Patent Description:
Current pedestrian warning systems, and the legislation that requirements them, are directed to passive systems in which the vehicle emits a warning sound (often synthesized to sound like an internal combustion engine driven vehicle) generally in the direction of travel of the vehicle and usually below some threshold speed (e.g. <<NUM>/h).

While such warming sounds may be useful when the there are a small number of vehicles in the vicinity of a pedestrian, they are likely less effective in congested urban setting with heavy traffic concentration due to the masking effect created by the confluence of noise emitted by the numerous vehicles.

In addition the current systems assume that the pedestrian is attuned to, and paying attention to, the 'engine like' sounds being emitted.

External alert sounds that warn of the approach of quiet vehicles are an emerging requirement from automakers due to concerns over pedestrian and cyclist safety and because of legislation in several countries. These sounds are typically only produced when the vehicle is moving below a certain speed, but may also adapt in nature (loudness/pitch) depending on speed. Current external alert sounds have limitations such as those described below.

Current external alert sounds are typically replayed at a constant volume irrespective of the noise level in the physical environment around the car. For example very noisy street environments with many conflicting and confusing sound and noise sources can confuse pedestrians and cyclists. Conversely in very quiet environments (such as late at night in a residential neighborhood) loud alert sounds would be disturbing to people around.

Current external alert sounds are not directed toward the intended direction of motion of the vehicle. For example, an existing electric vehicle waiting to turn left across oncoming traffic where there is a pedestrian crossing would have its alert sounds projected forward but the actual intended direction of motion is at a right angle.

Current external alert sounds may not be easily localized. That is, the nature of the sounds used make it difficult for a human being to determine the origin of the sound source.

There is a need for a system and method for pedestrian alert that mitigates or eliminates one or more of the deficiencies described above. <CIT> discloses a method for monitoring and signaling a traffic situation in the surrounding environment of a vehicle, wherein a sensor acquires a surrounding environment of the vehicle, an object at risk is recognized in the acquired environment, and a collision probability and a prediction reliability are determined for the recognized object at risk. When there is a given collision probability and a low prediction reliability an action of a first type is carried out, and when there is a given collision probability and a high prediction reliability an action of a second type is carried out. <CIT> discloses a method for directing a vehicle to operate in a noise generating mode based on a context. A present location of the vehicle is determined using a location sensing device. Then, it is determined whether the present location of the vehicle is within one or more noise generating zones. In response to determining that the present location of the vehicle is within a noise generating zone, the vehicle is directed to operate in the noise generating mode.

According to aspects of the present invention, there are provided a method, a system, a machine-readable medium and a vehicle according to claims <NUM>, <NUM>, <NUM> and <NUM>.

The system and method may be better understood with reference to the following drawings and description.

Other systems, methods, features and advantages will be, or will become, apparent to one with skill in the art upon examination of the following figures and detailed description. It is intended that all such additional systems, methods, features and advantages be included with this description and be protected by the following claims.

Described are a system and method for pedestrian alert that derives a pedestrian path representing a projected path for a pedestrian, derives a vehicle path representing a projected path for a motor vehicle, determines an intersection of the pedestrian path and the vehicle path, determines alert characteristics responsive to the determined intersection, and generates an alert that is emitted from the vehicle responsive to the determined alert characteristics.

The system and method for pedestrian alert may be built, installed or implemented in a motor vehicle such as an automobile, passenger bus, commercial vehicle or other similar motorized vehicles that are operated in environments where they may be in close proximity to pedestrians. The system and method for pedestrian alert mitigates the likelihood of a collision between the motor vehicle and a pedestrian by emitting an alert that may draw the attention of the pedestrian to the presence of the motor vehicle.

While the system and method for pedestrian alert is described referencing a pedestrian, it is to be understood that the system and method are equally applicable with reference to a person riding a bicycle or skateboard, a person in a wheel chair or motorized chair, a pet animal (e.g. a dog), a domesticated animal (e.g. a sheep or cow) or wildlife (e.g. a deer).

<FIG> is a schematic representation of a system for pedestrian alert <NUM>. The system for pedestrian alert <NUM> may comprise a pedestrian path deriver <NUM>, a vehicle path deriver <NUM>, an intersection determiner <NUM>, an alert characteristic generator <NUM> and an alert generator <NUM>.

