in addition to environmental data of the vehicle captured by environmental sensors, data from the GPS system and / or data from the electronic horizon concept are also used to calculate the vehicle's speed plan on the expected target path.

[0029] Preferably, a target reference point is defined on the intended target path such that at the target reference point, the vehicle has finished approaching the uncontrolled intersection and can adopt a standard speed for driving on the target road, wherein the required time for the vehicle to reach the target reference point during the movement corresponding to the speed plan is calculated. The target reference point is a point on the target path where the vehicle has finished the entire process of approaching the uncontrolled intersection, i.e., completed the entire operation of approaching the intersection, and the vehicle can continue to travel at this point at the typical speed of the target road without reducing speed due to the entire operation of entering the new road.

[0030] Preferably, the available time required for an external vehicle detected within or outside the field of view of the environmental sensor to reach the target reference point while moving at a possible speed (i.e., at the possible speed of the relevant road segment and / or at a speed that may depend on current environmental conditions (e.g., weather conditions)) is calculated.

[0031] In this method, it is preferable to check whether the required time is less than the available time. If not, the speed plan for the vehicle on the expected target path is recalculated based on the vehicle's field of vision and the expected target path, with a reduced speed. Therefore, if the vehicle reaches the target reference point (preferably in the exit area of ​​the intersection) no faster than any oncoming vehicle, the speed plan is adjusted by reducing the speed.

[0032] The collision point is preferably calculated, whereby it describes the position of the motor vehicle on its intended target path, where the vehicle enters the danger zone at the intersection where a collision with an oncoming vehicle is possible. Specifically, the collision point can describe the position of the motor vehicle where its profile, and thus the outer profile of the vehicle, enters the danger zone, particularly where it intersects with the connecting line of the intersecting streets. Preferably, the danger zone can be defined such that it begins at the imaginary connecting line of the nearest lane edge from the intersection of the lane and the intersecting lane. Thus, the collision point, i.e., the point of possible collision with a vehicle crossing the target path, is located not only on the target path but also preferably on the connecting line of the nearest outer road boundary of the intersecting roads. This connecting line can also be called a stop line and is preferably the line where the stop point is located, at which the motor vehicle typically stops when entry into the target road is impossible.

[0033] The new speed reduction plan can specify that the minimum speed is reached at the point of impact, such as stopping at the point of impact, but if possible, the speed at the point of impact should be greater than zero, preferably less than 5 km / h.

[0034] Preferably, it is checked whether the required time is less than the available time. If so, the speed of the motor vehicle is adjusted according to a standard speed that will not be reduced due to the risk of collision, in order to pass through the intersection. Thus, it is not necessary to reduce the speed due to the possibility of a collision with oncoming vehicles when entering the intersection, allowing the selection of a standard speed suitable for entering the intersection, regardless of the risk of collision.

[0035] Preferably, based on the vehicle's field of vision and the expected target path, a numerical optimization method is used to calculate the vehicle's speed plan along the expected target path, wherein the optimization method uses a cost function for efficiency and / or time optimization. Therefore, in addition to field of vision, time optimization (i.e., the vehicle's rapid forward movement) and / or efficiency optimization (e.g., energy optimization) also play a role in determining the speed plan used to approach an unregulated intersection.

[0036] The motor vehicle according to the invention includes a control unit installed in the vehicle, the control unit being configured to perform the method described above. During entry into an intersection, the speed of the motor vehicle can be adjusted by the control unit, at least in the longitudinal direction. Attached Figure Description

[0037] The invention will be described below by way of example with reference to the accompanying drawings.

[0038] Figure 1 This is a diagram of an unregulated intersection.

[0039] Figure 2It is a schematic representation of an uncontrolled intersection, and represents a scenario in which a motor vehicle turning right at a T-junction has a controlled right-of-way with various reference variables for the method of the present invention.

[0040] Figure 3 In two variants ( Figure 3 The diagrams (left and right images) illustrate the calculation of field of view 4.

[0041] Figure 4 yes Figure 2 A schematic diagram of a scenario involving a right-turning motor vehicle at a T-junction with controlled right-of-way, which includes other reference variables for use in the method according to the invention.

[0042] Figure 5 This is a schematic diagram of the calculated signal for geometric characteristics during the approach to a T-junction according to the method of the present invention.

[0043] Figure 6 This is a schematic representation of a situation where the decision point is reached at the end of the method according to the invention and free velocity planning can be performed.

[0044] Figure 7 This is a general block diagram illustrating the method according to the present invention.

