WO2015174824A2

WO2015174824A2 - A system and method for extracting route and traffic density

Info

Publication number: WO2015174824A2
Application number: PCT/MY2015/050031
Authority: WO
Inventors: Raja Mohamad Fairuz R. MOHAMAD YUSOFF; Norazah ABD AZIZ
Original assignee: Mimos Berhad
Priority date: 2014-05-15
Filing date: 2015-05-07
Publication date: 2015-11-19
Also published as: WO2015174824A3; MY188014A

Abstract

A system (10) and method (20) for extracting route and traffic density employ analysis of Geographical Information (GI) to define route and traffic density. The present invention comprising a geolocation recorder module (101) adapted to gather traffic information from at least one source; an analysis module (110) adapted to receive the traffic information and process the information to provide route density information; a display module (106) adapted to display the route density information; and a decision maker module (107) to facilitate route planning. The analysis module preferably comprises a map extractor module, a route ETL module, a route frequency module, a route colour conversion module and at least one relational database. The approach of the present invention involves producing valuable density and quality Geographical Information (GI) data to simulate route planning by extracting route and traffic density, for example for urban safety research and planning.

Description

A SYSTEM AND METHOD FOR EXTRACTING ROUTE AND TRAFFIC DENSITY

FIELD OF INVENTION

The present invention relates to a system and method for extracting route and traffic density. In particular, the invention relates to systems and methods that employ analysis of Geographical Information (Gl) to define route and traffic density. BACKGROUND ART

The selection of an appropriate technique to produce valuable density is an important consideration when working with Gl and urban safety, including route planning. For example, in the case of determining route planning for a patrol car, although the invention is not so limited, routes have been conventionally planned by looking at crime indexes using classical frequency based density methods. However, the classical frequency based methodology can be defined as an open set, which might fall within range [0,∞). Furthermore, classical frequency based analyses focus on individual roads (one road specifically), but do not cover all roads for a specific or defined area. It is therefore statistically difficult to distribute between places with high crime index and lower crime index since it is possible that the level of crime is not static to a particular road.

United States Patent Publication No. 2010/008227 describes a method for displaying traffic density information. The method disclosed comprises providing historical traffic density information, determining for which moment in time the traffic density information should be displayed, determining the traffic density information for that moment in time, and displaying the traffic density information for the moment on a display. United States Patent Publication No. 201 1/0298637 describes an electronic device configured to operate as a traffic information client. The traffic information client device comprises an interface adapted to receive traffic information messages, where a traffic information message comprises a location code which identifies a location of a traffic event. The traffic information client device further comprises a memory and a relational database stored in the memory, the relational database comprising at least a first set of relations including at least one relation which directly or indirectly associates location codes with location information.

X. Li et al, "Traffic Density-Based Discovery of Hot Routes in Road Networks", University of Illinois at Urbana-Champaign, Urbana, IL 61801 , USA (pgs 441 -449), proposes a density-based algorithm that, instead of clustering moving objects, clusters road segments based on the density of common traffic they share. The system is said to be both efficient and effective at discovering hot routes.

The object of the present invention is to provide a system and related methods for extracting route and traffic density, for example for urban safety research and planning. The solution involves producing valuable density and quality Geographical Information (Gl) data to simulate route planning.

The subject matter claimed herein is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one exemplary technology area where some embodiments described herein may be practice.

SUMMARY OF INVENTION

The present invention relates to a system and method for extracting route and traffic density. In particular, the invention relates to systems and methods that employ analysis of Geographical Information (Gl) to define route and traffic density.

One aspect of the present invention provides a system for extracting route and traffic density comprising a geolocation recorder module adapted to gather traffic information from at least one Automated Vehicle Locator; an analysis module adapted to receive said traffic information and process said information to provide route density information; a display module adapted to display said route density information; and a decision maker module to facilitate route planning. The geolocation recorder module (1 01 ) adapted to gather traffic information from at least one Automated Vehicle Locator; said traffic information is gathered by utilization of; dimension reduction technique (feature vector) ; more than one set relation to identifying the density road information based on the category of traffic information; and traffic information properties with specific road information namely; vehicle, date and time; and region wherein the system further discloses the ability of providing the required traffic information based on the time selection of client or user.

