WO2011016709A1

WO2011016709A1 - Monitoring, management and profiling system for driver and transport vehicle

Info

Publication number: WO2011016709A1
Application number: PCT/MY2010/000048
Authority: WO
Inventors: Di Bolhassan; Suhaili Bin Abang Hj Adris Abang
Original assignee: Di Bolhassan; Suhaili Bin Abang Hj Adris Abang
Priority date: 2009-08-07
Filing date: 2010-03-31
Publication date: 2011-02-10

Abstract

A method and system (100) for a real time monitoring, management and profiling for a driver/operator of a transport vehicle, with considerations to the real time situation and the environment, that can affect the performance of the driver/operator. The system is capable of acquiring, processing and interpreting data from existing data acquisition systems, on-board diagnostics systems, navigational components, ancillary sensors and regulatory databases to determine profiles of the driver/operator, for the purpose of assessing performance, safety and insurability. An identifier (110) is used for identifying the driver. Similar process of profiling for the transport vehicle is also included in the system. The profiling informations are made accessible to regulatory bodies and quasi government bodies (150) via information network system and information exchange system (145).

Description

MONITORING, MANAGEMENT AND PROFILING SYSTEM FOR DRIVER

AND TRANSPORT VEHICLE

FIELD OF INVENTION

The present invention relates to a real time monitoring, management and profiling system for a driver of a transport vehicle and for the transport vehicle itself, for the purposes of assessing aspects such as hire-ability, insurability, efficiency and safety. Such information are most helpful, particularly for insurance companies, regulatory bodies and quasi government bodies.

BACKGROUND OF THE INVENTION Available systems today already show demonstrable benefits in economy, efficiency, control and safety. However even the most recent systems employed, categorize the driving manoeuvres of the driver as events sometimes using time differentiated or statistical analysis. They typically do not take advantage of today^'s advances in communications and biometrics technologies. They also do not make use of today's availability of real-time information repositories such as integrated traffic systems (ITS) and geographical information systems (GIS). Nor do they account for the various modes of terrestrial transport vehicles today. As such these available systems are not able to accurately or convincingly identify the driver and conclusively link the findings of their modules to the driver. They can only do so with certainty for the vehicle being monitored which generally is a motor vehicle. They are also not able to consider the environmental conditions to determine if the style, manner, attitude of the driver at that point in time is in line with their operating environment (context) - eg. traffic is heavy, therefore driving below minimum speed limits on the outside lane of motorway is not dangerous as opposed to normal mode of operation. Similarly, the mode of transport is generally accepted to be a motor vehicle therefore no qualitative or quantitative information are available for driver of other transport vehicles such as motorcycles, mopeds, minivans, box vans, lorries, heavy good vehicles that are with and without containers - all of which have vastly different operating characteristics and make up more than half of the transport vehicles on today's roads. In the considerations for bire- ability, serviceability of the transport vehicle, operability and insurability, today's systems still rely primarily on paper based information garnered from interviews, application forms or manually entered sendee records. Where automated modules are employed, these rely on a downloading mechanism from local data storage. The accuracy of this information depends heavily on the honour of the driver providing the information as well as the timeliness of the download, as the driver may drive or operate the transport vehicle with diligence prior to their evaluation as local storage is generally quite limited and would only contain a specific amount of nearest past information due to the recycling of available storage. The environmental and geographical considerations are usually also historically based and any actuarial information are usually derived from statistics that are generally outdated.

Our online fleet management system (FMS) - atypical of most comprehensive and mature FMS available - captures vast amount of data and translates it into actionable information which can help improve an organization's competitive edge, such as by increasing profitability, by reducing costs and increasing customer loyalty through improved customer service and increased convenience. Our FMS is a technologically advanced asset and maintenance management software system, developed specifically to manage and track maintenance for fleets of cars, trucks, buses, and other transportation assets within medium scale and large organizations. Using this system, organizations can capture and analyze all costs associated with owning and operating a fleet of vehicles including equipment tracking, work order processing, preventive maintenance scheduling, parts and fuel inventory, and vehicle component warranty costs. Thus the productivity and safety of the fleet can be improved while lowering costs and extending the useful life of the vehicles. The FMS includes a system that monitors core values associated with driver behaviour and applies them to a 'pattern recognition' algorithm.

