A CONTROLLER TO DETERMINE CRASH INFORMATION

OF A VEHICLE AND METHOD FOR THE SAME

2. Applicants: a. Name: Bosch Global Software Technologies Private Limited Nationality: INDIA

Address: 123, Industrial Layout, Hosur Road, Koramangala, Bangalore - 560095, Karnataka, India b. Name: Robert Bosch GmbH

Nationality: GERMANY

Address: Feuerbach, Stuttgart, Germany

Complete Specification:

The following specification describes and ascertains the nature of this invention and the manner in which it is to be performed. Field of the invention:

[0001] The present invention relates to a controller to determine crash information of/for a vehicle and method for the same.

Background of the invention:

[0002] Generally, two-wheeler vehicle accidents mostly end up highly fatal. Currently, there are solutions existing with six dimensional Inertial Measurement Unit (IMU) to detect the crash and trigger the emergency which is an expensive solution. For the vehicles without IMU but with rollover sensor, there exists no method to detect and classify the crash and trigger emergency services.

[0003] According to state of the art US 10165429, a systems and methods for facilitating vehicle incident communications. The prior art disclosure relates to facilitating vehicle incident communications. In one use case, a mobile device may detect a vehicular accident and determine one or more contacts to notify about the vehicular accident. An occupant of the vehicle may be prompted, via a user interface of the mobile device, to confirm or cancel a proposed communication to the contact(s). Upon confirmation of the proposed confirmation, the communication to the contact(s) may be transmitted.

Brief description of the accompanying drawings:

[0004] An embodiment of the disclosure is described with reference to the following accompanying drawings,

[0005] Fig. 1 illustrates a block diagram of a controller to determine crash information of a vehicle, according to an embodiment of the present invention, and [0006] Fig. 2 illustrates a method for determining crash information of the vehicle, according to the present invention.

Detailed description of the embodiments:

[0007] Fig. 1 illustrates a block diagram of a controller to determine crash information of a vehicle, according to an embodiment of the present invention. The controller 110 configured to receive input signals comprising primary parameters 116 measured by in-vehicle sensors 104, 106, 108, 112, ... , 114. The primary parameters 116 comprises, an accelerator pedal status from a pedal/throttle sensor 104, a clutch status from a clutch switch 106, a gear position from respective sensors/s witches (not shown), a vehicle speed, wheel speeds for a front wheel and a rear wheel from respective wheel speed sensors 108, a front and rear brake status from respective sensor/s witches 112, and front and rear brake pressures from respective pressure sensors 114 of hydraulic braking unit. Although the controller 110 is configurable to receive other parameters as well (such as an engine speed from an engine speed sensor, etc.,), but only few parameters are mentioned for simplicity in understanding the present invention. The controller 110 further configured to receive input signals comprising secondary parameters 118 measured by in-built sensors 122, 124, 126, ... , 128 of a mobile device 120, characterized in that, upon detection of rollover status of the vehicle 100 as true, as detected/sensed by a rollover sensor 102, the controller 110 processes the primary parameters 116 and the secondary parameters 118 in a conditional manner and determine crash information of the vehicle 100.

[0008] According to another embodiment of the present invention, the controller 110 configured detect rollover status from the rollover sensor 102 as true, and then receive input signals comprising primary parameters 116 measured by in-vehicle sensors 104, 106, 108, 112, ... , 114. The primary parameters 116 comprises, the accelerator pedal status from the pedal/throttle sensor 104, the clutch status from the clutch switch 106, the gear position from respective sensors/switches (not shown), the vehicle speed, wheel speeds for the front wheel and the rear wheel from respective wheel speed sensors 108, the front and rear brake status from respective sensor/switches 112, and front and rear brake pressures from respective pressure sensors 114 of hydraulic braking unit. Although the controller 110 is configurable to receive other parameters as well (such as an engine speed from an engine speed sensor, etc.,), but only few parameters are mentioned for simplicity in understanding the present invention. The controller 110 further configured to receive input signals comprising secondary parameters 118 measured by in-built sensors 122, 124, 126, ... , 128 of the mobile device 120, characterized in that, the controller 110 processes the primary parameters 116 and the secondary parameters 118 in the conditional manner and determine crash information of the vehicle 100.