In another aspect the invention provides a system wherein said analysis module comprises a map extractor module, a route ETL module, a route frequency module, a route colour conversion module and at least one relational database. In a further aspect the invention provides a system comprising a traffic information database adapted to receive processed information from said geolocation recorder module, a geospatial database adapted to received processed information from said map extractor module, a Transposed database adapted to receive output from said route ETL module, a frequency database adapted to receive route frequency calculation output from said route frequency module and a route statistic database adapted to receive final processed data from said route frequency module and communicate said final processed data to said route colour conversion module. In yet another aspect the invention provides a method for extracting route and traffic density comprising recording traffic information gathered from at least one source with a geolocation recorder module; processing said traffic information in an analysis module to obtain route density information; generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database (204); displaying said route density information on a display module; and simulating route planning with a decision maker module.

In yet another aspect the invention provides a method for processing traffic information in an analysis module to obtain route density information further comprising steps of extracting a map with a map extraction module and saving processed information from said map extractor module into a geospatial database; reading and extracting geolocation information from said traffic information database with a route ETL module and storing output of the route ETL module in a transposed database; calculating route frequency from information received from the transposed database in a route frequency calculation module; and saving route frequency information in a frequency database.

In still another aspect the invention provides a method wherein the step of recording traffic information gathered from at least one source with a geolocation recorder module further comprises initiating said geolocation recorder module during system start up, and establishing a connection to said analysis module using a secure connection, which may or may not include performing authentication; storing said geolocation information in local machine memory if said connection is not established with said analysis module; extracting current location of geographic information and sending the extracted geographic information to said analysis module once successful connection to said analysis module is achieved.

In another aspect the invention provides a method wherein extraction of the map with said map extraction module comprises defining regions of interest (ROIs) for roads within a defined area; marking longitude and latitude for every intersection, road end and turn within the defined area with an unique identifier ( t_a, t , t_{c ...} ); computing a linear equation given two connected intersections or road ends or turns or any combination thereof; saving equation values as paired list A = { (t_a,t ), (t_b,t_c),(t_b,t_d), (t_c, t_e) } where a is the starting point, t_b is an intersection, t_c and t_e are on the same road, and t_d is an end point; determining whether all pairs have been evaluated and if some of elements in the paired list A have not been processed, pairing two locations to obtain a linear relationship in terms of slope and y-intercept values, indicating the values as a new identity (t'_a , t' _c, t'_{ac ...}), saving and the values into a new paired list A'; and saving or writing the paired values into said geospatial database if all pairs have been evaluated.

In a further aspect the invention provides a method wherein reading and extracting geolocation information from said traffic information database with said route ETL module comprises extracting geolocation information for a vehicle, including date/time or region from said traffic database; sorting the information by time; searching the nearest on-road location of the sorted information along with other properties thereof and storing into a new list; repeating this process until all original traffic information has been processed; and saving the transformed information into the transposed database.

In another aspect the invention provides a method wherein calculating route frequency from information received from the transpose database in a route frequency calculation module comprises reading and extracting transformed geolocation information for a specific vehicle, date/time or region from the transposed database as list C; determining the nearest on-road location of the sorted information along with other properties and storing data information into new list C; reading and extracting road ID information from the geospatial database; checking if the data information of list C is similar to the road ID information; if the data information of list C is not similar to the road ID information, creating new frequency data of the road information along with its properties and saving the data into the frequency database; if the data information of list C is similar to the road ID information, checking if the geolocation in list C is located on the same road or not; if the geolocation is not in the same road, saving the information as frequency data into the frequency database; and repeating the process until all of the information in the transposed database has been processed.

In still another aspect the invention provides a method wherein generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database comprises reading and extracting frequency information of a specific vehicle, date/time or region from the frequency database; sorting the data in matrix order, in which columns denote roads and properties such as vehicle, date/time or region are sorted into rows; using dimension reduction techniques to obtain percentages for each column; and saving the computational output along with the existing properties information into the route statistic database.

In another aspect the invention provides a method wherein generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database further comprises reading and extracting route statistic information generated; defining a range of colours to be encoded at least using colour space as RGB or CMYK components; computing a linear equation for all colour space components; creating a one-to-many mapping which transforms the route statistic information into colour space components; and updating the route statistic information with the colour encoded equations.