[0045] Figure 8 This is a schematic diagram showing the results of applying the method according to the invention to a 90° T-shaped intersection. The bar graph shown has curves of speed v, time t, curvature c, radius r, and entry authorization e over distance. Detailed Implementation

[0046] Figure 1 An unregulated intersection is shown to be approached and driven through using the method according to the invention.

[0047] Even the most advanced environmental sensors 3 cannot overcome the limited visibility conditions at intersection 2, which are caused by factors such as buildings, other vehicles, or other obstacles 11. Figure 1 As shown, these obstacles 11 can hinder the identification of incoming vehicles 8 crossing from the left or right. According to the invention, the speed v of a motor vehicle 1 approaching the intersection 2 can be adapted to the field of vision 4, particularly to the longitudinal and / or lateral visible range, thereby optimizing the collision avoidance system.

[0048] Figure 2The diagram illustrates a right-turn maneuver scenario where a right-turning vehicle 1 approaches a T-junction with a right-of-way sign using the method according to the invention. The diagram shows the vehicle itself, i.e., vehicle 1, the anticipated and known target path 5 for the planned driving scenario (i.e., the right turn), and the approach path of an intersecting external vehicle 8 approaching from the left side of the main road, which is therefore undetectable by the environmental sensor 3 in this case because it is outside its field of view 4. Vehicle 1 travels on a road with a left road boundary 20 and a right road boundary 21. Speed ​​limit 22 regulates the permissible speed on the road on which vehicle 1 travels and on the intersecting road where the vehicle has the right-of-way.

[0049] exist Figure 2 Stop point 12 is shown as the position where vehicle 1 must stop so that crossing vehicle 8 can cross intersection 2. Under a conservative observation, the left and right road edges define the field of view 4, which is a worst-case assumption. Clearly, the boundary of the field of view 4 at each point on the target path 5 of vehicle 1 can be determined by calculating the tangent 16 at the curve defined by the left and right road edges in the intersection 2 region, where the tangent 16 passes through the current position of vehicle 1, preferably through the environmental sensor 3 of vehicle 1 or the center of gravity 15 of vehicle 1. From this, the detection angles (left and right of the straight line forward in the direction of travel) for the left and right fields of view 4 can be calculated. The turn into the intersection ends at the target reference point 6, which is determined by the algorithm itself.

[0050] The following detailed description involves, for example Figure 2 The right turn at the T-shaped intersection shown represents an embodiment of the present invention.

[0051] Data capture at the intersection: When vehicle 1 approaches intersection 2, data capture is automatically initiated via specific logic. The data required for the approaching intersection 2 comes from GPS maps, electronic horizons, cloud-based map APIs, and / or in-vehicle sensors such as cameras and / or radar, preferably including: road width and / or speed limits and / or the width and / or speed limits of the main traffic road and / or the intersection angle from the secondary road to the main traffic road and / or the transition radius from the secondary road to the main road.

[0052] The algorithm preferably calculates the following variables starting from the current position of vehicle 1: road boundary, target path of vehicle 1, route of traversing external vehicle 8, and stop point 12.

[0053] Then, the geometric characteristics of the current situation are calculated. The field of view 4 is determined by calculating the detection angles 13 and 14 on the left and right sides of vehicle 1. The center of gravity 15 of vehicle 1 is preferably used as the basis for calculating these angles. The tangent 16 can be defined according to the longitudinal direction of the vehicle and the left or right road boundary. One or more detection angles, such as the left detection angle 13 and the right detection angle 14, are then calculated using trigonometric functions. Figure 3 The field of view 4 of the T-shaped intersection is shown, calculated based on the left and right road boundaries used.

[0054] Figure 3 The calculation of field of view 4 in the two variants is illustrated schematically. Figure 3 (Left and right images). Figure 3 The effect of the selected road boundary as an obstacle 11 on the resulting detection angles 13 and 14 of the surrounding environment sensor 3 is shown, for example, on the left and right sides in the direction of travel.

[0055] The calculation rules used to determine collision point 9 take into account the geometry of vehicle 1. A bounding box is created for this purpose, extending in both the width and length of vehicle 1 and adjusted according to its current alignment, such as... Figure 4 As shown. Through iterative checking, collision point 9 is defined as the centroid of the first intersection of the bounding box and the stop line. Based on this definition, collision point 9 is reached before reaching the aforementioned stop point 12. More precisely, when the centroid 15 of vehicle 1 reaches collision point 9, one of the vehicle edges reaches stop point 12.

[0056] Figure 4 The diagram schematically illustrates the points used to calculate the collision point 9, the target reference point 6, and the time t required for calculation. n and available time t a In this situation, external vehicle 8 approaches at the constant speed adopted – if we assume the worst-case scenario, this corresponds to the speed limit on the main road – from vehicle 1, i.e., motor vehicle 1, at the speed planned by function v. p The limited speed v approaches intersection 2.

