WO2010045539A2

WO2010045539A2 - Street quality supervision using gps and accelerometer

Info

Publication number: WO2010045539A2
Application number: PCT/US2009/060980
Authority: WO
Inventors: Richard Freitag
Original assignee: Siemens Corporation
Priority date: 2008-10-17
Filing date: 2009-10-16
Publication date: 2010-04-22
Also published as: WO2010045539A3

Abstract

Methods and systems are described that use condition assessing mobile clients that combine location and accelerometer data to create a detailed quality map of transportation infrastructure. Full resolution tracking or an event based database allows for the application of various data analyses.

Description

STREET QUALITY SUPERVISION USING GPS AND ACCELEROMETER

CROSS REFERENCE TO RELATED APPLICATIONS

[oooi] This application claims the benefit of U.S. Provisional Application No. 61/106,206, filed on October 17, 2008, the disclosure which is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

[0002] The invention relates generally to monitoring the condition of transportation infrastructure. More specifically, the invention relates to systems and methods that monitor transportation infrastructure while in-use without relying on embedded static sensors.

[0003] Transportation is the movement of people and goods from one location to another. Transport is performed by various modes, such as air, rail, road, water, cable, pipeline and space. Transportation may be divided into infrastructure, vehicles and operations. Infrastructure comprises the fixed installations necessary for transport, such as roadways, railways, airways, waterways, canals and pipelines, and terminals. Vehicles traveling on these networks include automobiles, bicycles, buses, trains, trucks, people and aircraft. Operations deal with the way the vehicles are operated and the procedures set for this purpose including financing, legalities and policies. In the transport industry, operations and ownership of infrastructure can be either public or private, depending on the country and mode,

[0004] Today roadways are principally asphalt or concrete. Modern pavements are designed for heavier vehicle loads and faster speeds. Water will undermine a pavement over time, so much of pavement and pavement joint design are meant to minimize the amount of water getting and staying under the slabs.

[0005] Track comprises two parallel steel rails, anchored to members called ties of timber, concrete, steel, or plastic to maintain a consistent distance apart. The track guides the flanged wheels, keeping the cars on the track without active steering. Spikes in wooden ties can loosen over time, but split and rotten ties may be individually replaced with new wooden ties or concrete substitutes. Concrete ties can also develop cracks or splits, and can also be replaced individually. Should the rails settle due to soil subsidence, they can be lifted and additional ballast tamped under the ties to level the rails .

[0006] With ongoing and increased demand, transportation infrastructure requires increased supervision to ensure reliability and safety. Considering the magnitude of today's transportation infrastructure, it is unfeasible to integrate sensors as part of the roadway or track to monitor their condition. In many cases, when the extent of repair becomes great, the roadway or track becomes unavailable .

[0007] Constant use as well as environment and weather damages transportation infrastructure which requires regular maintenance. For example, potholes appearing on roadway surfaces must be fixed not only because they cause damage to automobiles, but can be a safety risk and a cause of accidents.

[0008] Non-permanent obstacles that influence the flow of transportation may occur due to accidents, debris, rocks, animals, trees, etc. Non-permanent obstacles such as a car parked on a roadway shoulder or a distracting billboard are not situated on the transportation infrastructure, but are situated close to the infrastructure and may influence the regular flow of transportation .

[0009] To monitor the condition of transportation infrastructure, recent research proposes structural deformation monitoring using the Global Positioning System (GPS) in conjunction with accelerometers . However, these solutions propose installing static sensors at specific locations within the physical infrastructure.

[ooio] What is needed is a system and method that monitor transportation infrastructure while in-use without relying on embedded static sensors.

SUMMARY OF THE INVENTION

[ooii] The inventor has discovered that it would be desirable to have a system and method that monitors and supervises transportation infrastructure while in-use. Embodiments provide a quality metric for transportation infrastructure using GPS location data, accelerometer data and data transmission over unguided media. The technology may be present in some vehicles either as separate mobile devices (e.g., cell phones, smartphones, portable computers, GPS street navigators) or devices integrated into the vehicle. Data is acquired while the vehicle traverses the transportation infrastructure.