W⁷MlSt there are many profiling algorithms in the market, most are based on personality profiles where important factors such as environment and context are often not considered. These tests are also done in a controlled environment and not in the subject's everyday environment. SUMMARY OF THE INVENTION

An embodiment of the invention presents an algorithm-based real time monitoring, management and profiling system module for the driver/operator of a transport vehicle and of the transport vehicle itself. The algorithm may be implemented as an online module and/or in a programmed vehicle mounted on-board-cpu (OBC) unit. The algorithm is capable of processing real time driver/operator inputs including identifying the driver, the transport vehicle inputs, environment inputs, ancillary sensor inputs, situational inputs, geographical inputs, historical inputs, and inputs from department of motor vehicle or transport database. Additional inputs processed includes input information from the monitoring, collection, evaluation and processing of raw data from the FMS mobile tracking system, navigational data from the OBCs global positioning system (GPS) and also the transport vehicle's on-board diagnostics interface module (OBDI). The invention will determine as well as categorise the driver's or operator's skill, behaviour and risk independently of the traditional actuarial classifications derived from a driver's age, gender, experience. The particular transport vehicle's performance characteristics are also taken into consideration. This resulting analysis will be presented via a proprietary scale which will allow an insurer or a company to decide on the driver's insurability, hire-ability and suitability. Similar analysis and profiling is provided to assess the transport vehicle's efficiency and safety. Our mobile data communications server (MDCS), a middleware type application, is used in the system such that this information processed by the invention may be acquired from most devices and from any service provider. Thus the system is able to support even competing vehicular GPS tracking devices, although most likely with lesser functionality. The MDCS will accept all transmissions or raw data, from multiple service providers and process them into a unified set of variables which is fed into the system. Personal/mobile identification technology devices, eg. a biometric scanner, is used to identify the driver/operator for retrieving corresponding data for profiling and grading. It is to accurately and definitively identify a driver/operator of a transport vehicle, identifying said transport and attributing to same, an analysis for determining the profiles.

In an embodiment of the invention, the profiling information for the driver/operator and transport vehicle are made accessible to regulator}' bodies and quasi government bodies such as hiring companies and insurance companies, λ'ia information exchange sendees (IES) and information network services (INS).

Ln an embodiment of the invention, the system is used in conjunction with a FMS. The shortcoming of a FMS discussed in the foregoing section is eliminated or reduced by placing the data gathering, right in the subject's environment and capturing real world information.

The system includes modules for data acquisition, data processing (with core values assessment), and data interpretation for determination of real time driver profile, real time transport vehicle profile, along with presentation of grades. The data processing module includes determining the humanized variables. Core values assessment is conducted for the humanized variables for generating core values representing the driver or transport vehicle profile, in graded outputs.

The invented system further includes evaluation of driver/operator aid usage factors such as use of safety belts, signal lights, brake pressure etc. Traffic conditions affecting the real time situation such as traffic jam, are evaluated. Environmental factors affecting the real time situation such as weather systems - including raining - are also evaluated. The system also evaluates geo-related factors like location of the drive, location based traffic regulations, statistical information such as crime types/rate in the area, and the like. It also evaluates the particular transport vehicle's being driven characteristics or factors such as the type of transport vehicle, related performance and allowed manoeuvres.

Reports for both the driver/operator and the transport vehicle are generated. Proprietary cumulative grading may be generated. Proprietary trip analysis & reports may also be generated. The system incorporates a location centric approach with a location aware engine (LAE), such that any information attached to an object is considered to be based on its location.

Acquisition of information in real time is via global system for mobile (GSM) telecommunication data links such as 3 G, GPRS, and future formats. It may also be via GSM short messaging systems (SMS) or via satellite modems. In an embodiment, the data acquisition is via FMS via the OBC with built-in digital and analog sensors, built- in navigation module (GPS and CellLoc function), via controller-area-network (CAN- bus) and OBDI connections. External ancillary sensors such as for door lock, tyre pressure, accelerometers are included. Data from environmental information systems such as integrated traffic systems (ITS), weather information, regulatory information such as summons information, are also acquired. Geographical information such as road speeds, traffic profile, crime profile, etc are used.

