WO2022258150A1

WO2022258150A1 - Computer-implemented method of assisting a driver, computer program product, driving assistance system, and vehicle

Info

Publication number: WO2022258150A1
Application number: PCT/EP2021/065304
Authority: WO
Inventors: Bilal Khan; Anna PÄTZOLD
Original assignee: Lotus Tech Innovation Centre Gmbh
Priority date: 2021-06-08
Filing date: 2021-06-08
Publication date: 2022-12-15

Abstract

Described is a computer-implemented method of assisting a driver of a vehicle through providing alerts to the driver based on events relating to the vehicle and/or the vehicle's surroundings using a driving assistance system, by detecting a condition of the driver through a driver monitoring system that detects physiological parameters and/or activity-related parameters of the driver and by detecting vehicle parameters, wherein, based on the physiological parameters and/or the activity-related parameters, and the vehicle parameters, a driver distraction level is calculated, wherein, if the driver distraction level equals or exceeds a predetermined distraction threshold, an alert timing value is set to an early alert value, whereas, if the driver distraction level is lower than the threshold, the alert timing value is set to a late alert value, wherein an alert timing is determined by the alert timing value.

Description

Computer-implemented method of assisting a driver, computer program product, driving assistance system, and vehicle

The present disclosure relates to computer-implemented methods of assisting a driver, computer program products, driving assistance systems, and vehicles.

It is known that driving for extended periods of time is physiologically exhausting and tiring.

Over time, a driver's concentration level drops, the driver gets distracted and/or drowsy. A decline in concentration may lead to potentially hazardous traffic situations not being recognized early enough or not judged correctly. Dangerous traffic situations may be misinterpreted leading to wrong reactions and interventions.

Fatigue alert systems are generally known in the art. Such systems assess the alertness of a driver using a variety of criteria. Among others it is known to detect and electronically evaluate eye, pupil and/or eyelid movements of the driver by means of cameras, and on this basis to draw conclusions as to the driver's state of alertness. An alert can then be emitted in the form of an acoustic signal, a graphical display or a vibration of a vehicle interface e.g., the steering wheel. Furthermore, modern vehicles are frequently equipped with driver assistance systems. Such driver assistance systems may, for example, include an automatic longitudinal speed regulation, frequently called adaptive cruise control, which is capable of automatically maintaining the distance to a preceding vehicle. To this end, the assistance system may interact alternately with the accelerator and the brake. Also, lane assist systems are frequently installed in current vehicles. Lane assistance systems prevent the vehicle from inadvertently leaving the lane by interfering with the steering mechanism. These systems too are contributors to safety.

The aforementioned systems ease the burden on the driver but may contribute to the driver not maintaining his situational awareness of the current traffic conditions on the road.

For some time now work has been going on to develop vehicles which are operated partially or completely autonomously. Such vehicles are intended to drive from a current location of the vehicle to a target location without the need of an intervention by the driver, wherein dangerous situations are automatically detected.

It is, however, possible that for safety reasons in extreme situations control of the vehicle is to be handed over to the driver. It is also feasible that autonomous driving could be restricted to certain zones and would not be permitted outside these zones. In urban regions, for example, where the number of road users of all categories is high including vehicle drivers, cyclists, pedestrians etc., automatic driving could be legally prohibited. Then it must be ensured that even with motor vehicles equipped with such automated driving systems, drivers must always be in control in such zones.

During times in which the vehicle drives autonomously, the driver of the vehicle may occupy himself with other activities. For example, a driver might read, listen to music, watch a film or make a telephone call. While such activities are going on, the driver might not pay attention to what is happening on the road. If, however, the driver must assume control of the vehicle, for example when the driver is approaching a self-driving zone or is about to get into a potentially hazardous situation, the driver must be alerted to this fact. Depending on the current activity of the driver, it may take a certain amount of time until he or she has gathered attention on the traffic and becomes aware of the situation before he or she can take over control of the motor vehicle. Therefore, an alert must be issued in advance in good time.

US 10,449,856 B1 discloses a driving assistance apparatus that assists a transition from an autonomous driving mode in which a vehicle is driven under autonomous control to a manual driving mode in which the vehicle is driven by a driver, comprising: one or more memories; and circuitry that, in operation, performs operations including detecting an activity by the driver, detecting a plurality of conditions of the driver, that include a level of concentration of the driver, and determining a take-over request method which is a method of presenting, in the vehicle, a take-over request that informs the driver that the autonomous driving mode is going to be cancelled, the determining being based on at least the detected activity by the driver and the plurality of detected conditions, wherein the determining includes, if the detected activity by the driver is a specific activity, determining the take-over request method so that the take-over request is highlighted depending on the detected level of concentration.