[0012] One aspect of the invention provides a method for creating a transportation infrastructure record while traversing the infrastructure in a transport vehicle using a condition assessing mobile client. Methods according to this aspect of the invention include acquiring acceleration data (acceleration a,, a_^, a,) in one or more axes (x,y,z) wherein an x acceleration is in the direction of travel, a y acceleration is perpendicular to the x acceleration and a z acceleration is perpendicular to the plane defined by the x-y accelerations, determining if the acquired acceleration data (acceleration a_x, a_%, a.) is an acceleration perturbation, if the acquired acceleration data (acceleration a_t, a_s, a.) is an acceleration perturbation, accompanying the acquired acceleration data (acceleration a_x, a_v. a,) with an event duration

(timet_l~t₀) and location (latitude,longitude,altitude) , and classifying the acceleration perturbation as an avoidable obstacle if the acceleration perturbation was a symmetric positive/negative acceleration in the x direction, classifying the acceleration perturbation as an unavoidable obstacle if the acceleration perturbation was a negative acceleration in the x direction, classifying the acceleration perturbation as an avoidable obstacle if the acceleration perturbation was in the y direction, and classifying the acceleration perturbation as a hole or bump obstacle if the acceleration perturbation was in the z direction.

[0013] Another aspect of the invention further comprises calculating the position and size of an obstacle based on the acceleration data (acceleration a,, a_v, a,) for that obstacle, the transport vehicle speed (velocity V₁, v^v,) , and an event start/stop time (timet_l-t₀) for that obstacle.

[0014] Another aspect of the invention further comprises receiving obstacle data at a condition assessing server processor, accessing an infrastructure map where the obstacle is located, marking the location on the infrastructure map where the obstacle is located, and assembling an infrastructure quality map showing obstacles that indicate safety risks on the infrastructure map.

toois] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[0016] FIG. 1 is an exemplary system framework of a mobile transportation infrastructure condition assessing apparatus .

[0017] FIG. 2 is an exemplary system framework of a stationary processing apparatus for the mobile transportation infrastructure condition assessing apparatus .

[0018] FIG. 3 is an exemplary method.

DETAILED DESCRIPTION

[0019] Embodiments of the invention will be described with reference to the accompanying drawing figures wherein like numbers represent like elements throughout. Before embodiments of the invention are explained in detail, it is to be understood that the invention is not limited in its application to the details of the examples set forth in the following description or illustrated in the figures. The invention is capable of other embodiments and of being practiced or carried out in a variety of applications and in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of "including," "comprising," or "having," and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.

[0020] The terms "connected" and "coupled" are used broadly and encompass both direct and indirect connecting, and coupling. Further, "connected" and "coupled" are not restricted to physical or mechanical connections or couplings.

[002U It should be noted that the invention is not limited to any particular software language described or that is implied in the figures. One of ordinary skill in the art will understand that a variety of software languages may be used for implementation of the invention. It should also be understood that some of the components and items are illustrated and described as if they were hardware elements, as is common practice within the art. However, one of ordinary skill in the art, and based on a reading of this detailed description, would understand that, in at least one embodiment, components in the method and system may be implemented in software or hardware .

[0022] Embodiments of the invention provide methods, system frameworks, and a computer-usable medium storing computer-readable instructions that monitor transportation infrastructure and provide a quality metric using GPS location data, accelerometer data and data transmission over unguided media. The invention may be deployed as software as an application program tangibly embodied on a program storage device. The application code for execution can reside on a plurality of different types of computer readable media known to those skilled in the art.

[0023] Transportation infrastructure is primarily used to describe roadway and track, but may also refer to other types of transportation infrastructure.