[0009] According to an embodiment of the present invention, the crash information is at least one of, a crash type and a crash severity. The crash type is determined to be any one selected from a group comprising a front crash, a rear crash, a side crash, and a skid. The crash severity is determined to be any one selected from a group comprising a low level, a medium level, and a high level for each of the crash type.

[0010] According to the present invention, the controller 110 is provided with necessary signal detection, acquisition, and processing circuits. The controller 110 is the control unit which comprises input/output interfaces having pins or ports, a memory element (not shown) such as Random Access Memory (RAM) and/or Read Only Memory (ROM), Analog-to-Digital Converter (ADC) and a Digital-to- Analog Convertor (DAC), clocks, timers, counters and at least one processor (capable of implementing machine learning) connected with each other and to other components through communication bus channels. The memory element is prestored with logics or instructions or programs or applications or modules/models and/or threshold values/ranges, which is/are accessed by the at least one processor as per the defined routines. The internal components of the controller 110 are not explained for being state of the art, and the same must not be understood in a limiting manner. The controller 110 may also comprise communication units to communicate with ECU of the vehicle 100 or a MCU of a mobile device 120, through wireless or wired means such as Global System for Mobile Communications (GSM), 3G, 4G, 5G, Wi-Fi, Bluetooth, Ethernet, serial networks, and the like. The controller 110 is implementable in the form of System-in-Package (SiP) or System-on-Chip (SOC) or any other known types. [0011] According to an embodiment of the present invention, processing of the primary parameters 116 and the secondary parameters 118 in a conditional manner comprises processing of at least one of selected from a group comprising at least one of the primary parameters 116 and at least one of the secondary parameters 118, as per predefined set of conditions, namely, a first set of condition, a second set of condition, a third set of condition and a fourth set of condition, for determination of respective crash type. In other words, either primary parameters 116 are used alone, or secondary parameters 118 are used alone or both of them are used together for determination of the crash type. For example, the front crash, the rear crash, and the skid is determined using the primary parameters 116, whereas the side crash is determined using the secondary parameters 118. Although the determination of the crash type or crash severity is done using the primary parameters 116 and secondary parameters 118, but the plausibility of the determined crash type and/or crash severity is made using the secondary parameters 118 in addition to the determined crash type.

[0012] According to an embodiment of the present invention, the controller 110 processes all the predefined set of conditions, i.e., the first set of condition, the second set of condition, the third set of condition and the fourth set of condition in parallel and processes further based on the whichever is detected to be true. Alternatively, the controller 110 is configured to process the first set of condition, the second set of condition, the third set of condition and the fourth set of conditions in a pre-set sequence. The processing stops when a specific set of conditions is detected to be true and the rest are skipped or ignored, thereby increasing the processing time.

[0013] According to an embodiment of the present invention, the controller 110 is configured to determine front crash/collision of the vehicle 100. As per the first set of conditions, the controller 110 is configured to monitor real-time speed profile of the vehicle 100 and an acceleration profile of the vehicle 100 for an abnormal pattern, upon detection of the rollover status as true. The speed profile and the acceleration profile are monitored in dependence of or after an emergency braking status is detected to be true. The emergency braking status is determined based on a running status of the vehicle 100, a brake pedal status and a brake pressure as detected by respective sensor. The brake pressure is checked to identify the difference between emergency and normal braking. For example, if rollover status is detected to be true, the brake pedal status is also true, and the vehicle acceleration is less than a calibratable threshold acceleration, only then the front crash is determinable. Specifically, after rollover status is detected, if the brake status is true and the vehicle acceleration is less than the threshold acceleration for the time duration before the instant of detection of the rollover status, the front crash is said to be determined. The vehicle acceleration data for threshold time duration (calibratable) before the instant of detection of rollover is considered for monitoring the acceleration profile. If “t” is the time of detection of rollover status as true, then “T” is the threshold time duration, and the data considered for acceleration profile is “t-T” onwards till time “t” The monitoring of acceleration profile comprises searching for specific acceleration pattern, such as sudden decrease and then increase, etc. Similarly, monitoring of the speed profile comprises detection of pattern of vehicle speed in the speed data stored for threshold time duration, i.e., “t- T” time onwards. It is to be noted that, “T” is calibratable. In an embodiment, the crash severity is determined based on a level of vehicle speed at “t-T” onwards after detection of rollover status as true.