[0057] Speed ​​limit calculated at the collision point: If visibility is insufficient, vehicle 1 will decelerate in the direction of collision point 9. The conservative target speed at collision point 9 is fixed at 2 km / h, but can be calibrated for specific applications. A speed of 2 km / h allows for gradual entry into intersection 2 under poor visibility conditions until detection angles 13 and 14 provide sufficient visibility for peripheral sensors 3 to confirm an appropriate line of sight. After stopping at stop point 12 where the road is fully visible, the speed limit applies to the main road.

[0058] Figure 5 The image shows an example of a calculated signal for calculating the geometric characteristics of a T-shaped intersection.

[0059] Figure 5 The geometric analysis of a 90° T-shaped intersection is shown. The development of the field of view 4 based on a conservative calculation of the current vehicle position is shown. Detection angles on the left (13) and right (14), with the vehicle's longitudinal direction represented by dashed lines, and the collision point marked at the fork (9).

[0060] During the approach to intersection 2, the following positions are shown: target path position 0 m as P1, target path position 30 m as P2, target path position 68 m collision point as P3, and target path position 100 m as P4.

[0061] Speed ​​Planning: This function block evaluates the continuous speed planning v along the upcoming target path 5 of vehicle 1, taking into account the following input data. p The input data may vary in some embodiments: the position of vehicle 1, electronic field of view (especially the upcoming curvature), tilt and vector of the legal speed limit, ADAS sensors that may be used to improve the electronic field of view, and current vehicle status signals (such as vehicle speed and acceleration).

[0062] In a preferred embodiment, the function may include a numerical optimization method, wherein a cost function is used, which can be customized for efficiency or time optimization based on given factors and constraints imposed by the driver, vehicle, and the road itself, such as gradient, curvature, and legal speed limits. Speed ​​limits are considered for both secondary and primary roads.

[0063] The specific algorithm can be, for example, a high-level method as described above, or it can be, for example, a simple planner based solely on kinematics.

[0064] It should be noted that speed planning uses the legal speed limit specified by the electronic horizon as a standard feature, but the reverse loop "Plan deceleration (stop point)" S7 may change this input to force low speed and / or zero speed at collision point 9—the speed limit of the aforementioned collision point 9, see further description of this function below.

[0065] The time calculation is based on the results of geometric calculations and the current velocity planning.

[0066] Target Reference Point Calculation: First, a target reference point 6 for time calculation must be determined based on the previously planned speed of vehicle 1 along the target path 5. Target reference point 6 represents the end of the turning maneuver, where vehicle 1 reaches an appropriate stable speed, allowing it to smoothly merge into the main traffic flow without harming other vehicles. In some embodiments, the technical definition of target reference point 6 is the position where vehicle 1 reaches the target speed—the maximum speed on the main traffic road. On curved roads or in traffic conditions, additional conditions are needed to determine a reasonable target reference point 6. In curves, for example, where it is not safe to reach the maximum speed allowed on the main road, another condition can be used, such as based on the acceleration of vehicle 1. In this case, target reference point 6 can be defined as the point where the acceleration of vehicle 1 drops below a threshold after passing stop point 12, indicating that a stationary driving condition has been achieved after acceleration on the main road. The last mentioned option provides flexibility in defining target reference point 6, even on curved sections where the target speed may never be reached.

[0067] Required time t n The calculation: This function calculates the time required for vehicle 1 to perform the planned maneuver along the target path 5 at the planned speed. The required time t can be calculated from the relationship between the planned self-velocity curve and the distance from vehicle 1 via the target path 5 to the previously calculated target reference point 6. n .exist Figure 4 The required time t is shown in the figure. n Visualization.

[0068] In some embodiments, an additional, calibrable safety span can be added to the time calculation. Overall, the calculated required time t n Defines the velocity planning v considering the current effective velocity. p The time span required for vehicle 1 to pass through intersection 2 and successfully merge into the main road traffic.

[0069] Calculate available time t a Available time t a The distance of the potential crossing vehicle 8, calculated as the intersection of the left envelope of the field of view 4 and the target distance of the crossing vehicle 8, divided by the constant speed of the crossing vehicle (see [reference]). Figure 4 In the worst-case scenario, we assume that constant speed corresponds to the maximum speed on the main road.