<FIG> is a schematic representation of a scenario in which the system for pedestrian alert <NUM> may be used from an overhead perspective. Included in the example scenario <NUM> are a motor vehicle <NUM> and three pedestrians 204A, 204B and 204C (collectively or generically pedestrians <NUM>). Pedestrian 204B is a cyclist while pedestrians 204A and 204B are on foot. The example motor vehicle <NUM> is equipped and/or has installed therein a system for pedestrian alert <NUM>, one or more pedestrian sensors <NUM>, one or more emitters <NUM> and one or more environment sensors <NUM>. The scenario <NUM> also includes a respective predicted path of travel for the pedestrian 206A, 206B and 206C (collectively or generically predicted path of travel for the pedestrian <NUM>) for each of the pedestrians 204A, 204B and 204C. The scenario <NUM> also includes a predicted path of travel for the motor vehicle <NUM>. The scenario <NUM> further includes a respective alert signal 160A and 160B (collectively or generically alert signal <NUM>) for each of pedestrians 204A and 204B.

Referring again to <FIG>, the pedestrian path deriver <NUM> may receive input signals and data from pedestrian sensors <NUM> and/or a pedestrian detection system <NUM>. The pedestrian sensors <NUM> may include one or more of optical/vision sensors (e.g. cameras), infrared sensors, ultrasonic sensors, laser/LIDAR, radar, inductive loop and other similar well know sensors for detecting the presence and position of pedestrians <NUM> that are in proximity of the motor vehicle <NUM>. The pedestrian detection system <NUM> may also, or alternatively, receive input signals and data from pedestrian sensors <NUM>. The pedestrian detection system <NUM> may be any known system or sub-system for detecting the presence and position of pedestrians <NUM> that are in proximity of the motor vehicle <NUM>. The pedestrian detection system <NUM> may be a standalone system or may be a sub-system of another advanced driver assistance system (ADAS) equipped in the motor vehicle <NUM> such as, for example, a pedestrian warning system that provides a warning to the motor vehicle operator (e.g. driver) that a pedestrian <NUM> has been detected and that may additional initiate braking action. The pedestrian detection system <NUM> may be able to recognize and distinguish different pedestrian types such as, for example, pedestrians on foot, cyclists and animals and may provide this information to other components of the system for pedestrian alert <NUM> such as the pedestrian path deriver <NUM> and alert characteristics generator <NUM>.

The pedestrian path deriver <NUM> may derive a predicted path of travel for a detected pedestrian based on, for example, a time sequence analysis of a series of positions (e.g. locations) and times where the pedestrian <NUM> has been detected. The analysis may use any known technique including, for example, numerical analysis methods such as extrapolation or regression to generate future predicted positions (locations) for the pedestrian <NUM> thereby deriving a predicted path of travel for the pedestrian <NUM>. The predicted path of travel for the pedestrian <NUM> may include any of a bearing, projected path algorithm/function and a pedestrian speed. The predicted path of travel for the pedestrian <NUM> may indicate that the pedestrian <NUM> is substantially stationary when that is the case.

The vehicle path deriver <NUM> may receive input signals and data from vehicle path sensors <NUM> and/or navigation system <NUM>. The vehicle path sensors <NUM> may include one or more sensor associated with vehicle speed, steering angle, global positioning system (GPS), yaw, compass bearing, road/lane detection, turn signal operation, road map, route and other similar sensors. The navigation system <NUM> may also or alternatively receive input signals and data from vehicle path sensors <NUM>. The navigation system <NUM> may be any known system or sub-system for navigating a selected route and/or determining the location of the motor vehicle <NUM> relative to a road map.

The vehicle path deriver <NUM> may derive a predicted path of travel for the motor vehicle <NUM> based on, for example, applying any known projection algorithms to the signals and data received from the vehicle path sensors <NUM>. Alternatively, or in addition, the vehicle path deriver <NUM> may derive the predicted path of travel for the motor vehicle <NUM> base on signals and data received from the navigation system <NUM> including, for example, a selected route and/or road map data. The predicted path of travel for the motor vehicle <NUM> includes future predicted positions (locations) for the motor vehicle <NUM>. The predicted path of travel for the motor vehicle <NUM> may include any of a bearing, projected path algorithm, route and a motor vehicle speed.