[0014] According to the present invention, the vehicle speed is either directly measured from the wheel speed sensors 108 for front wheel(s) and the rear wheel(s) or modelled using engine speed, gear position/number and gear ratio. The vehicle speed is modelled to plausiblize with the measured vehicle speed using wheel speed sensors 108. The modelled vehicle speed is helpful in case of failure or error in measuring the wheel speed sensors 108 and/or crash. Similarly, vehicle running condition status is checked based on ignition status and vehicle speed. The acceleration profile is monitored using vehicle acceleration signal and upon receiving the emergency braking status. The speed profile is monitored using vehicle speed signal and upon receiving the emergency braking status.

[0015] According to an embodiment of the present invention, the controller 110 is configured to determine the rear crash event/incident of the vehicle 100 based on the second set of condition. As per the second set of condition, the controller 110 is configured to monitor speed profile of the vehicle 100 and acceleration profile of the vehicle 100 upon detection of rollover status to be true for the abnormal pattern. The speed profile of the vehicle 100 is monitored in dependence of a driver demand status. The driver demand status is based on vehicle running status, accelerator pedal signal, and clutch pedal status using respective sensors. For example, vehicle acceleration is greater than a second threshold acceleration without any changes in accelerator pedal or throttle or decreasing accelerator pedal without clutch disengagement. Specifically, when rollover status is detected to be true, and if the rate of change of acceleration is less than a threshold value, along with the rate of change of speed is less than second threshold speed, the controller 110 determines the crash to be rear crash. A misdetection of quick shift or cruise control as the rear crash event is avoided. Again, the crash severity is determined based on the vehicle speed and/or combination of at least one secondary parameters. The speed data and the acceleration data considered for profiling or pattern recognition is from “t-T” time onwards till “t”, i.e., the threshold time duration, as explained previously. For example, the abnormal pattern comprises sudden increase or decrease in vehicle acceleration profiles without change in driver demand such as accelerator pedal status, brake pedal status, clutch pedal status, etc.

[0016] According to an embodiment of the present invention, the controller 110 is configured to determine side crash event of the vehicle 100 based on third set of conditions. As per the third set of conditions, the controller 110 monitors the at least one secondary parameter 118 measured by in-built sensors of the mobile device 120 upon detection of the rollover status to be true. [0017] According to an embodiment of the present invention, the controller 110 is configured to detect crash due to skid of the vehicle 100 based on the fourth set of conditions. As per the fourth set of conditions, the controller 110 is configured to monitor and detect vehicle slip based on brake status, brake pressure and upon detection of rollover status to be true.

[0018] According to an embodiment of the present invention, the crash severity is determined and plausibilized based on at least one selected from a group comprising at least one of said primary parameters 116 and at least one of said secondary parameters 118. The at least one secondary parameter 118 comprises a strength of wireless connection signal between the mobile device 120 connected to the vehicle 100, the vehicle speed before detection of the crash event, a crash notification, a vehicle speed using the mobile device 120 after detection of the crash event, an output of an accelerometer sensor 124, and an output of a gyroscopic sensor 126. The controller 110 configured to determine the plausibility using the strength of wireless signal based on comparison of the measured strength of wireless signal between a first transceiver 132 of the mobile device 120 and a second transceiver 134 of the vehicle 100 with at least one threshold strength. The crash severity is determined to be low level if measured strength is found to be more than first threshold strength, medium level for strength less than the first threshold but greater than a second threshold and high level for strength lesser than the second threshold. Thus, based on the strength of the wireless connection signal, the crash severity is determined. The crash severity based on strength of the wireless signal is usable independently of other secondary parameters 118 and primary parameters 116, and just after the rollover status is detected to be true. Furthermore, the crash severity is determinable in combination with different level of vehicle speed detected in the threshold time duration, i.e., low level severity for vehicle speed less than a first pre-set speed, medium level severity for vehicle speed greater than first pre-set speed but less than a second pre-set speed, and high level severity for vehicle speed greater than the second pre-set speed. The crash severity is determinable using one or combination of two or more of the secondary parameters 118. [0019] The plausibility of the crash severity using the vehicle speed before detection of the crash event comprises, comparison of measured vehicle speed with a speed limit for a specific geolocation detected using a geolocation receiver 122. For example, if the maximum speed for a road segment inside the city is 50 kmph, and if the detected speed at the instant of crash was found to be 50-60 kmph, then the severity is determined to be low. If the crash speed is 60-70 kmph, then the severity is medium. Similarly, if the crash speed is more than 70 kmph, then the severity is determined to be high. The speed range is calibratable based on the speed limit of a specific geolocation or other factors and the above numeric example is for ease of understanding and the present invention is not limited by the same.