In another aspect the invention provides a method wherein displaying route density information on a display module further comprises obtaining route statistic information including the road ID information, list D; encoding the route statistic information using said encoder equations; reading and extracting the road information of the road ID information, list D', from the geospatial database; creating new values as a new layer based on all information of lists D and D'; drawing the layer using the encoded equations; and displaying the layer, at least overlaying it with a predefined map. The present invention consists of features and a combination of parts hereinafter fully described and illustrated in the accompanying drawings, it being understood that various changes in the details may be made without departing from the scope of the invention or sacrificing any of the advantages of the present invention. BRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS

To further clarify various aspects of some embodiments of the present invention, a more particular description of the invention will be rendered by references to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail through the accompanying drawings in which: FIG. 1 illustrates the system for extracting route and traffic density of an embodiment of the invention, showing interaction over a network.

FIG. 2 illustrates a flow diagram of the method for extracting route and traffic density of an embodiment of the invention.

FIG. 3 illustrates a flow diagram of the step of recording vehicle geolocation. FIG. 4 illustrates a flow diagram of the step of extracting a map. FIG. 5 illustrates a flow diagram of the step of routing Extract, Transform, Load (ETL). FIG. 6 illustrates a flow diagram of the step of calculating route frequency. FIG. 7 illustrates a flow diagram of the step of obtaining road information.

FIG. 8 illustrates a flow diagram of the step of obtaining road information (cont.). FIG. 9 illustrates a flow diagram of the step of displaying information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention provides a system and method for extracting route and traffic density. In particular, the invention relates to systems and methods that employ analysis of Geographical Information (Gl) to define route and traffic density.

Hereinafter, this specification will describe the present invention according to the preferred embodiments. It is to be understood that limiting the description to the preferred embodiments of the invention is merely to facilitate discussion of the present invention and it is envisioned without departing from the scope of the appended claims.

Figure 1 illustrates an exemplary overview of a system 10 to extract route and traffic density showing its interaction over a network 100. The system 10 includes a geolocation recorder module 101 adapted to gather traffic information from a source. For example, the source may include Automated Vehicle Locator Systems (AVLS). Satellites receive requests for geolocation information from vehicles and then send the geolocation information to the vehicles making the requests via radio or wireless communication. Thereafter, the information is then resent via radio or wireless communication, from the in-vehicle system to an analysis server 1 10 to process the information. The analysis server 1 10 includes a map extractor 102, route ETL module 103, analysis components 104 and related databases 105 to analyse traffic data comprising the geolocation information. The analysed information is transmitted to a client computer via wireless communication or by any other means of secure communication. The client computer displays the results 106 as a layer on the map. In certain embodiments, a decision maker module (i.e. decision support system) 107 is provided at the client to facilitate, for example, route planning management. The geolocation recorder module (101 ) is adapted to gather traffic information from the Automated Vehicle Locator; traffic information is gathered by utilization of; dimension reduction technique (feature vector); more than one set of relation to identify the density road information based on the category of traffic information; and traffic information properties with specific road information namely; vehicle, date and time; and region wherein the system further discloses the ability of providing the required traffic information based on the time selection of client or user. Figure 2 illustrates a flow chart of a method for extracting route and traffic density 20 according to an embodiment of the invention. The method 20 includes recording geolocation of a vehicle 200 with geolocation recorder module embed in an in-vehicle system or other device, or through an application that receives such traffic information. Recording of traffic information gathered from a source with a geolocation recorder module (200) further comprising gathering traffic information by utilization of; dimension reduction technique (feature vector); more than one set relation to identifying the density road information based on the category of traffic information; and traffic information properties with specific road information namely; vehicle, date and time; and region wherein the method further discloses the ability of providing the required traffic information based on the time selection of client or user.

The geolocation information obtained is stored in a Traffic Information database 206. At an analysis server, a map is extracted 201 with a map extraction module and the processed information saved into a Geospatial database 207. A route ETL module reads and extracts information 202 from the Traffic Information database. The output of the route ETL module is stored in a Transposed database 208. The information from the Transposed database is used to calculate route frequency 203 in a route frequency calculation module. This information is then saved in a Frequency database 209. Calculation of route frequency 203 in the route frequency calculation module repeats until all of the data in the Transposed database and the Frequency database has been processed. The final processed data from the route frequency calculation module is saved in a Route Statistic database 210. Processed data saved to the Route Statistic database is used to generate route colour conversion 204, through a route colour conversion module in an analysis server or a client machine. The results are then displayed 205 using a display module in a client environment.