The intersection determiner <NUM> receives the predicted path of travel for the pedestrian <NUM> from the pedestrian path deriver <NUM> and the predicted path of travel for the motor vehicle <NUM> from the vehicle path deriver <NUM>. The intersection determiner <NUM> may use future time sequence analysis to determine if the predicted path of travel for the pedestrian <NUM> will intersect the predicted path of travel for the motor vehicle <NUM> at some future point in time. The determination may result in a determination that intersection <NUM> will occur or will not occur. In addition to the predicted path of travel for the pedestrian <NUM> and the predicted path of travel for the motor vehicle <NUM>, the intersection determination may take into account other factors such as, for example, the width of the motor vehicle, turning radius of the motor vehicle, road map information and other similar factors. When a determination is made that intersection <NUM> will occur (e.g. a collision between the pedestrian 204A and the motor vehicle <NUM> is imminent), one or more intersection locations and corresponding intersection times where the intersection <NUM> will occur may be calculated (e.g. predicted).

The alert characteristics generator <NUM> receives the results of the intersection determination (e.g. intersection will occur or intersection will not occur) and when the determination is that intersection <NUM> will occur, may also receives the one or more intersection locations and corresponding intersection times from the intersection determiner <NUM>. The alert characteristic generator <NUM> may also receive the predicted path of travel for the pedestrian <NUM> from the pedestrian path deriver <NUM> and the predicted path of travel for the motor vehicle <NUM> from the vehicle path deriver <NUM>. The alert characteristic generator <NUM> may also receive an indication of pedestrian type (e.g. pedestrian on foot, cyclist or animal) from the pedestrian path deriver <NUM> or the pedestrian detector <NUM>. The alert characteristic generator <NUM> may also receive signals or data from one or more environment sensors <NUM> such as, for example, one or more externally mounted microphones for detecting background noise levels in the environment through which the motor vehicle <NUM> is traveling. The alert characteristics generator <NUM> generates characteristics of an alert signal in response to the received inputs described above. The alert signal <NUM> is a signal that is emitted from the motor vehicle <NUM> to alert the pedestrian <NUM> of presence and location of the motor vehicle <NUM> and of a potential intersection (e.g. collision) with the motor vehicle <NUM>.

The alert characteristics generated by the alert characteristics generator <NUM> include a loudness (a. sound pressure level, volume or gain) and a direction, and may further include one or more of a
pitch or frequency, alert signal content and other alert characteristics. For example, the loudness may be adjusted up or down in response to the level of environmental noise detected by the external microphones <NUM> in order to achieve a substantially constant audibility for a specific human hearing capability at a range appropriate to the speed of the motor vehicle. In another example, the loudness may be adjusted up or down based on the substantial direction of travel (e.g. toward or away from) relative to the direction of travel of the motor vehicle <NUM>. The loudness may also be increased over time when the intersection determiner <NUM> continues to determine that intersection will occur (e.g. a collision between the pedestrian <NUM> and the motor vehicle <NUM> is imminent) after the alert signal <NUM> has been emitted for some time.

The alert signal content may include impulse sounds. Impulsive sound sources that contain transient broadband information are, in general, more easily localized than continuous tone or periodic signals. The sound signal content may be adapted to be more easily audible by people (e.g. the elderly) with most common forms of hearing loss. The sound signal content may, for example, include sounds that produce most energy below <NUM> thereby adapting the alert signal to the most common form of hearing loss which is a "noise-induced notch" that occurs around <NUM>. Such a sound signal content may also have greater range at the same amplitude compared to a signal with more energy in the higher frequency content because sound absorption in air increases with frequency. The sound signal content may alternatively or in addition include a component specifically audible to animals (e.g. pets or wildlife) either all of the time or when the detected pedestrian type is animal rather than human.

The generated alert characteristics may include a direction that changes over time in response to the predicted path of travel for the pedestrian <NUM> and the predicted path of travel for the motor vehicle <NUM> in order for the alert signal <NUM> to be emitted in the direction of the pedestrian <NUM> even as the motor vehicle <NUM> and/or pedestrian <NUM> continue to move relative to each other over time.