It is also known that sometimes, alerts annoy drivers if they are issued too frequently or too early. This could lead to drivers ignoring alerts and then missing an important alert. Issuing respective alerts at the right moment in time is therefore important.

The known driver assistance systems, however, are not sensitive enough to determine how distracted or drowsy drivers actually are. It is therefore an object of the invention to improve the accuracy of determination of a driver's condition.

The object is solved by a computer-implemented method of assisting a driver according to claim 1, a computer program product according to independent claim 10, a driving assistance system according to independent claim 11 , and a vehicle according to independent claim 13. Further embodiments are described in dependent claims.

Described is a computer-implemented method of assisting a driver of a vehicle through providing alerts to the driver based on events relating to the vehicle and/or the vehicle’s surroundings using a driving assistance system, by detecting a condition of the driver through a driver monitoring system that detects physiological parameters and/or activity-related parameters of the driver and by detecting vehicle parameters, wherein, based on the physiological parameters and/or the activity-related parameters, and the vehicle parameters, a driver distraction level is calculated, wherein, if the driver distraction level equals or exceeds a predetermined distraction threshold, an alert timing value is set to an early alert value, whereas, if the driver distraction level is lower than the threshold, the alert timing value is set to a late alert value, wherein an alert timing is determined by the alert timing value.

The vehicle can be motor driven. It can be a car, a truck, a bus, or the like. The method can be used in human controlled, autonomous or semi-autonomous vehicles in self-driving, assisted driving or autonomous driving modes.

The terms „alert“ and ..warning" are used interchangeably within this disclosure. The distraction of a driver can have different reasons, for example tiredness, drowsiness, conversations with other passengers in the car or via phone, or other, non-driving related activities such as reading, using mobile devices or the like.

The events can be related to certain driver assistance systems, e.g., lane assist systems that provide alerts if the vehicle is about to cross a lane without indicator. Another exemplary use of the method can relate to parking assistance systems. A third exemplary use can relate to collision warning systems.

It has been found that physiological parameters of the driver in combination with the vehicle’s parameters provides for a more accurate assessment of the driver’s distraction level, or, vice versa, his alertness. Even though physiological parameters alone might indicate that a driver is tired or distracted, he might be fully aware about the surroundings. If in addition, however, vehicle parameters are taken into account, more data points are available that can help determine a driver's real distraction or drowsiness level. The more distracted or tired a driver is, the longer it takes for him to recognize and evaluate a particular situation and to react appropriately. Therefore, it is advantageous if a more distracted driver is warned earlier than an attentive driver. If attentive drivers are warned too early or too frequently, they might disregard alerts provided by the warning systems.

The driver distraction level can be a weighted sum of contributions from vehicle parameters and physiological parameters captured through the driver monitoring system (DMS). Driver distraction level values can be determined through the driver monitoring system and in parallel through the vehicle parameters. The driver monitoring system as well as a vehicle parameter capturing system can monitor amount, frequency and intensity of certain behaviors and use those criteria to determine the driver distraction level from the respective input source.

As an example, the driver monitoring system can be configured to detect the driver’s face, in particular the driver’s eyes. Through this recognition capability, the driver monitoring system can detect eye blinking, yawning, gaze behavior, and/or head orientation. A tunneled gaze behaviour can indicate cognitive distraction, whereas switching the gaze between relevant areas of interest, e.g., road scene, vehicle displays, mirrors, rather represents driver awareness.

The driver monitoring system can also detect non-driving-related tasks such as typing on a device, talking, singing, etc.. Visual-manual distraction, e.g., typing on a mobile device, interacting with the in-vehicle systems, more adversely affects driving safety than cognitive-auditory distraction, e.g., talking on the phone or with a passenger. Cognitive-auditory distraction can increase the driving safety as the information processing resources load on a different domain than the driving task, which is visual-manually loaded

The distraction levels can be proportional to, indirect proportional to the driver behavior or follow any other logic that connects the driver behavior to the distraction level. Certain behaviors can be assigned certain values which can be fixed or variable and depend on the degree to which the driver exhibits such behavior. As a proportionality example, the frequency of lane departures can be multiplied with a fixed factor to yield a certain distraction value contribution. As an indirect proportionality example, the inverse of the frequency of switching the driver’s gaze can be multiplied with a fixed factor to determin a certain distraction value contribution.