[0020] The plausibility using response to the crash notification comprises a response to a cancellable crash notification in the mobile device 120. The crash notification is timer based trigger alert which is displayed after detection of the crash event either through the rollover sensor 102 or the crash type determination or both. So when the rollover status is detected to be true, and if the driver is able to cancel the notification before the countdown timer reaches zero, then the crash severity is considered to be of low level, else the crash severity is detected to be a medium level or a high level when combined with the vehicle speed during “t-T” till time t.

[0021] The plausibility using vehicle speed using the mobile device 120 after detection of the crash event comprises comparison of vehicle speed measured using wheel speed sensor 108 and vehicle speed measured using the mobile device 120 such as using the geolocation receiver 122. For example, once the rollover status is detected to be true, then the vehicle speed measured using the wheel speed sensor 108 and the vehicle speed measured using the mobile device 120 are compared with each other. For the crash severity of low level, both the speeds are almost of the same value without significant change (increase or decrease) in the vehicle speed. For the crash severity of high level, there is huge difference between both the speed due to fact that the vehicle 100 might be skidding along with the driver or the vehicle 100 is stationary and the driver is thrown away with the mobile device 120. Similarly, for the crash severity of medium level, the difference in speed is at intermediate value. In addition, the vehicle speed reduces to zero very quickly or rear wheel and front wheel rotating at different speeds. Furthermore, difference between front and rear wheel speed is checked to identify if the crash occurred due to a wheelie condition or a normal driving condition, which again is usable to determine crash severity.

[0022] The plausibility of crash severity using accelerometer sensor 124 (single axis or multi-axis) comprises detecting a change in lateral acceleration from the reference value. The level of the change in lateral acceleration in specific axis indicates the crash severity from low level, medium level to high level. Similarly, the plausibility using gyroscopic sensor 126 (single axis or multi-axis) comprises detecting change in orientation of the mobile device 120 from a reference orientation to determine the crash severity from low level, medium level, and high level.

[0023] According to an embodiment of the present invention, plausibilizing the severity determined is possible by making use of in-built sensors available in the mobile device 120 (inertial sensors, geolocation receiver 122, proximity sensor 128) to check if the mobile device 120 is in the vicinity of the user and that the user has made a detectable movement after the crash. If the rider has not made any movement, then the severity could be classified as medium level or high level in combination with the vehicle speed at “t-T” onwards till “f ’ time.

[0024] In accordance to an embodiment of the present invention, the controller 110 is at least one of an Electronic Control Unit (ECU) of the vehicle 100 and the Mobile Control Unit (MCU) of the mobile device 120. In case of the mobile device 120, the MCU of the mobile device 120 is interfaced with the ECU of the vehicle 100 either through wireless or wired manner as known in the art, such as Universal Serial Bus (USB), type C cable, micro-USB cable, Bluetooth™, Wi-Fi, Near Field Communication (NFC), etc. In case of the vehicle 100, the ECU is at least one of an Engine Management System (EMS) unit, a Tire Pressure Monitoring System (TPMS) unit, a Telematics Control Unit (TCU), Anti-lock Braking System (ABS) unit, a Body Control Unit (BCU), a Human-Machine Interface (HMI) unit, other vehicular control units, and a combination thereof, is interfaced with the MCU of the mobile device 120. In an embodiment, the EMS ECU and ABS ECU are connected to sensors mentioned above and provides all the information related to primary parameters 116. Similarly, the mobile device 120 corresponds to electronic computing devices such as smartphone, tablets, wearable electronics such as smart watch, smart glasses, etc. The controller 110 is connectable to an external entity 130 such as a cloud or remote server comprising cloud computing architecture and having single or network of servers, databases connected with each other for processing of inputs and providing outputs. The external entity 130 is also possible to be nearby emergency responders informed through messages.