[0024] In one embodiment, a permanent infrastructure record is produced that comprises location, time and acceleration data. It may be used as a permanent data source. A condition assessing mobile client embodiment or an existing mobile communication device such as a cell phone, smartphone, portable computer, GPS street navigator and others adapted for use as a condition assessing apparatus may be used during transport. Embodiments may or may not be used with a centralized condition assessing server due to the limited resources of existing mobile devices.

[0025] The permanent data acquisition may be used for a transportation infrastructure quality map, input to a server-side analysis where changes in infrastructure quality are tracked. The permanent data acquisition may be used to decide whether maintenance is necessary, show traffic patterns that indicate safety risks and be used as a detection/avoidance alarm.

[0026] Another embodiment is event based data acquisition. Accelerometer data in a condition assessing mobile client is buffered and a condition assessing server processor triggers predetermined events . For example, when acquired acceleration data correlates with a specific event, such as when an automobile strikes a roadway pothole or an object obstructs an infrastructure right-of-way, both become determined obstacles. The time and location of the event may be saved and/or transmitted to a server for future reference. The event based data acquisition may be used to prepare an infrastructure quality map containing unsafe spots on the infrastructure and to pass on impending warnings to other vehicles of an obstacle just experienced.

[0027] FIG. 1 shows an embodiment of a condition assessing mobile client framework 101 and FIG. 2 shows an embodiment of a condition assessing server processor 201. The mobile client 101 comprises a GPS receiver 103, a clock 105, a motion sensor suite 107, an online data synchronization module 109 communicating over a network 111, for example, General Packet Radio Service (GPRS) and Wireless Local Area Network (WLAN) ) , an offline data synchronization module 113 communicating over a network 111, for example, Local Area Network (LAN) and Recommended Standard-232 (RS-232), a Peer-to-Peer (P2P) communications module 115, an alert receiver 117, a processor 119, memory 121 and a data store 123.

[0028] The GPS receiver 103 outputs spatial information that indicates the vehicle's position/location in latitude, longitude, and elevation/altitude (spatial analysis) in time. Regarding the platform executing the mobile client 101, the GPS receiver 103 may be replaced by any available technology providing the required resolution for embodiments such as Assisted-GPS (A-GPS) , mobile phone tracking, and others. This includes systems that increase geographic sensor resolution through interpolation and extrapolation algorithms or triangulation. Location information is gathered at the technical sampling rate of the receiver 103 used and synchronized with the output of the clock 105. [0029] The motion sensor suite 107 may contain from one to three accelerometers capable of detecting acceleration in one or more corresponding perpendicular axes and are correlated with time. The dimension of the infrastructure determines the number of required accelerometers. Tracks can be considered as two dimensional and roadways as three dimensional. Using a subset number of accelerometers reduces the functionality correspondingly. An accelerometer measures the acceleration it experiences relative to freefall. Single- and multi-axis (two or more) accelerometers detect magnitude and direction of the acceleration as a vector quantity and are used to sense vibration and shock. Micromachined accelerometers are present in many portable electronic devices, such as smart phones . Most micromechanical accelerometers operate in-plane. Integrating two devices perpendicularly forms a two-axis accelerometer. Adding an additional out-of-plane device, three axes may be measured.

[0030] Depending on the transportation infrastructure to be measured, the accelerometer suite 107 has to provide an adequate sampling rate based on the Nyquist-Shannon theorem,

[0032] where f_t> is the required sampling frequency, s_mm is the maximum obstacle size to be detected, v_max is the maximum possible velocity and 2 is the multiplier required by Nyquist-Shannon.

[0033] The system clock 105 timestainps of the outputs of the GPS receiver 103 and motion sensor suite 107 with a high resolution signal to provide real-time data logging capability. The outputs of the GPS receiver 103, clock 105 and motion sensor suite 107 are coupled to the processor 119. The processor 119 combines the position, time and acceleration data and analyzes the collected data according to an executable program stored in memory 121. Results and acquired data are stored in the data store 123 if online data synchronization 109 is not available. If online data synchronization 109 is available, acquired data will be uploaded to the server processor 201 for additional data analysis.