[0070] Then check the required time t. n Is it less than the available time t? a At the beginning, the field of vision 4 is usually very small because vehicle 1 is still far from intersection 2 (see...). Figure 4(See left figure). Therefore, the time t required for vehicle 1 to reach the target reference point 6 is... n This is typically longer than the time required for potential cross-traffic vehicles on the main road (= available time t). a At the start of the calculation, the time t required to satisfy the condition is therefore not met. n Available time t a Therefore, by clicking the "Set Stop Speed" box, a loop is executed that returns to the speed planning, triggering a new speed planning process. p During this period, the speed limit at collision point 9 is set to the "collision point speed limit" (e.g., 2 km / h). This conservative speed planning provides a stop (or deceleration to the "collision point speed limit") at collision point 9. p The process is then performed by vehicle 1. In the next iteration, where vehicle 1 has moved slightly forward and thus the visibility condition has changed, this process is repeated until the vehicle reaches the point where the condition is satisfied within time t. n Available time t a This means reaching decision point 17.

[0071] Reaching Decision Point 17 – Unrestricted Velocity Programming: Time t Required if Conditions are Met n Available time t a Therefore, the calculated "unrestricted" speed plan is valid because the current visibility range of 4 is sufficient for safe driving further, without needing to plan a stop at the collision point 9. It should be noted that this "unrestricted" speed plan v... p The vehicle does not stop at point 9, thus allowing acceleration to reach a higher speed v while approaching intersection 2. This is permissible because the ADAS of vehicle 1 can still utilize sensors for collision avoidance, as there is sufficient visibility to operate safely, and vehicle 1 can turn into intersection 2.

[0072] Figure 6 This illustrates the scenario where decision point 17 is reached and free velocity planning is possible: at this point, there exists sufficient visibility or field of view 4—to the left in this example—to enable velocity planning v. p There is no need to conservatively reduce the speed v to a standstill; instead, the controller can rely on ADAS sensors to avoid collisions. Independently, Adaptive Cruise Control (ACC) plans the free speed only considering the input from the previously indicated speed planning function.

[0073] Figure 7 This is a general block diagram illustrating the method according to the present invention.

[0074] exist Figure 7The overall functionality of the method according to the invention is illustrated. At the defined decision point 17, the algorithm terminates and allows vehicle 1 to freely plan its speed v without being forced to stop at the collision point 9 (“optimal speed” ov). In contrast, a conservative method (“normal speed” cv) would always provide a stop at the collision point 9, which would result in an unnecessary increase in driving time and energy consumption, as well as non-human behavior.

[0075] Figure 7 The diagram shows: Start S, intersection data detection S1, geometric characteristic calculation S2, speed planning S3, time planning S4, comparison of required time < available time S5, if the result of S5 is Y, then reach the decision point – followed by unlimited speed planning S6; otherwise, in the case of N, then proceed to deceleration (stop point) step planning S7 and back to S3. E is the end of the method.

[0076] at last, Figure 8 The results of applying the method according to the invention to a 90° T-junction are shown. The bar graph shown from top to bottom represents the distances of speed v, time t, curvature c, radius r, and entry authorization e. Decision point 17 is shown as a dashed line. The endpoint of the calculation and turning maneuver according to the invention is located at target reference point 6. The graph showing speed v and time t illustrates the conventional value cv without curve start optimization and the optimized value ov according to the invention. The time saved s by this method is evident.

[0077] Therefore, this invention provides a novel method for achieving safe and human-like cruise control in longitudinal assistance systems, such as adaptive cruise control (ACC) for motor vehicles at unregulated intersections. Here, GPS map data and in-vehicle sensors can be used to derive the intersection geometry and plan maneuvers, calculate the geometric visibility range considering the intersection geometry and potential obstacles, and plan and execute predictive deceleration to an appropriate speed until reaching a specific “decision point” where the sensor visibility range is sufficient to identify other vehicles and avoid collisions. Thus, the vehicle 1 can maintain its speed entering the intersection, or accelerate or decelerate below its usual speed, avoiding unnecessary conservative stops without impeding cross-traffic, thereby reducing the vehicle 1's travel time and energy consumption. Appropriate speed selection improves safety and achieves human-like driving behavior.

[0078] This method is particularly useful for right and left turns at T-junctions, right and left turns at X-junctions, and right and left turns, for example, when lanes merge.

[0079] List of reference numerals

[0080] 1 motor vehicle

[0081] 2 intersections

[0082] 3 Ambient environment sensors

[0083] 4 fields of view

[0084] 5 Target Path

[0085] 6 target reference points

[0086] 7 Target Roads

[0087] 8 outside vehicles

[0088] 9 collision points

[0089] 10 Danger Zones

[0090] 11 obstacles

[0091] 12 stops

[0092] 13 Left detection angle

[0093] 14 Right detection angle

[0094] 15 Center of Gravity

[0095] 16 tangents

[0096] 17 decision points

[0097] 18. Electronic Horizon, GPS data, API data

[0098] 19. Update vehicle location, electronic horizon, ADAS sensors, and vehicle status.