Vehicle parameters that can be used to determine driver distraction ar, for example, steering corrections, lane departures, time headway, frequency of braking, steering wheel reversal rate, difference between driving speed and speed limit as well as speed change rate, etc.. Small corrections of the steering and positioning in the lane indicate a non-distracted driver, whereas close to zero corrections indicate a cognitively distracted driver, who might be keen to an effect of ooked but failed to see" - the gaze is directed towards the road scene, but information retrieved is not processed and hence cannot be reacted to.

Afterwards, those determined distraction levels can be weighted, e.g., per per behavior and/or per source, e.g., 2/3 DMS and 1/3 vehicle parameters and summed up.

Certain behaviors can lead, viewed in isolation or in combination, to the assessment of a high distraction of the driver, e.g., if some of the criteria exceed certain limits, for example, if driver’s eyes are closed for more than two seconds, or if the speed of the vehicle relative to a lane bor der (e.g., indicated through a lane marking) is higher than a certain threshold.

If the resulting driver distraction level exceed the predetermined distraction threshold, an early alert timing is appropriate to provide the driver with more time for reacting appropriately to a given situation.

As an example, a yawning driver that is not engaged in a non-driving-related task (like typing on a mobile phone) and who shows small steering corrections does not exceed the distraction treshold As another example, a non-frequently blinking driver that is engaged in a conversation with the passenger and shows a reduced time headway and an increased number of lane departures exceeds the distraction threshold.

That way, alerts will only be provided if they are really necessary and the driver realizes that if an alert is provided, it has to be taken seriously. This increases safety of operation of a vehicle.

In a first further embodiment of the computer-implemented method, the driver monitoring system detects at least one of a heart rate of the driver, a viewing direction of the driver, a pupil size of a driver’s eye, an eye lid blinking speed, sound generated by the driver and/or a driver input into a human-machine-interface of the vehicle.

It is known that tiredness can be determined through observation of physiological parameters. For example, pupil size and eyelid blinking speed both change in tired humans. A tired person usually has larger pupils, and his eyelids blink slower than those of an attentive driver. Tired persons also tend to have lower breathing speeds and heart rates than awake drivers.

The viewing direction of a driver can help determine his area of attention. E.g., if the driver doesn’t observe the road, he is most likely distracted. If, for example, it is determined that the driver looks downwards, he might be reading. Under these circumstances, it will take longer for the driver to capture and process the current situation and react appropriately.

In another further embodiment of the computer-implemented method, the detected vehicle parameters include at least one of a vehicle speed, a steering angle, a steering angle change rate, a steering angle change amplitude, an accelerator input, and/or a brake input.

It has been found that drivers who are awake and focused usually have lower amplitudes of control inputs into the various vehicle controls like steering wheel, brake pedal and accelerator pedal than tired drivers. A tired driver tends to overexaggerate because of a reduction in fine motor control of the related muscles. Also, it happens quite frequently that tired drivers get startled occasionally which will lead to an overreaction.

In another further embodiment of the computer-implemented method, the late alert value generates an alert later relative to a detection of an alert situation than the early alert value.

That way, a tired or distracted driver will get alerted earlier. In contrast, awake and attentive drivers will receive fewer alerts as the alerts will only be issued late, giving the driver more time to react and deescalate a given situation. In another further embodiment of the computer-implemented method, the alert is at least one of an optical, acoustical, and/or haptical alert signal.

The alerts can be issued via screens, lights, loudspeakers, vibrations, in particular through the steering wheel and the like. In particular if more than one sense of the driver is addressed, it is more likely that a distracted driver will pay attention.

In another further embodiment of the computer-implemented method, a distraction incidence is calculated based on an occurrence of distraction levels equaling or exceeding the distraction threshold, wherein a default alert timing value is set to the early alert value if the occurrence equals or exceeds a predetermined occurrence threshold, wherein the default alert timing value is set to the late alert value if the occurrence is lower than occurrence threshold, wherein the default alert timing value is stored in a storage medium.

Drivers who tend to be distracted more regularly than others will benefit from more and earlier warnings than drivers who are usually alert and focus on driving the vehicle. Monitoring how often a driver is distracted therefore helps to provide appropriate alerts depending on the driver type.

The storage medium can be located in the vehicle. It can alternatively or additionally be located at a server accessible via communication equipment of the vehicle, e.g., telecommunication means implementing protocols like 4G, 5G etc.

In another further embodiment of the computer-implemented method, the driver is detected, wherein the default alert-timing value is set per driver of the vehicle and stored in a driver pro file.