[0034] The processor 119 is coupled to the online data synchronization module 109, offline data synchronization module 113, P2P communications module 115 and alert receiver 117.

[0035] The online data synchronization module 109 may transmit preprocessed data periodically, on-demand, or in real-time to the server processor 201 with a zero, or small time delay with respect to the time of data acquisition. The online data synchronization module 109 may use wireless transmission technologies over the communications network 111 such as WLAN, GPRS, Universal Mobile Telecommunications System (UMTS) , Code Division Multiple Access (CDMA) and others. The offline data synchronizer module 113 is used when online data transmission is not available at the time of data acquisition. In this case, all data is saved within the data store 123 until it can be actively synchronized with the server processor 201. For example, when reaching a maintenance station or an available location where a data connection over the network 111 to the server processor 201 is available. [0036] The alert receiver 117 receives communications from the server processor 201 to inform the mobile client 101 about determined obstacles on the transportation infrastructure that are an immediate threat to the mobile client based on the mobile client's present location.

[0037] Permanent obstacles are received by the server processor 201 as added map information, an equivalent to street signage commonly used in GPS navigation devices. This does not require constant communication to the server processor 201. Non-permanent obstacle information is acquired by the server processor 201 based on route information as calculated by the mobile client 101. If no route information is available, obstacle information is acquired from the server processor 201 within a specific radius. New obstacle information may be acquired each time the mobile client 101 moves beyond, for example, 0.5 units of a specified radius. This information is acquired based on the actual use and position of a mobile client 101 (online situation) as well as planned use and position (offline situation) of the mobile client 101 within the infrastructure. The P2P communications module 115 communicates with nearby peers using the same transportation infrastructure to share nearby obstacle information.

[0038] Peer detection is performed through commonly used directed P2P technology such as supernodes or distributed hash tables. In case an obstacle is detected, alert information will be distributed through the supernode to all nearby clients.

[0039] The condition assessing server processor 201 comprises an online data collector module 203, an offline data collector module 205, an alert system 207, a processor 209, a reference motion sensor data store 211, a reference map data store 213, a maintenance identification module 215, an obstacle database 217 and memory 219 ,

[0040] The online data collector 203 allows mobile clients 101 to send (synchronize) information over the network 111 to the server processor 201. The online data collector 203 receives data and forwards it to the processor 209. The offline data collector 205 receives data from mobile clients 101 whenever clients 101 reach an area allowing communications, and transmits infrastructure data processed by a mobile client 101 based on its use between the last and current synchronization .

[0041] A vehicle traversing a transportation infrastructure determines the origin of an accelerated coordinate system with respect to the reference GPS determined coordinate system 103. x determines the forward (positive) or reverse (negative) direction of movement, y any horizontal movement and z any vertical movement. Expected accelerations are filtered via comparison to reference motion data 211. x direction accelerations determine changes in forward/reverse speed (velocity) (e.g. , stop signs, traffic lights, sudden stops, etc.) , y accelerations determine changes in x direction (e.g., turns, curves, swerves, etc.) , z accelerations determine changes in the plane defined by the x—y directions (e.g., hills, bumps, potholes, etc.) . Obstacles are determined by x,y,orz direction acceleration perturbations from the reference motion data 211. Symmetric positive/negative acceleration perturbations in the x direction define avoidable obstacles. Negative acceleration perturbations in the x direction define unavoidable obstacles. Acceleration perturbations in the y direction define avoidable obstacles that require reduced speed. Acceleration perturbations in the z direction define holes or bumps. Current transport vehicle speed {velocity v^v^w) combined with acceleration perturbations {acceleration a_x. a_v. a,) and an event start/stop time {timet_x —t₀) is used to calculate the position and size of an obstacle as well as to determine a safe speed to negotiate the obstacle if possible.