[0099] 20 Left side of the road boundary

[0100] 21 Right side road boundary

[0101] 22 Speed ​​Limit

[0102] widths of b1 and b2

[0103] c-curvature

[0104] cv traditional value

[0105] d distance

[0106] e-authorization access

[0107] Ending with E

[0108] F: Failure

[0109] ov optimization value

[0110] Radius of r, r1, r2

[0111] s saves time

[0112] S starts

[0113] T True

[0114] t time

[0115] t n Time required

[0116] t a Available time

[0117] v speed

[0118] v p Speed ​​Planning

[0119] P1 Target path location 0m

[0120] P2 target path location 30m

[0121] P3 target path position 68m, collision point

[0122] P4 target path location 100m

[0123] S1 intersection data acquisition

[0124] S2 Geometric Property Calculation

[0125] S3 Speed ​​Planning

[0126] S4 Time Planning

[0127] Comparison of S5 required time < available time

[0128] S6 Reaching the Decision Point – Unrestricted Speed ​​Planning

[0129] S7 deceleration planning (stop point)

[0130] Y is

[0131] N has no

Claims

1. A method for adaptive cruise control of a motor vehicle (1) when the motor vehicle (1) approaches an uncontrolled intersection (2), wherein, The motor vehicle (1) includes ambient environment sensors (3) for capturing data about the surrounding environment of the motor vehicle, particularly ADAS sensors. During the approach of the motor vehicle (1) to the uncontrolled intersection (2), ambient environmental data of the motor vehicle is received. Based on the ambient environmental data of the motor vehicle (1) and the current position of the motor vehicle (1), a geometric calculation of the field of view (4) of the ambient environmental sensor (3) in the direction toward the uncontrolled intersection (2) is performed. Based on the field of view (4) and the expected target path (5) of the motor vehicle (1), a speed plan (v) of the motor vehicle (1) on the expected target path (5) is calculated. p ), where, according to the speed planning (v p ) to adjust the speed (v) of the motor vehicle (1).

2. The method according to claim 1, in, In addition to the vehicle environment data captured by the environmental sensor (3), data from the GPS system and / or data from the electronic horizon concept are also used to calculate the vehicle's (1) speed plan (v) on the expected target path (5). p ).

3. The method according to claim 1 or 2, in, Determine a target reference point (6) on the expected target path (5) such that at the target reference point (6), the motor vehicle (1) has finished approaching the uncontrolled intersection (2) and can adopt a standard speed for driving on the target road (7), wherein the motor vehicle (1) is calculated at a speed corresponding to the speed planning (v p The required time (t) during the movement of ) until reaching the target reference point (6). n ).

4. The method according to claim 3, in, Calculate available time (t) a The available time (t) is required for an external vehicle (8) detected in the field of view (4) of the surrounding environment sensor (3) or located outside the field of view (4) of the surrounding environment sensor (3) to move at a possible speed until it reaches the target reference point (6). a ).

5. The method according to claim 4, in, The required time (t) for checking the above n Is it less than the available time (t)? a If this is not the case, then based on the field of vision (4) of the motor vehicle (1) and the expected target path (5), the speed plan (v) of the motor vehicle (1) at a reduced speed (v) on the expected target path (5) is recalculated. p ).

6. The method according to at least one of the preceding claims, in, Calculate the collision point (9), wherein the collision point (9) describes the position of the motor vehicle (1) on the expected target path (5) of the motor vehicle (1), at which the motor vehicle (1) enters the danger zone (10) at the intersection (2) where it may collide with an oncoming vehicle (8) crossing the road.

7. The method according to claim 6, in, The reduced speed (v) includes the minimum speed at the point of impact (9), such as being at rest or at a speed greater than zero and less than 5 km / h at the point of impact (9).

8. The method according to claim 4, in, The required time (t) for checking the above n Is it less than the available time (t)? a In this case, the speed (v) of the motor vehicle (1) is adjusted according to a standard speed to pass through the intersection (2), and the standard speed is not reduced due to the risk of collision.

9. The method according to at least one of the preceding claims, in, Based on the field of vision (4) of the motor vehicle (1) and the expected target path (5), the speed planning (v) of the motor vehicle (1) on the expected target path (5) is calculated by means of a numerical optimization method. p The optimization method preferably uses a cost function for efficiency optimization and / or time optimization.

10. Motor vehicles, including control units installed in motor vehicles, in, The control unit is configured to perform the method according to at least one of the preceding claims.

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