[0025] According to the present invention, a working of the controller 110 is described. Consider the vehicle 100 to be a motorcycle with rollover sensor 102 installed in the motorcycle. The user installs a mobile application in the smartphone and connects to the EMS ECU of the vehicle 100 over Bluetooth™. The user, such as driver, rider, or pillion rider, is provided with the smartphone as the mobile device 120 either mountable on the handlebar of the motorcycle or carried in a pocket of shirt or trouser of the driver or pillion rider or kept inside a bag, storage compartment of the vehicle. Both the smartphone and the EMS ECU are in sync or synchronized with time. The smartphone itself is connected with the external entity 130 which provides emergency services through known telecommunication networks, such as 3G, 4G, 5G, Global System for Mobile (GSM), Code Division Multiple Access (CDMA), etc. Assuming that the user is driving the motorcycle at 70 km/hr speed. The EMS ECU stores the data for the predetermined time in the memory element and/or continuously transmits the data to the smartphone over Bluetooth™. The data gets overwritten to manage the memory requirements such as after calibratable number of drive cycles/rasters where each drive cycle corresponds to engine start to engine shutdown. Once the rollover status is detected to be true, the EMS ECU monitors all the data from the in-vehicle sensors 104, 106, 108, 112, ..., 114 and checks the predetermined conditions for the t-T time onwards. Consider, rear crash is determined based on the analysis. The EMS ECU transmits the determined rear crash event/incident to the smartphone along with the all the data for in-vehicle parameters 116 from “t-T” period till “t” The controller 110 of the smartphone then plausibilizes the determination by monitoring the in-built sensors 122, 124, 126, ... 128 of the mobile device 120. The controller 110 analyzes secondary parameters 118 measured through the in-built sensors 122, 124, 126, ... 128 for the same time duration t-T onwards till t. Further, the controller 110 of the mobile device 120 displays a cancellable alert notification. If cancelled, the severity is determined to be low level. If the notification remains unattended, the crash severity is increased to medium level or high level based on the speed just before the crash, i.e. “t-T” time to “f ’ time. Finally, if it is confirmed that the rear crash has indeed occurred, the controller 110 also determines severity of the crash event and accordingly alerts the responders/emergency contacts through the external entity 130. The responders is the cloud or emergency contacts saved in the smartphone or nearby emergency service providers such as ambulances/hospitals.

[0026] In another example, consider the vehicle 100 is involved in the side crash. In this case once the rollover of the vehicle 100 is detected by the EMS ECU of the vehicle 100, the front crash, rear crash and skid are set as false as respective conditions are not fulfilled. However, the datasets of the primary parameters measured by the in-vehicle sensors 116 is transmitted to the MCU of the mobile device 120. The MCU processes the datasets and plauzibilizes the severity using the at least one secondary parameter 118 such as acceleration of a particular axis. Once confirmed, then the severity is determined based on value of the acceleration and accordingly the external entity 130 is informed. [0027] In accordance to an embodiment of the present invention, at first the crash type is determined followed by determination of crash severity. The primary parameters are used together with the secondary parameters for the determination of the crash information. The controller 101 detects crash by using the rollover sensor 102 information only and determines the crash severity sensor fusion mechanism involving the at least one in-vehicle sensors 104, 106, 108, 112, ... 114 and the at least one in-built sensor 122, 124, 126, . . . , 128 of the mobile device 120. All the relevant information from the ABS ECU such as vehicle speed, front and rear brake status, front and rear brake pressure and the front and rear wheel speed, and from EMS ECU such as engine speed, accelerator pedal status, clutch status, gear information, etc., and from MCU of the mobile device 120 such as accelerometer signal, gyroscopic signal, geolocation signal, a Bluetooth signal, etc., are captured for analysis and plausibilization for determination of the severity of the detected crash.