[0042] The reference map 213 contains the topology of the transportation infrastructure being traversed and assessed. The obstacle database 217 contains obstacles identified and determined from experience by mobile clients 101 via the processor 209. The processor 209 constructs a database listing: 1) obstacle position - the location of an identified obstacle {latitude, longitude, altitude) . The position defines the center of the obstacle, 2) obstacle size - the size of the identified obstacle is based on its center position, 3) vehicle direction - the vector {velocity v_x,v_%,v_z) of the moving transport vehicle during the obstacle's detection, 4) avoidable obstacle - if the obstacle is avoidable, 5) unavoidable obstacle (blocking) - if the obstacle is blocking the transportation infrastructure way in the vehicle direction, 6) permanent obstacle - if the obstacle is part of the transportation infrastructure rather than an obstacle that has been added to the infrastructure. Permanent obstacles are determined by the server processor 209 using an obstacle's detection count and event timestamp(s) , 7) safety factor - a factor to calculate a safe speed to negotiate an avoidable obstacle, 8) detection count - how many times the obstacle has been identified by mobile clients 101, and 9) obstacle timestamp - the last time the obstacle was detected.

[0043] The reference motion sensor data 211 provides information on the expected acceleration for each point within the transportation infrastructure, for example, for uniform transversal motion only vertical acceleration is expected.

[0044] The data processor 209 couples with the data collectors 203, 205 to synchronize with one or more mobile clients 101. The online data collector 203 performs the same tasks as the offline data collector 205 but in real-time. The offline data collector 205 receives data uploaded by mobile clients 101 to increase the detection count of determined obstacles, or to add new obstacles to the database 217.

[0045] The reference map data 213 maintains reference map information for visual representation of the transportation infrastructure with data from the mobile clients superimposed on it. It is possible to obtain reference map data to extend the current map system in case of infrastructure changes. For example, in case of permanent blocking obstacles, the processor 209 detects these and modifies the reference map data appropriately.

[0046] The obstacle database 217 is used when analyzing data collected from the mobile client (s) 101. The processor 209 adds new obstacles to the database 217 or increases the detection count for known obstacles. The reference motion sensor data 211 lists expected accelerations [acceleration a,,α_v, a,) of each point in the transportation infrastructure topology when moving through the infrastructure. The processor 209 inputs these values in order to determine the existence of new obstacles within the infrastructure.

[Q047] The alert system 207 monitors the obstacle database 217 and sends alerts to interested mobile clients 101. In case of online clients 101, the P2P system 115 is used to determine interested nearby peers that may require immediate reaction to certain obstacles. The maintenance identification system 215 monitors the obstacle database 217 at a lower frequency and determines transportation infrastructure routes that require maintenance activity.

[0048] FIG. 3 shows data acquisition and processing among one or more mobile clients 101 and a server processor 201. For a vehicle traversing a transportation infrastructure, for example, a first automobile on a roadway, (step 301) , the mobile client 101 being either a portable smart device executing the condition assessing framework or one fixed to the first automobile, constantly acquires acceleration data (acceleration a_v, a_λ, a,) in one or more axes (step 303) .

[0049] For an acceleration axis perturbation, the acceleration data [acceleration a_x, a^, a,) is stored with an event timestamp (timet) , an event duration (timet_] -t₀) , location (latitude,longitude,altitude) and the vehicle's vector (velocity v_x,v_^,v_) (step 305) . The mobile client 101 calculates the size of an acceleration perturbation from the location (latitude,longitude,altitude) and event duration (timeI₁ ^t₀) (step 307) .

£0050] The mobile client 101 compares the acquired acceleration data [acceleration a_x, a_^, a.) with a reference and thresholds 123 to eliminate background acceleration noise that is not part of the transportation infrastructure (step 309) . The acceleration data {acceleration a_x, a_%, a.) classifies an obstacle as avoidable for symmetric positive/negative x accelerations a_x , unavoidable for negative only x accelerations a_x , an obstacle requiring avoidance for v accelerations α_v and a hole or bump for z accelerations a, (step 311) . The classified obstacle data is stored 123.