Processing the acquired information follows the step of acquisition of information, and includes statistical analysis for determination of frequency of occurrences, for assessing driver's/operator's consistency and time-based differentiation analysis for determination of specific types of event - eg. over-speeding events, over-idling events, are evaluated. Analysis is made for categorising a driving manoeuvre into a humanly comprehensible format while retaining a metric representation for the system, to determine an empirical grade or profile. Interpretation of the processed information follows the step of processing the information. This interpretation step is to qualitatively and quantitatively determine the driver/operator profile, in terms of consistency, style such as whether their action is normal or aggressive or nervous etc. Accordingly, based on the driver/operator profile, risk for insurability is assessed. This step also qualitatively and quantitatively determines the transport vehicle profile to assess aspects like serviceability, maintenance, saleability or purchaseability and insurability.

The present invention consists of certain novel features and a combination of parts hereinafter fully described and illustrated in the accompanying drawings and particularly pointed out in the appended claims; it being understood that various changes in the details may be possible without departing from the scope of the invention or sacrificing any of the advantages of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

In the following drawings, same reference numbers generally refer to the same parts throughout. The drawings are not necessarily to scale, instead emphasis is placed upon illustrating the principles of the invention. The various embodiments and advantages of the present invention will be more fully understood when considered with respect to the following detailed description, appended claims and accompanying drawings wherein:

Fig.l illustrates a block diagram of functional overview of the system, describing the steps towards profiling, according to an embodiment of the invention.

Fig.2 illustrates a block diagram of the algorithm, describing the steps representing driver/operator identification and data acquisition, according to an embodiment of the invention.

Fig.3 illustrates a block diagram of the subsequent steps following those in Fig.2, representing data processing by comparison of new data acquired and analysed in Fig.2 with previous data interpretations and generation of the driver/operator profile report, according to an embodiment of this invention.

Fig.4 illustrates an exploded block diagram view of the process algorithm— PD I - within Fig.3 describing the steps representing the unique process of this invention for data processing and data interpretation of new additional (previously ignored by prior art) data to evaluate the driver/operator profile, according to an embodiment of the invention.

Fig.5 illustrates an exploded block diagram view of the process algorithm - PD II - within Fig.4, for the process of analysis and evaluation of the driver/operator derived from Fig.2 against data acquired in Fig.4 and derived norms, according to an embodiment of the invention. DETAILED DESCRIPTION OF THE INVENTION

The following description presents several preferred embodiments of the present invention in sufficient detail such that those skilled in the art can make and use the invention. Before describing in detail embodiments that are in accordance with the present invention, it should be noted that all of the figures are drawn for ease of explanation of the basic teachings of the present invention only. The extension of the figures with respect to the number, position, relationship and dimension of the parts of the preferred embodiment will be within the skill of the art after the following teachings of the present invention have been read and understood. Further, the exact dimensions and dimensional proportions to conform to specific force, weight, strength and similar requirements will likewise be within the skill of the art after the following teachings of the present invention have been read and understood.

Fig.l presents an overall architecture of the system (100) according to an embodiment of the invention. An OBC (105) in the transport vehicle is used for data access/input and data output, which interfaces with a personal/mobile identification device/sensor (eg. a biometric scanner) (110) and CAN-bus (115). The input information are collected as raw data (120) and passed along to the MDCS (125) resulting in the performance data derived via statistical and time differentiated analysis while driving the transport vehicle (130). The invention, a profiling engine (135), uses all the acquired information to generate profiles for the driver/operator and the transport vehicle. The profile information (140) are made accessible to regulatory and quasi government bodies (150) via information network systems and information exchange systems (145).

As shown in Fig.2, in an embodiment of the invention, when the system (100) is in operation, personal/mobile identification device/sensor identifier (215) is used to identify the driver/operator (220). Thereafter the relevant driver/operator file (225) is retrieved (230). The name 'operator' is being used when the profile for the transport vehicle is interpreted. Real time information is acquired (240), from sources such as the MDCS (235), ITS, IES/FNE, for analysis and pattern recognition (245). New data is compiled (250) and added to the particular driver/operator new data holding file (260) as shown in Fig.3. Subsequently the system retrieves (320) the driver/operator file information (315) as well as (330) the new data holding file (325). Both the sets of data, previous and new, are compared for assessing significant change (335). If there is no significant change, the system proceeds to derive the driver/operator profile (345) with the new analysis/information acquired followed by amending the driver profile (355) with this latest data and generating a report (350). In case a significant change is detected between the previous and the new data, the change is evaluated (340) followed by amending the driver profile (355) with the latest data and generating a report (350). The step - PD I - of deriving the driver/operator profile (345) includes multiple inputs and considerations as mentioned above that were heretofore ignored collectively by prior art, as shown in Fig.4 and forms the embodiment of the invention.