It is common that a vehicle is used by more than one driver. Through detecting who currently drives the vehicle, it is possible to apply the correct baseline alert timing value.

In particular if combined with the above disclosed embodiment, it is possible to transfer the baseline alert timing value to every vehicle used by a respective driver. For example, a driver can be detected, and a request can be made to a server to download the driver's profile which can contain a baseline alert timing value.

In another further embodiment of the computer-implemented method, an intensity of the alert signal is set according to the alert timing value. If the alert timing value is set to a late alert value, an alert will only be provided at a relatively late stage compared to if the alert timing value is set to an early alert value. That way, many alerts can be avoided for focused drivers as they usually react prior to the alert.

In another further embodiment of the computer-implemented method, a configuration of at least one other driving assistance system is changed based on the distraction threshold.

For example, if combined with a lane keeping system, a distracted driver can be warned earlier about a risk of leaving the lane then an attentive driver. If combined with a parking assistance system, an alert could be issued at a greater distance to an obstacle if a driver is drowsy. If combined with an adaptive cruise control system, a threshold distance to another car driving in front of the own vehicle can be increased for distracted drivers and decreased for attentive drivers.

A first independent aspect relates to a computer program product with a non-transitory computer-readable storage medium having commands embedded therein which, when executed by a processor, cause the processor to execute the method as described above.

Another independent aspect relates to a driving assistance system of a vehicle for providing alerts to a driver of the vehicle based on events relating to the vehicle and/or the vehicle’s surroundings through an alert signal generator, with a driver monitoring system for detecting physiological parameters and/or activity-related parameters of the driver, and at least one vehicle sensor for monitoring at least one vehicle parameter, the driver monitoring system, the at least one vehicle sensor and the alert signal generator being connected to a driving assistance system controller, wherein the controller is configured to determine a driver distraction level based on signals of the driver monitoring system and the at least one vehicle sensor, wherein the con troller is further configured to set an alert timing value to an early alert value if the driver distrac tion level equals or exceeds a predetermined distraction threshold, wherein the controller is fur ther configured to set the alert timing value to a late alert value if the driver distraction level is lower than the distraction threshold, wherein the controller is further configured to issue an alert at a timing determined by the alert timing value.

The alert signal generator can generate optical, acoustical or optical alert signals. The driver monitoring system can comprise cameras and other sensors to monitor a driver. The vehicle sensor can be a speed sensor, a steering wheel sensor come on a pedal sensor or the like. In a first further embodiment of the driving assistance system, the controller is further connected to at least one surrounding monitoring sensor, wherein the controller is configured to issue an alert based on an event detected through the surrounding monitoring sensor.

The surrounding monitoring sensor can be a camera, a lidar, a radar, an ultrasound sensor or the like.

Another independent aspect relates to a vehicle with a driving assistance system as described above.

Further features and details will be shown in the following description in which - where applicable with reference to the drawings - at least one exemplary embodiment will be described in detail. Described and/or shown features constitute the subject in itself or in any possible and meaningful combination, eventually also independent from the claims. In particular, they can be subject of one or more separate applications. The figures show schematically:

Fig. 1 a car with a driving assistance system on a lane;

Fig. 2 the driving assistance system of Fig. 1 in more details, and

Fig. 3 a flow-chart of a method of assisting a driver.

Fig. 1 shows a car 2 driving on a lane 4.

The car 2 is equipped a driving assistance system 6 for monitoring a driver’s 8 condition, in par ticular related to the driver’s 8 alertness, or, vice versa, drowsiness, tiredness, or distraction level.

The driving assistance system 6 comprises a driver monitoring system 10 with an eye tracking camera 12. The eye tracking camera 12 can be mounted on a dashboard of the car 2, or it could be located at a ceiling or window column of the car 2. The eye tracking camera 12 can comprise hardware and software enabling identifying driver’s eyes 14 so that the eye tracking camera 12 provides preprocessed information about the driver’s eyes 14. Depending on the concrete embodiment, the hardware and software can enable identifying a viewing direction 16, pupil size and/or blinking speed of the eyes 14. The driver monitoring system 10 further comprises a microphone 18. The microphone 18 moni tors sounds generated in the passenger cabin of the car 2. Through the microphone 18, a breathing speed of the driver 8 can be measured as well as other sounds that can indicate a lack of attention, for example snoring or the like. Also, it is possible to determine whether the driver 8 is engaged in discussions with other passengers or via a mobile communication device. If that is the case, the driver 8 usually needs more time to recognize situations on the lane 4 and react appropriately.