[0051] If a communications link is available over the network 111, the obstacle data is transmitted to the server processor 201 (steps 313, 317, 319) . If a communications link is not available, the obstacle data is stored 123 at the mobile client 101 for future uploading to the server processor 201 (steps 313, 315) .

[0052] If peer detection is acknowledged, a P2P communications link is available and the mobile client 101 broadcasts the obstacle data to other mobile clients in a predetermined proximity, for example, a second automobile with a mobile client 101 traveling behind and in the same direction as the first automobile (steps 313, 317, 331, 333) .

[0053] Using P2P technology, peers exchange obstacle information to their assigned supernode, the supernode is responsible for sending obstacle information to all subnodes . Obstacles are identified by comparing acceleration data to reference data and defined thresholds. The alert receiver 117 then takes necessary action for notifying a vehicle operator and may be any available or future technology capable of representing spatial information to the vehicle operator. This may be, but Is not limited to visual representation on a map, acoustic notification in form of speech or earcons, haptic feedback on the transportation vehicle (vibration, force, etc.) or any combination.

[0054] The obstacle data is received at the server processor 210 (step 319). Using the obstacle's location data, a map is accessed 213 of the traversed infrastructure (step 321) and the location of the obstacle is marked (step 323) .

[0055] For each obstacle, the processor 209 creates and stores attributes pertaining to the obstacle in a database 217 (step 325) . From the obstacle attributes 217 in conjunction with the marked infrastructure map 213, an infrastructure quality map is assembled (step 327) . An alert is sent to subscribed vehicles approaching an identified obstacle(s) (steps 325, 327).

[0056] Mobile clients 101 with online data sync module 109 and route calculation capability such as street navigation systems subscribe to alert information on the given route. If deviations from the calculated route are detected the new route segment will be added to the subscription. Mobile clients 101 with offline data sync module 113 capability only will use the processor 119 in conjunction with storage 123 and current GPS position 103. Depending on the information representation capabilities of the mobile device supporting the mobile client 101 system framework, the vehicle operator will be notified in proximity to an obstacle.

[0057] One or more embodiments of the present invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. Accordingly, other embodiments are within the scope of the following claims .

Claims

CLAIMSWhat is claimed is:

1. A method for creating a transportation infrastructure record while traversing the infrastructure in a transport vehicle using a condition assessing mobile client comprising: acquiring acceleration data [accelerationa_t,a^,a.) in one or more axes (x,y,z) wherein an x acceleration is in the direction of travel, a y acceleration is perpendicular to the x acceleration and a z acceleration is perpendicular to the plane defined by the x — y accelerations; determining if the acquired acceleration data [acceleration a_x, a^, a.) is an acceleration perturbation; if the acquired acceleration data {acceleration a ,, a_v, a,) is an acceleration perturbation, accompanying the acquired acceleration data (accelerationa_x, a_v,a.) with the acceleration perturbation event duration (timet_l —t_Q) and location (latitude,longitude,altitude) as obstacle data; and classifying the acceleration perturbation as an avoidable obstacle if the acceleration perturbation was a symmetric positive/negative acceleration in the x direction, classifying the acceleration perturbation as an unavoidable obstacle if the acceleration perturbation was a negative acceleration in the A- direction, classifying the acceleration perturbation as an avoidable obstacle if the acceleration perturbation was in the >^• direction, and classifying the acceleration perturbation as a hole or bump obstacle if the acceleration perturbation was in the z direction,

2. The method according to claim 1 further comprising comparing the acquired acceleration data

against reference acceleration data to determine if the acquired acceleration data {acceleration a _x, a _v. a. ) is an acceleration perturbation,

3. The method according to claim 1 further comprising filtering noise from the acquired acceleration data [accelerationa_t ,a_v .α, ) .

4. The method according to claim 1 further comprising calculating the position and size of an obstacle based on the acceleration data [accelerationa_Λ,a_v,a.), the transport vehicle speed (velocityv_x,v_x,v_) and an event start/stop time (timet_x-t_Q) for that obstacle.