Figure 3 illustrates in more detail the step of recording geolocation information 200 with a geolocation module, as previously illustrated in Figure 2 and described above. The module is initiated during system startup 300 and a connection to the server is established 301 using a secure connection, which may or may not include performing authentication. Success of connection is determined 302. If the connection is not established with the analysis center, the module stores the geolocation information in local machine memory 303. Once successful connection is achieved, current location of the geographic information is extracted 304 using standard GPS and GLONASS locking mechanisms. Thereafter, it is determined if connection is established and geo-location, time captured and vehicle ID is sent for each predefined intervals of 5 seconds. . Upon confirmation that a connection is established, the module continues through a client - server environment; the web service 306. Otherwise, if connection is not established, the module enters a sleep mode process 307. The client server environment 306 includes any application of a client-server environment at the analysis server, such as a web service. If the module is not in exit mode or does not shutdown during sleep mode, the step of extracting geographical information 304 is repeated, otherwise the shutdown procedure is the final step for a module which enters into the sleep mode. The geographic information sent through in step 305 and 306 is also stored in the Traffic database 206. Extraction of the map 201 with a map extraction module is illustrated in more detail in Figure 4. The process involves defining Regions of Interests (ROIs) 400 for roads within a defined area. A check is then conducted 401 to determine whether all roads within the defined area have been processed completely or not. If data to be processed still exists, longitude and latitude for every intersection, road end and turn within the defined area are marked with an unique identifier (t_a, t_b, t_{c ...} ) 402. The process then involves computing a linear equation given two connected intersections or road ends or turns or any combination thereof 403. The equation values are saved as paired list A ( A = { (ta.t_b). (t_b,tc),(t ,t_d), (t_c, t_e) } where A is the starting point, t is an intersection, t_c and t_e are on the same road, and t_d is an end point). A determination is then made as to whether all pairs have been evaluated 404. If some of elements in the paired list ( A) have not been processed, two locations are paired to obtain a linear relationship in terms of slope and y-intercept values 405. The values are then indicated as a new identity (t'_ab, t'_bc, t'_{ac ...}) and the values saved or written into new paired list (Α') 406. The procedure is repeated until all of the pairs have been processed. Then, the paired values (Α') are saved 407 into the Geospatial Relational database 207.

A flow diagram of routing the ETL module 202 is illustrated in more detail in Figure 5. Initially, geolocation information for a vehicle, such as date/time or region, is extracted 500 from the Traffic database 206. The information is then sorted by time 501 (. list B) and the transformed information updated as a new empty list 502 (list B'). Each element in the original traffic information (list B) is extracted 503 and processed 504. Processing 504 comprises searching the nearest on-road location of the sorted information along with other properties thereof based on the element of step 503 and storing this into the new list (list B'). Steps 503 to 504 are repeated until all original traffic information has been processed. The transformed information (list B') is then saved 505 into the Transposed database 208. Calculation of route frequency 203 in the route frequency calculation module is illustrated in more detail in Figure 6. Initially, the transformed geolocation information for a specific vehicle, date/time or region is extracted 600 from the Transposed database 208. A determination is then made as to whether all of the geolocation information has been processed 601 . If not, it will be saved as a temporary list 602. Then, the nearest on-road location of the sorted information along with other properties is determined and stored into new list C 603. Road ID information (ID R 1 ) is then read and extracted 604 from the geospatial database 207. The process then involves checking if the data information (list C) already exist in the road ID information (ID R 1 ) 605. If not, the process involves creating new frequency data of the road information along with its properties and saving the data 606 into the Frequency database 209. Otherwise, the process involves checking if the geolocation (list C) is located on the same road (ID R 1 ) or not 607. If the geolocation is not in the same road, the information is saved as frequency data 608 into the Frequency database 207. The process is then repeated 609 until all of the information in the Transposed database have been processed.