The alert generator <NUM> receives the alert characteristics generated by the alert characteristics generator <NUM> and generates an alert signal <NUM> that is emitted by the emitters <NUM>. The emitters <NUM> may include one or more of fixed audio transducers (a. loudspeakers), steerable audio transducers, ultrasonic transducers or other similar mechanisms that can be used to generate a directionally controllable audio signal (a. alert signal <NUM>) to be directed at the pedestrian <NUM>. Alert signal <NUM> directionality may be achieved from an array of loudspeakers using known phase and amplitude modulation (e.g. phase array) techniques. Alternatively, or in addition, alert signal <NUM> directionality may be achieved by selecting one or more audio transducers from an array of transducers or by steering one or more steerable audio transducers.

The alert signal <NUM> may be generated in addition to, as a modification to, or in place of, another warning signal such as, for example, an omnidirectional or fixed direction pedestrian warning that is required for electric vehicles in some jurisdictions.

The alert signal <NUM> may be of a higher in frequency so that its source can be more easily located by the pedestrian <NUM>, is more attention grabbing than the regular warning sound, and is emitted at a higher volume. In addition the alert sound volume can be continually increased if the system <NUM> continues to determine that pedestrian and vehicle paths will intersect.

Operation of the system for pedestrian alert <NUM> may be ongoing over time. Each of the inputs received from the various sensors and each of the outputs generated by the components of the system <NUM> described herein may be reasserted, updated, added or removed on a continuous or periodic basis over time. Each of the derivations, determinations and generations generated by the components of system <NUM> describe herein may be recalculated, reassessed or regenerated on a continuous or periodic basis over time.

The system can detect a cyclist 204B travelling in the same direction as the vehicle (in the same or an adjacent lane) and emit an alert signal <NUM> having different alert characteristics that is intended to draw the cyclists 204B attention to the presence of the motor vehicle <NUM> rather than warn of an impact.

The system for pedestrian alert <NUM> may be used for either forward travel only or both forward and backward (reversing) travel of the motor vehicle <NUM>. In addition the system for pedestrian alert <NUM> may be used in either or both of vehicles mandated to have static pedestrian warning systems installed (e.g. electric vehicles) and vehicles that are not so mandated (e.g. internal combustion engine driven vehicles).

<FIG> is a representation of a method for pedestrian alert. The method for pedestrian alert <NUM> may be, for example, implemented using any of the systems <NUM> and <NUM> described herein with reference to <FIG> and <FIG>. The method for pedestrian alert <NUM> may include the following actions.

Deriving a predicted path of travel for the pedestrian <NUM>. The predicted path of travel for a pedestrian <NUM> may be derived using any known techniques including, for example, numerical analysis methods such as those described above. The derivation may be based on signals and data received from pedestrian sensors <NUM> and/or pedestrian detection system <NUM>. Multiple predicted paths of travel for pedestrian 206A, 206B and 206C may be derived concurrently, each for a respective pedestrian 204A, 204B and 204C.

Deriving a predicted path of travel for the motor vehicle <NUM>. The predicted path of travel for the motor vehicle <NUM> may be derived by applying any known projection algorithms to the signals and data received from the vehicle path sensors <NUM>. Alternatively, or in addition, the vehicle path deriver <NUM> may derive the predicted path of travel for the motor vehicle <NUM> base on signals and data received from the navigation system <NUM> including, for example, a selected route and/or road map data.

Determining intersection of the predicted path of travel for the pedestrian and the predicted path of travel for the motor vehicle <NUM>. Determination of intersection may use future time sequence analysis to determine if the predicted path of travel for the pedestrian <NUM> will intersect the predicted path of travel for the motor vehicle <NUM> at some future point in time. The determination may result in a determination that intersection <NUM> will occur or will not occur. In addition to the predicted path of travel for the pedestrian <NUM> and the predicted path of travel for the motor vehicle <NUM>, the intersection determination may take into account other factors such as, for example, the width of the motor vehicle, turning radius of the motor vehicle, road map information and other similar factors. When a determination is made that intersection <NUM> will occur (e.g. a collision between the pedestrian 204A and the motor vehicle <NUM> is imminent), one or more intersection locations and corresponding intersection times where the intersection <NUM> will occur may be calculated (e.g. predicted). The predicted path of travel for the pedestrian <NUM> may not intersect the predicted path of travel for the motor vehicle <NUM> when the predicted path of travel for the pedestrian 206B is substantially parallel to the predicted path of travel for the motor vehicle <NUM>, for example, in the case of cyclist 204B. The predicted path of travel for the pedestrian <NUM> may not intersect the predicted path of travel for the motor vehicle <NUM> when the predicted path of travel for the pedestrian 206C is laterally displaced from and non-convergent on the predicted path of travel for the motor vehicle <NUM>, for example, in the case of pedestrian 204C walking on a sidewalk or on the roadside.