Fig.4 illustrates PD I - the system architecture for the profiling algorithm. On initiating the operation, the type of transport vehicle is first determined (410). According to the type of transport, a transport characteristic and pattern file (415) is uploaded (420) followed by loading external influencing factors like GIS database (425) from GIS file (430) and loading intelligent transport information system (ITIS) database (440) from ITIS (435) file. It is further followed by loading of environment information system (EIS) database (445) from EIS file (450). All the above is analysed with the new data collected (455) and thereafter the driver profile is derived (345).

Fig.5 illustrates PD II - the process flow chart for the analysis and evaluation step (455) of Fig.4. If the new collected data derived action or activity is not within the normal standards (510) as defined in the system (100) and against the information loaded (415,430,435,450), the system (100) evaluates if it is situational (520). If the situation does not account this deviation from norms, evaluation is conducted for poor skill (535) and if it is of dangerous level (545). Subsequently, the driver/operator profile (555) is derived from the above evaluations and log/alert records leading to the grading report (560). The log and alert modules (515,525,540,550) send notifying and alerting messages to the driver file (530) according to the status detected and also feed the information for deriving driver/operator profile (555) and the grading report (560). Similar algorithm for deriving transport vehicle profile is included. The invented system (100) is able to monitor a driver's real time input, reactions, decisions and correlates them with measured real world environment variables. Under measured input following are examples of real world environment variables measured. Precise variables:

- vehicle speed

- vehicle engine rpm

- gravitational forces

- road speed

- environment speed

- average speed

Humanized variables derived from several precise measured variables :

- perceived speed , eg. too fast, just right, too slow

- cornering speed

- braking style

- acceleration style

- idling behaviour

- security behaviour, such as those derived from monitoring engine on/off status, door locks status, status while fuelling, etc

As to further discussion of the manner of usage and operation of the present invention, the same should be apparent from the above description. Accordingly, no further discussion relating to the manner of usage and operation will be provided.

While the foregoing description presents preferred embodiments of the present invention along with many details set forth for purpose of illustration, it will be understood by those skilled in the art that many variations or modifications in details of design, construction and operation may be made without departing from the present invention as defined in the claims. The scope of the invention is as indicated by the appended claims and all changes that come within the meaning and range of equivalence of the claims are intended to be embraced therein.

Claims

1. A method of real time monitoring, management and profiling for a driver/operator of a transport vehicle and for the transport vehicle, via an on-line algorithm based system, the method comprising steps of:

acquiring the driver/operator identification by a identifier (215);

acquiring information from at least one fleet management system (FMS) via a mobile tracing system, at least one on-board diagnostics system in the transport vehicle and at least one ancillary sensor in the transport vehicle;

acquiring informations on real-time environment (240), weather (240), navigation (240), geography (240), history (240) and regulations (240);

processing the acquired information by statistical analysis (340) in case of a repeating user, to form a first dataset, the first dataset being for evaluating consistency;

processing the acquired information by time-based differentiation analysis (245) to form a second dataset, the second dataset being for determination of specific types of event; processing acquired information for evaluating the transport vehicle characteristics and allowed maneuvers to form a third dataset; and

interpreting the first, the second and the third datasets for categorizing a driving maneuver into a humanly comprehensible format while retaining a metric representation, and determining empirical grade (350) and profile (345) for the driver/operator and for the vehicle, the grade (350) and the profile (345) being for determination of skill, behavior and risk towards performance, insurability and safety.

2. The method according to claim 1, wherein the FMS is a typical on line fleet management system.

3. The method according to claim 1, wherein the real time informations are acquired via global system for mobile (GSM) telecommunication data links.