[0028] The crash severity of the vehicle 100 is determined based on conditions such as brake pressure is checked to identify the difference between emergency and normal braking, difference between front and rear wheel speed is checked to identify if the crash occurred due to a wheelie condition or a normal driving condition, sudden increase or decrease in vehicle acceleration profiles without change in driver demand such as accelerator pedal status, brake pedal status, clutch pedal status, etc., change of gear without powertrain being open, etc. The Bluetooth signal strength is also monitored to determine the severity of the crash. If the signal strength is low, then the mobile device 120 is far off from the vehicle 100 which leads to the understanding of that the user has fallen at a larger distance from the vehicle 100. Another way of plausibilizing the severity determined is again making use of sensors available in mobile device 120 (such as inertial sensors, gyroscope 126, proximity sensor 128, geolocation receiver 122) to check if the mobile device 120 is in the vicinity of the user and that the user has made a detectable movement after the crash. If the rider hasn’t made any movement, then the crash severity is classified as medium level or high level in combination with the vehicle speed found before the crash. On detection of crash, a timer-based notification is provided on the mobile application for the user to respond. If user doesn’t respond, an intimation (severity, location, proximity of mobile phone from the vehicle) is sent to external entity 130.

[0029] According to an embodiment of the present invention, the controller 110 to provide crash information of the vehicle 100 is provided. The controller 110 configured to detect the rollover status through the rollover sensor 102 and then determine and plauzibilize the crash information based on conditional evaluation of the at least one selected from the group comprising at least one of the primary parameters 116 and the at least one of the secondary parameters 118. The threshold time duration is applicable for primary parameters 116 and the secondary parameters 118. Moreover, time duration after “t” is also usable for analysing the primary parameters 116 and the secondary parameters 118 based on the need/requirement.

[0030] Fig. 2 illustrates a method for determining crash information of the vehicle, according to the present invention. The method comprises plurality of steps of which a step 202 comprises receiving input signals comprising primary parameters 116 measured by in-vehicle sensors 104, 106, 108, 112, ... , 114 of the vehicle 100. A step 204 comprises receiving input signals comprising secondary parameters 118 measured by in-built sensors 122, 124, 126, 128 of the mobile device 120. The method is characterized by a step 208 which comprises upon detection/sensing of rollover status from the rollover sensor 102 of the vehicle 100 as true, processing the primary parameters 116 and the secondary parameters 118 in the conditional manner and determining the crash information of the vehicle 100. The step 202 and step 204 are in sequence one after the other and possible to be interchanged with each other in the same sequence (shown in dotted boxes). Alternatively, the step 202 and the step 204 are performed in parallel (shown in solid line boxes), but processed only after the roll over status is detected to be true. The method is executed or performed by the controller 110. The controller 110 receives the inputs signals continuously but starts processing only after receiving the true status signal from the rollover sensor 102. If rollover status is not true, the step 202 and step 204 is continuously received for regular operations of the vehicle 100. Alternatively, the step 202 and the step 204 are performed only after the rollover status is true.

[0031] According to the method, the crash information is at least one of, the crash type and the crash severity. The crash type is determined to be any one selected from the group comprising the front crash, the rear crash, the side crash, and the skid, and the crash severity is determined to be any one selected from a group comprising low level, medium level, and high level.

[0032] According to the method, processing of said primary parameters 116 and said secondary parameters 118 in a conditional manner comprises processing at least one selected from the group comprising at least one of the primary parameters 116 and at least one of the secondary parameters 118 as per predefined set of conditions, namely, the first set of condition, the second set of condition, the third set of condition and the fourth set of condition, for determining respective crash type. The method comprises step 208 of determining the front crash based on first set of condition. As per the first set of condition, the method comprises real-time monitoring of the speed profile of the vehicle 100 and the acceleration profile of the vehicle 100 for the preset abnormal pattern. The speed profile and the acceleration profile are monitored after receiving an emergency braking status. The emergency braking status is determined based on a running status of the vehicle 100, the brake pedal status and the brake pressure measured by respective sensor. A step 210 comprises determining the rear crash based on second set of condition. As per the second set of conditions, the method comprises monitoring the speed profile of the vehicle 100 and the acceleration profile of the vehicle 100 upon detection of rollover status to be true. The speed profile of the vehicle 100 is monitored in dependence of the driver demand status. The driver demand status is based on vehicle running status, accelerator pedal signal, and clutch pedal status measured by respective sensor. A step 212 comprises determining the side crash based on the third set of condition. As per the third set of condition, the method comprises monitoring at least one of the secondary parameters 118 measured by the in-built sensors 122, 124, 126, 128 of the mobile device 120. A step 214 comprises determining the skid based on the fourth set of conditions. As per the fourth set of conditions, the method comprises monitoring detection of vehicle slip based on brake status and brake pressure from respective sensor. The predefined set of conditions are checked either in parallel or sequentially as per defined order.