Determining alert characteristics <NUM>. Determination of alert characteristics uses the results of the intersection determination act <NUM> (e.g. intersection will occur or intersection will not occur). When the determination is that intersection <NUM> will occur, determination of alert characteristics may also use the one or more intersection locations and corresponding intersection times generated in the intersection determination act. Determination of alert characteristics may also use the predicted path of travel for the pedestrian <NUM> and the predicted path of travel for the motor vehicle <NUM>. Determination of alert characteristics may also use an indication of pedestrian type (e.g. pedestrian on foot, cyclist or animal). Determination of alert characteristics may also use signals or data from one or more environment sensors <NUM> such as, for example, one or more externally mounted microphones for detecting background noise levels in the environment through which the motor vehicle <NUM> is traveling. Determination of alert characteristics includes generating characteristics of an alert signal in response to the received inputs described above. The alert signal <NUM> is a signal that is emitted from the motor vehicle <NUM> to alert the pedestrian <NUM> of presence and location of the motor vehicle <NUM> and optionally of a potential intersection (e.g. collision) with the motor vehicle <NUM>.

The alert characteristics that are determined (e.g. generated) include a loudness and a direction, and may further include one or more of a pitch or frequency, alert signal content and other alert characteristics. For example, the loudness and pitch characteristics that are determined for an alert signal 160A that will be directed at a pedestrian 204A for whom an intersection has been determined will typically be louder and sharper (e.g. more attention seeking) than the loudness and pitch characteristics that are determined for an alert signal 160B that will be directed at a pedestrian 204B that is proximate to the motor vehicle <NUM> but for whom no intersection has been determined. The alert characteristic such as loudness and pitch determined for pedestrian 204A may be determined to ensure that the alert signal 160A attracts the pedestrian's attention and warns the pedestrian 204A of the danger posed by an imminent collision. In the case of pedestrian 204B the alert characteristics such as loudness and pitch may be determined so that the alert signal 160B alerts the pedestrian 204B of the presence of the motor vehicle <NUM> without being startling or distracting. For pedestrian 206C who is not in close proximity to the motor vehicle <NUM> and for whom no intersection has been determined the alert characteristic may be determined so that no alert signal <NUM> is generated.

The determined loudness characteristic may be adjusted up or down in response to the level of environmental noise detected by the external microphones <NUM> in order to achieve a substantially constant audibility for a specific human hearing capability at a range appropriate to the speed of the motor vehicle <NUM>. The loudness may also be increased over time when the intersection determination act <NUM> continues to determine that intersection will occur (e.g. a collision between the pedestrian 204A and the motor vehicle <NUM> is imminent) even after the alert signal <NUM> has been emitted for some time.

The alert signal content may include impulse sounds. Impulsive sound sources that contain transient broadband information are, in general, more easily localized than continuous tone or periodic signals. The sound signal content may
include a component specifically audible to animals (e.g. pets or wildlife) either all of the time or when the detected pedestrian type is animal rather than human.

Determination of alert characteristics corresponding to one or more alert signals <NUM> may be determine concurrently where each set of alert characteristics is associated with a respective one of one or more pedestrians (e.g. 204A, 204B and 204C).

Generating the alert signal <NUM>. Generation of the alert signal uses the alert characteristics resulting from the alert characteristics determination act <NUM> and generates an alert signal <NUM> that is emitted by the emitters <NUM>. Alert signal <NUM> directionality may be achieved using any of the mechanisms described above with reference to signal generator <NUM> responsive to direction characteristics resulting from the alert characteristics determination act <NUM>. The direction of the alert signal <NUM> may be changed or updated over time in response to a changing or updated direction characteristic. Other characteristic of the generated alert signal <NUM> such as, for example, loudness may also change over time in response to changes made in the alert characteristics determination act <NUM>. One or more different alert signals such as 160A and 160B may be generated concurrently responsive to respective corresponding sets of alert characteristics resulting from the alert characteristics determination act <NUM>.