Figure 7 illustrates a flow diagram of obtaining road information, which includes part of route colour conversion 204 through the route colour conversion module. The process initially includes reading and extracting frequency information of a specific vehicle, date/time or region 700 from the Frequency database 209. The data is then sorted in matrix order, in which columns denote roads and properties such as vehicle, date/time or region sorted into rows 701 . Dimension reduction techniques are used to obtain percentages for each road (column) 702, followed by saving the computational output along with the existing properties information 703 into the Route Statistic database 210. Figure 8 illustrates a flow diagram for obtaining road information, another part of the route colour conversion 204. The process involves reading and extracting route statistic information 800 generated by the process flow of Figure 7. A range of colours to be encoded is then defined 801 , at least using colour space as RGB (Red, Green, Blue) or CMYK (Cyan, Magenta, Yellow and Key (Black)) components. The process then includes computing a linear equation for all colour space components 802. After that, a one-to-many mapping is created which transforms the route statistic information into colour space components 803, followed by saving the route statistic information with the colour encoded equations 804.

Figure 9 illustrates displaying of results 205 using a display module in a client environment. This involves obtaining route statistic information including the road ID information (list D) 900 from the process flow illustrated in Figure 8. The route statistic information is then encoded 901 using the encoder equation generated in Figure 8. The process then involves reading and extracting the road information of the road ID information (list D') 902 from the Geospatial database 207. New values are then created as a new layer 903 based on all of this information (lists D and D'), followed by drawing the layer using the encoded equation 904. Finally, the layer is displayed, at least overlaying it with a predefined map 905.

Unless the context requires otherwise or specifically stated to the contrary, integers, steps or elements of the invention recited herein as singular integers, steps or elements clearly encompass both singular and plural forms of the recited integers, steps or elements.

Throughout this specification, unless the context requires otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated step or element or integer or group of steps or elements or integers, but not the exclusion of any other step or element or integer or group of steps, elements or integers. Thus, in the context of this specification, the term "comprising" is used in an inclusive sense and thus should be understood as meaning "including principally, but not necessarily solely". It will be appreciated that the foregoing description has been given by way of illustrative example of the invention and that all such modifications and variations thereto as would be apparent to persons of skill in the art are deemed to fall within the broad scope and ambit of the invention as herein set forth.

Claims

A system (10) for extracting route and traffic density comprising:

a geolocation recorder module (101 ) adapted to gather traffic information from at least one Automated Vehicle Locator;

an analysis module (1 10) adapted to receive said traffic information and process said information to provide route density information;

a display module (106) adapted to display said route density information; and

a decision maker module (107) to facilitate route planning,

characterized in that

the geolocation recorder module (101 ) adapted to gather traffic information from at least one Automated Vehicle Locator; said traffic information is gathered by utilization of; dimension reduction technique (feature vector); more than one set relation to identifying the density road information based on the category of traffic information; and traffic information properties with specific road information namely; a) vehicle, b) date and time; and c) region wherein the system further discloses the ability of providing the required traffic information based on the time selection of client or user.

A system (10) as claimed in claim 1 , wherein said analysis module (1 10) further comprising the following modules to receive said traffic information and process said information to provide route density information:

a map extractor module (102);

a route ETL module (103);

a route frequency module,

a route colour conversion module; and

at least one relational database (105).

A system (20) according to claim 2, further comprising a traffic information database (206) adapted to receive processed information from said geolocation recorder module (101 ), a geospatial database (207) adapted to received processed information from said map extractor module (102), a Transposed database (208) adapted to receive output from said route ETL module (103), a frequency database adapted to receive route frequency calculation output from said route frequency module and a route statistic database adapted to receive final processed data from said route frequency module and communicate said final processed data to said route colour conversion module.

A method (20) for extracting route and traffic density comprising:

recording traffic information gathered from at least one source with a geolocation recorder module (200);

processing said traffic information in an analysis module to obtain route density information (201 , 202, 203);

generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database (204);

displaying said route density information on a display module (205); and simulating route planning with a decision maker module,

characterized in that

recording traffic information gathered from at least one source with a geolocation recorder module (200) further comprising:

gathering traffic information by utilization of; dimension reduction technique (feature vector); more than one set relation to identifying the density road information based on the category of traffic information; and traffic information properties with specific road information namely; a) vehicle, b) date and time; and c) region wherein the method further discloses the ability of providing the required traffic information based on the time selection of client or user.