4. The method according to claim 1. wherein the real time informations are acquired via GSM short messaging systems.

5. The method according to claim 1, wherein the real time informations are acquired via satellite modems.

6. The method according to claim 1 , wherein the FMS information is acquired via built- in digital and analog sensors.

7. The method according to claim 1 , wherein the FMS information is acquired via built- in navigation module.

8. The method according to claim 1, wherein the FMS information is acquired using controller area network (CAN-bus) (115) and on-board diagnostics interface (OBDI) connections.

9. The method according to claim 1, wherein the FMS information is via external ancillary sensors.

10. The method according to claim 1, wherein the acquired informations include informations from global positioning system (GPS) via an on board computer (OBC) unit (105), through an OBDI in the transport vehicle.

1 1. The method according to claim 1, further comprising a step of:

generating a proprietary cumulative grading for the driver/operator and the transport vehicle.

12. The method according to claim 1. further comprising a step of:

generating a proprietary trip analysis and report.

13. The method according to claim 1 wherein the informations are acquired from any service provider via a mobile data communications server ( MDCS) (125).

14. The method according to claim 13, further comprising a step of:

accepting all transmitted raw data from a plurality of service providers; and processing the raw data into a unified set of variables, for interpretation.

15. The method according to claim 1, wherein the on-line algorithm is an algorithm that is programmed in OBC unit (105).

16. The method according to claim 1, further comprising a step of providing the profile and grade to quasi government bodies and regulatory bodies (150) via information exchange system and information network system (145).

17. An on-line algorithm based system (100) for real time monitoring, management and profiling for a driver/operator of a transport vehicle and for the transport vehicle, the system comprising:

an identifier (215) for identifying the driver/operator;

a first sub-module for acquiring information from at least one existing FMS via mobile tracing system, at least one on-board diagnostics system in the transport vehicle and at least one ancillary sensor in the transport vehicle;

a second sub-module for acquiring real-time informations on environment (240), weather (240), navigation (240). geography, history (240) and regulations information (240);

a third sub-module for processing the acquired information by statistical analysis (245) in case of a repeating user, to form a first dataset the first dataset being for evaluating consistency;

a fourth sub-module for processing the acquired information by time-based differentiation analysis (245) to form a second dataset. the second dataset being for determination of specific types of event;

a fifth sub-module for processing acquired information for evaluating the transport vehicle characteristics and allowed maneuvers to form a third dataset; and

a sixth sub-module for interpreting the first, the second and the third datasets for categorizing a driving maneuver into a humanly comprehensible format while retaining a metric representation, and determining empirical grade (350) and profile (345) for the driver/operator and for the vehicle, the grade (350) and the profile (345) being for determination of skill, behavior and risk towards performance, insurability and safety.

18. The system (100) according to claim 17, wherein the FMS is a typical on line fleet management system.

19. The system (100) according to claim 17, wherein the real time informations are acquired via GSM telecommunication data links.

20. The system (100) according to claim 17, wherein the real time informations are acquired via GSM short messaging systems.

21. The system (100) according to claim 17, wherein the real time informations are acquired via satellite modems.

22. The system (100) according to claim 17, wherein the FMS information is acquired via built-in digital and analog sensors.

23. The system (100) according to claim 17, wherein the FMS information is acquired via built-in navigation module.

24. The system (100) according to claim 17, wherein the FMS information is acquired using CAN-bus (115) and OBDI connections.

25. The system (100) according to claim 17, wherein the FMS information is via external ancillary sensors.

26. The system (100) according to claim 17, wherein the acquired informations include informations from GPS via an OBC unit (105), through an OBDI in the transport vehicle.

27. The system (100) according to claim 17, wherein the algorithm further generates a proprietary cumulative grading for the driver/operator and the transport vehicle.

28. The system (100) according to claim 17, wherein the algorithm further generates a proprietary trip analysis and report.

29. The system (100) according to claim 17, further comprising an MDCS (125) for acquiring information from any service provider.

30. The system (100) according to claim 29, wherein the MDCS (125) accepts transmitted raw data from a plurality of service providers and processes the raw data into a unified set of variables, for interpretation.

31. The system (100) according to claim 17, wherein the on-line algorithm is an algorithm that is programmed in OBC unit (105).

32. The system (100) according to claim 17. further comprising a provision for making the profile and grade accessible to quasi government bodies and regulator}' bodies (150) via information exchange system and information network system (145).