Other embodiments of a method for pedestrian alert may include more, fewer, or different acts than those illustrated in <FIG>. The method for pedestrian alert <NUM> is ongoing over time. Each of the inputs received from the various sensors and each of the outputs generated by acts of the method <NUM> described herein may be reasserted, updated, added or removed on a continuous or periodic basis over time. Each of the derivations, determinations and generations generated by the acts of
method <NUM> describe herein may be reassessed or regenerated on a continuous or periodic basis over time.

<FIG> is a schematic representation of a system for pedestrian alert. The system <NUM> comprises a processor <NUM>, memory <NUM> (the contents of which are accessible by the processor <NUM>) and an I/O interface <NUM>.

The processor <NUM> may comprise a single processor or multiple processors that may be disposed on a single chip, on multiple devices or distributed over more that one system. The processor <NUM> may be hardware that executes computer executable instructions or computer code embodied in the memory <NUM> or in other memory to perform one or more features of the system. The processor <NUM> may include a general purpose processor, a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), a digital circuit, an analog circuit, a microcontroller, any other type of processor, or any combination thereof.

The memory <NUM> may comprise a device for storing and retrieving data, processor executable instructions, or any combination thereof. The memory <NUM> may include non-volatile and/or volatile memory, such as a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or a flash memory. The memory <NUM> may comprise a single device or multiple devices that may be disposed on one or more dedicated memory devices or on a processor or other similar device. Alternatively or in addition, the memory <NUM> may include an optical, magnetic (hard-drive) or any other form of data storage device.

The memory <NUM> may store instructions which when executed using the process <NUM> may cause the system <NUM> to render the functionality associated with pedestrian path deriver <NUM>, vehicle path deriver <NUM>, intersection determiner <NUM>, alert characteristics generator <NUM> and alert generator <NUM> as described herein. The computer code may be written in any computer language, such as C, C++, assembly language, channel program code, and/or any combination of computer languages. In addition the memory <NUM> may store the predicted path of travel of pedestrian <NUM>, predicted path of travel of motor vehicle <NUM> and alert characteristics <NUM>.

The I/O interface <NUM> may be used to connect devices such as, for example, pedestrian sensors <NUM>, vehicle path sensors <NUM>, environment sensors <NUM>, emitters <NUM> and to other components of the system <NUM>.

All of the disclosure, regardless of the particular implementation described, is exemplary in nature, rather than limiting. The systems <NUM> and <NUM> may include more, fewer, or different components than illustrated in <FIG> and <FIG>. Furthermore, each one of the components of systems <NUM> and <NUM> may include more, fewer, or different elements than is illustrated in <FIG> and <FIG>. Flags, data, databases, tables, entities, and other data structures may be separately stored and managed, may be incorporated into a single memory or database, may be distributed, or may be logically and physically organized in many different ways. The components may operate independently or be part of a same program or hardware. The components may be resident on separate hardware, such as separate removable circuit boards, or share common hardware, such as a same memory and processor for implementing instructions from the memory. Programs may be parts of a single program, separate programs, or distributed across several memories and processors.

The functions, acts or tasks illustrated in the figures or described may be executed in response to one or more sets of logic or instructions stored in or on computer readable media. The functions, acts or tasks are independent of the particular type of instructions set, storage media, processor or processing strategy and may be performed by software, hardware, integrated circuits, firmware, micro code and the like, operating alone or in combination. Likewise, processing strategies may include multiprocessing, multitasking, parallel processing, distributed processing, and/or any other type of processing. In one embodiment, the instructions are stored on a removable media device for reading by local or remote systems. In other embodiments, the logic or instructions are stored in a remote location for transfer through a computer network or over telephone lines. In yet other embodiments, the logic or instructions may be stored within a given computer such as, for example, a CPU.

Claim 1:
A method comprising:
determining (<NUM>) an intersection (<NUM>) of a first path representing a predicted path for a person or animal and a second vehicle path representing a predicted path for a vehicle over a continuous time period;
determining (<NUM>) an alert characteristic responsive to the intersection, the alert characteristic including a loudness characteristic and a direction characteristic;
emitting (<NUM>) a directionally controllable alert signal (160A, 160B) from the vehicle (<NUM>) in a direction toward the person or animal responsive to the direction characteristic; and
increasing loudness of the emitted alert signal (160A, 160B) over said continuous time period.