The driving assistance system 6 further comprises a steering angle sensor 20, a wheel speed sensor 22, a brake pedal sensor 24, and an accelerator pedal sensor 26. The steering angle sensor 20 can be located at a steering column of the car 2 or it can be located at a steered wheel of the car 2. The wheel speed sensor 22 is usually located at a wheel of the car 2. Brake pedal sensor 24 and accelerator pedal sensor 26 are located at the respective pedals which are usually located in a footwell area of the passenger cabin of the car 2.

Eye tracking camera 12, microphone 18, steering angle sensor 20, wheel speed sensor 22, brake pedal sensor 24, and accelerator pedal sensor 26 are connected to a controller 30 such that the controller 30 can receive input from the respective aforementioned sensors 20, 22, 24, and 26.

The controller 30 comprises a processor 32 and a non-transitory computer-readable storage medium 34. The non-transitory computer-readable storage medium 34 comprises a computer program product 35, which, if loaded and executed by the processor 32, can execute the methods described in this description.

The controller 30 is also connected to a display 36, a loudspeaker arrangement 38 and a steer ing wheel column actuator 40. The controller 30 can activate one or more of display 36, loud speaker 38, and steering wheel column actuator 40 depending on the circumstances to alert the driver 8.

The controller 30 is further connected to another driving assistance system in the form of a lane keeping assistant 44 with a road camera 46 that monitors an area in front of the car 2 in driving direction 48.

In the situation displayed in Fig. 1, the car 2 drives at an angle relative to the lane 4, i.e., the driving direction 48 is not parallel to lane markings 50 of the lane. The lane keeping assistant 44 identifies the aforementioned circumstance and provides respec tive information to the driving assistance system 6.

As per the methods described herein, the driving assistance system 6 determines a driver distraction value and, if an alert situation occurs, issues an alert according to an alert timing value.

Fig. 2 shows the driving assistance system 6 in more detail.

The controller 30 is connected to the aforementioned monitoring systems 10 and sensors 12,

18, 20, 22, 24, and 26 on the one hand and to the alert generators 36, 38, and 40.

The controller 30 further comprises a timer 54 for timing alerts according to the preset alert timing value.

The controller 30 further comprises a communication module 56. The communication module 56 can connect to a remote server 58 via a mobile communication network 60. Via access to the remote server 58, a driver profile 64 stored in the non-transitory computer-readable storage medium 34 related to the driver 8 can be bidirectionally updated.

The driving assistance system 6 is connected to aforementioned lane keeping assistant 44 and to further driving assistance systems such as a parking assistant 66 and an adaptive cruise control system 68.

Fig. 3 shows a flow chart of the method.

After the start of the method, the driver monitoring system 10 data and the vehicle sensor 20,

22, 24, and 26 data are fed to the controller 30, which then calculates a distraction value based on the sensor input.

After the distraction value is calculated, it is compared to a threshold. If the threshold is met or exceeded, an alert timing value is set to early. Also, an alert mode is adjusted accordingly, e.g., the types of alerts issued and their intensity, e.g., volume, brightness, frequency, etc.

If the threshold is not met or exceeded, the timing value is set to late and the alert mode is adjusted accordingly, e.g., fewer, less dominant alerts. If an alert situation is identified, an alert is issued according to the alert timing value in an alert mode determined by the alert timing value.

Since the distraction situation might be subject to rapid changes, e.g., if a passenger like a child attracts attention, the distraction value is reassessed in short intervals.

The number of early alert timing values and/or the duration thereof is counted and assessed at given intervals, e.g., weekly. If the number, or frequency, equals to or exceeds a certain threshold, a baseline alert timing value is set to early, otherwise it is set to late.

Components and systems described above can be stand-alone or used by other systems of the car. Sensor data such as camera data for example can be provided to different systems and utilized for different purposes. Systems can be implemented as functions in control units with more functionalities, e.g., a function of the aforementioned driving assistance system with multiple components such as lane keeping assistants and adaptive cruise control systems.

While at least one exemplary embodiment has been presented in the foregoing summary and detailed description as well as the claims, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration in any way. Rather, the foregoing summary and detailed description will provide those skilled in the art with a convenient road map for implementing at least one exemplary embodiment, it being understood that various changes may be made in the function and arrangement of elements described in an exemplary embodiment without departing from the scope as set forth in the appended claims and their legal equivalents.