A method as claimed in claim 4, wherein processing said traffic information in an analysis module to obtain route density information (201 , 202, 203) further comprising steps of: extracting a map with a map extraction module 201 , saving processed information from said map extractor module into a geospatial database (207);.

reading and extracting geolocation information from said traffic information database with a route ETL module, and storing output of the route ETL module in a transposed database (202); calculating route frequency from information received from the transposed database in a route frequency calculation module; and (203)

saving route frequency information in a frequency database (209).

A method as claimed in claim 4, wherein recording traffic information gathered from at least one source with a geolocation recorder module further comprises steps of:

initiating said geolocation recorder module during system start up (300); establishing a connection (301 ) to said analysis module using a secure connection, which may or may not include performing authentication; storing said geolocation information in local machine memory if said connection is not established with said analysis module (303);

extracting current location of geographic information (304) and sending the extracted geographic information to said analysis module (305) once successful connection to said analysis module is achieved.

A method as claimed in claim 5, wherein extracting a map with a map extraction module further comprises:

defining regions of interest (ROIs) for roads within a defined area (400); marking longitude and latitude for every intersection, road end and turn within the defined area with an unique identifier ( t_a, t , t_{c ...} ) (402);

computing a linear equation given two connected intersections or road ends or turns or any combination thereof (403);

saving equation values as paired list A = { (t_a,t ), (t_b,t_c),(t_b,t_d), (t_c, t_e) } where A is the starting point, t is an intersection, t_c and t_e are on the same road, and t_d is an end point (403); determining whether all pairs have been evaluated (404) and, if some of elements in the paired list A have not been processed, pairing two locations to obtain a linear relationship in terms of slope and y-intercept values (405), indicating the values as a new identity (t'_a , t' _c, t'_ac ...), saving and the values into a new paired list A' (406); and

saving or writing the paired values into said geospatial database if all pairs have been evaluated (407).

A method as claimed in claim 5, wherein reading and extracting geolocation information from said traffic information database with said route ETL module comprises:

extracting geolocation information for a vehicle, including date/time or region from said traffic database (500);

sorting the information by time (501 );

searching the nearest on-road location of the sorted information along with other properties thereof and storing into a new list (502);

repeating this process until all original traffic information has been processed (504); and

saving the transformed information into the transposed database (505).

A method as claimed in claim 5, wherein calculating route frequency from information received from the transpose database in a route frequency calculation module further comprises:

reading and extracting transformed geolocation information for a specific vehicle, date/time or region from the transposed database as list C (600); determining the nearest on-road location of the sorted information along with other properties and storing data information into new list C (603); reading and extracting road ID information from the geospatial database (604);

checking if the data information of list C is similar to the road ID information (605); if the data information of list C is not similar to the road ID information, creating new frequency data of the road information along with its properties and saving the data into the frequency database (606);

if the data information of list C is similar to the road ID information, checking if the geolocation in list C is located on the same road or not

(607);

saving the information as frequency data into the frequency database if the geolocation is not in the same road (608); and

repeating the process until all of the information in the transposed database has been processed.

10. A method as claimed in claim 4, wherein generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database (204) comprises:

reading and extracting frequency information of a specific vehicle, date/time or region from the frequency database (700);

sorting the data in matrix order, in which columns denote roads and properties such as vehicle, date/time or region are sorted into rows (701 ); using dimension reduction techniques to obtain percentages for each column (702); and

saving the computational output along with the existing properties information into the route statistic database (703).

1 1 . A method of claim 1 1 , wherein generating route colour conversion through a route colour conversion module in an analysis server or a client machine using processed data saved to the route statistic database (204) further comprises: reading and extracting route statistic information generated (800);

defining a range of colours to be encoded at least using colour space as RGB or CMYK components (801 );

computing a linear equation for all colour space components (802);

creating a one-to-many mapping which transforms the route statistic information into colour space components (803); and updating the route statistic information with the colour encoded equations (804).

12. A method as claimed in claim 4, wherein displaying said route density information on a display module further comprises steps of:

obtaining route statistic information including the road ID information, list D (900);

encoding the route statistic information using said encoder equations (901 );

reading and extracting the road information of the road ID information, list D', from the geospatial database (902);

creating new values as a new layer based on all information of lists D and D' (903);

drawing the layer using the encoded equations (904) ; and displaying the layer, at least overlaying it with a predefined map (905).