[0033] According to the method, determining and plausibilizing the crash severity is based on at least one selected from the group comprising at least one of the primary parameters 116 and at least one of the secondary parameters 118. The at least one secondary parameters 118 comprises the strength of wireless connection signal between the mobile device 120 connected to the vehicle 100, the vehicle speed before detection of the crash event, the crash notification, the vehicle speed using the mobile device 120 after detection of the crash event, the output of accelerometer sensor 124 and the output of the gyroscopic sensor 126.

[0034] According to the method, the plausibility using strength of wireless signal comprises comparing the measured strength of wireless signal between the first transceiver 132 of the mobile device 120 and the second transceiver 134 of the vehicle 100 with at least one threshold strength. The plausibility using the vehicle speed before detection of the crash event comprises, comparing the measured vehicle speed with the speed limit for the geolocation using the geolocation receiver 122 of the satellite based positional system such as Navigation with Indian Constellation (NavIC) or Global Positioning System (GPS). The plausibility using the crash notification comprises receiving the response to the crash notification in the mobile device 120. The crash notification is timer based cancellable alert which is displayed after detection of the crash event. The plausibility based on vehicle speed 100 using the mobile device 120 after detection of the crash event comprises comparing the vehicle speed measured using wheel speed sensor 108 and the vehicle speed measured using the mobile device 120. The plausibility using accelerometer sensor 124 comprises detecting the change in acceleration from the reference value. The plausibility using gyroscopic sensor 126 comprises detecting change in orientation of the mobile device 120 from the reference orientation.

[0035] According to the present invention, the method is performed by at least one selected from the group comprising the Electronic Control Unit (ECU) of the vehicle 100 and the Mobile Control Unit (MCU) of the mobile device 120. Specifically, the controller 110 is the ECU of the vehicle 100 but in communication with the mobile device 120 through known wired or wireless means. Alternatively, the controller 110 is the MCU of the mobile device 120 but in communication with the control unit of the vehicle 100 through wired or wireless means. In yet another alternative, the controller 110 is the control units of the both the vehicle 100 and the mobile device 120 used together with shared processing capabilities.

[0036] According to the present invention, the controller 110 and method to detect the crash and classify crash severity is provided. The crash information aids the rider/driver with respect to the data. The controller 110 analyzes the driving maneuvers to determine the crash severity. The information to emergency contacts or external entity 130 based on the response from the rider to the notification sent through mobile application (alternate contact numbers, medical emergency). The location of the crash using geolocation receiver 122 for support emergency services. The crash location is detected multiple times by different vehicles 100, then geo tagging of accidental zones is done to alert the riders in advance. The crash information stored is usable for legal procedures (such police complaints, insurance claims, etc...,). The present invention provides a low cost solution using existing vehicle 100 and mobile device 120. The external entity 130 is possible to be other vehicle passing by the site of accident or buildings or infrastructure with necessary means for establishing and communicating through Vehicle to Vehicle (V2V) or Vehicle to Infrastructure (V2I) or Vehicle to Everything connectable (V2X) mode of communication. In accordance to an embodiment, the rollover status is determinable without using rollover sensor 102 but estimated using at least one of the in-vehicle sensors or at least one of the built-in sensors of the mobile device 120.

[0037] It should be understood that the embodiments explained in the description above are only illustrative and do not limit the scope of this invention. Many such embodiments and other modifications and changes in the embodiment explained in the description are envisaged. The scope of the invention is only limited by the scope of the claims.