Any feature disclosed in the claims, the description and the drawings, including constructive de tails, relative positioning or method steps can be relevant to the invention taken in isolation or in any meaningful combination with any other feature(s).

Reference numerals car lane driving assistance system driver driver monitoring system eye-tracking camera eyes viewing direction microphone steering angle sensor wheel speed sensor brake pedal sensor accelerator pedal sensor controller processor non-transitory computer-readable storage medium computer program product display loudspeaker arrangement steering wheel column actuator lane keeping assistant road camera driving direction lane marking timer communication module remote server mobile communication network driver profile parking assistant adaptive cruise control system

Claims

1. A computer-implemented method of assisting a driver (8) of a vehicle (2) through provid ing alerts to the driver (8) based on events relating to the vehicle (2) and/or the vehicle’s surroundings (4) using a driving assistance system (6), by detecting a condition of the driver (8) through a driver monitoring system (6) that detects physiological parameters and/or activity-related parameters of the driver (8) and by detecting vehicle parameters, wherein, based on the physiological parameters and/or the activity-related parameters, and the vehicle parameters, a driver distraction level is calculated, wherein, if the driver distraction level equals or exceeds a predetermined distraction threshold, an alert timing value is set to an early alert value, whereas, if the driver distraction level is lower than the threshold, the alert timing value is set to a late alert value, wherein an alert timing is de termined by the alert timing value.

2. The computer-implemented method according to claim 1, wherein the driver monitoring system (6) detects at least one of a heart rate of the driver (8), a viewing direction of the driver (8), a pupil size of a driver’s eye, an eye lid blinking speed, sound generated by the driver (8) and/or a driver input into a human-machine-interface of the vehicle (2).

3. The computer-implemented method according to claim 1 or 2, wherein the detected vehi cle parameters include at least one of a vehicle speed, a steering angle, a steering angle change rate, a steering angle change amplitude, an accelerator input, and/or a brake in put.

4. The computer-implemented method of any of the preceding claims, wherein the late alert value generates an alert later relative to a detection of an alert situation than the early alert value.

5. The computer-implemented method of any of the preceding claims, wherein the alert is at least one of an optical, acoustical, and/or haptical alert signal.

6. The computer-implemented method of any of the preceding claims, wherein a distraction incidence is calculated based on an occurrence of distraction levels equaling or exceed ing the distraction threshold, wherein a default alert timing value is set to the early alert value if the occurrence equals or exceeds a predetermined occurrence threshold, wherein the default alert timing value is set to the late alert value if the occurrence is lower than occurrence threshold, wherein the default alert timing value is stored in a stor age medium.

7. The computer-implemented method of claim 6, wherein the driver is detected, wherein the default alert-timing value is set per driver of the vehicle and stored in a driver profile.

8. The computer-implemented method of any of the preceding claims, wherein an intensity of the alert signal is set according to the alert timing value.

9. The computer-implemented method of any of the preceding claims, wherein a configuration of at least one other driving assistance system (44) is changed based on the distraction threshold.

10. A computer program product with a non-transitory computer-readable storage medium (34) having commands embedded therein which, when executed by a processor (32), cause the processor (32) to execute the method according to any of the preceding claims.

11. A driving assistance system (6) of a vehicle (2) for providing alerts to a driver (8) of the vehicle (2) based on events relating to the vehicle (2) and/or the vehicle’s surroundings (4, 50) through an alert signal generator (36, 38, 40), with a driver monitoring system (6) for detecting physiological parameters and/or activity-related parameters of the driver (8), and at least one vehicle sensor (20, 22, 24) for monitoring at least one vehicle parameter, the driver monitoring system (6), the at least one vehicle sensor (20, 22, 24) and the alert signal generator (36, 38, 40) being connected to a driving assistance system controller (30), wherein the controller (30) is configured to determine a driver distraction level based on signals of the driver monitoring system (6) and the at least one vehicle sensor (20, 22, 24), wherein the controller (30) is further configured to set an alert timing value to an early alert value if the driver distraction level equals or exceeds a predetermined distraction threshold, wherein the controller (30) is further configured to set the alert timing value to a late alert value if the driver distraction level is lower than the distraction threshold, wherein the controller (30) is further configured to issue an alert at a timing determined by the alert timing value.

12. The driving assistance system of claim 11 , wherein the controller (30) is further connected to at least one surrounding monitoring sensor (46), wherein the controller (30) is configured to issue an alert based on an event detected through the surrounding monitoring sensor (46).

13. Vehicle with a driving assistance system (6) according to claim 11 or 12.