5. The method according to claim 4 further comprising calculating a safe speed to negotiate avoidable obstacles .

6. The method according to claim 5 wherein the condition assessing mobile client further comprises a cell phone, a smartphone, a portable computer or a street navigator adapted for use as a condition assessing apparatus.

7. The method according to claim 1 further comprising determining if a network communications link is available to a condition assessing server processor.

8. The method according to claim 7 wherein if the network communications link is not available, storing obstacle data at the mobile client for future uploading to the condition assessing server processor.

9. The method according to claim 7 wherein if a network communications link is available to a condition assessing server processor, receiving obstacle data at a condition assessing server processor comprising: accessing an Infrastructure map where the obstacle is located; marking the location on the Infrastructure map where the obstacle is located; and assembling an infrastructure quality map showing obstacles that indicate safety risks on the infrastructure map.

10. The method according to claim 9 further comprising passing on warnings to other vehicles of an obstacle.

11. The method according to claim 10 further comprising tracking obstacles added to the infrastructure quality map.

12. The method according to claim 11 further comprising for each obstacle, creating and storing attributes pertaining to the obstacle in a database.

13. The method according to claim 12 wherein for each determined obstacle, the obstacle database attributes comprise : the obstacle's position defined as the center of the obstacle; the obstacle's size based on the obstacle's center position; the vehicle's vector [velocity V₁ Λ\,V. ) when the obstacle is detected; whether the obstacle is: avoidable, if the obstacle is avoidable; unavoidable, if the obstacle is blocking the transportation infrastructure way In the vehicle's direction; permanent, If the obstacle Is part of the transportation infrastructure, determined using an obstacle's detection count and event timestamp(s) ; and a safety factor to calculate a safe speed to negotiate an avoidable obstacle; a detection count of how many times the obstacle has been identified by condition assessing mobile clients; and the obstacle's timestarnp.

14. The method according to claim 13 further comprising sending an alert to subscribed vehicles approaching an obstacle .

15. A system for creating a transportation infrastructure record while traversing the infrastructure in a transport vehicle in real-time comprising: a condition assessing mobile client comprising: a motion sensor suite configured to acquire acceleration data (acceleration a_x,a_v,a, ) in one or more corresponding perpendicular axes (x,y,z) wherein an x acceleration is in the direction of travel, a y acceleration is perpendicular to the x acceleration and a z acceleration is perpendicular to the plane defined by the x- y accelerations; a processor, memory and data store, the processor configured to execute instructions from the memory that determines acceleration perturbations from the acquired acceleration data {acceleration a_x, a_^,a.) and accompanies acceleration perturbation acceleration data (acceleration a_l, a_%, a,) with the acceleration perturbation event duration (timet_x —t₀) and location (latitude,longitude,altitude) as obstacle data, and classifies the obstacle data as an avoidable obstacle if the acceleration perturbation was a symmetric positive/negative acceleration in the x direction, classifying the acceleration perturbation as an unavoidable obstacle if the acceleration perturbation was a negative acceleration in the x direction, classifying the acceleration perturbation as an avoidable obstacle if the acceleration perturbation was in the y direction, and classifying the acceleration perturbation as a hole or bump obstacle if the acceleration perturbation was in the z direction.

16. The system according to claim 15 further comprising a Peer-to-Peer (P2P) communications module configured to broadcast obstacle data to other condition assessing mobile clients in a predetermined proximity.

17. The system according to claim 15 further comprising an online data synchronization module configured to communicate over a network in real-time with a condition assessing server processor.

18. The system according to claim 17 further comprising an offline data synchronization module configured to communicate over a network not in real-time with the condition assessing server processor.

19. The system according to claim 18 wherein the condition assessing server processor comprises: an online data collector module configured to receive obstacle data from condition assessing mobile clients in real-time; an offline data collector module configured to receive obstacle data from condition assessing mobile clients not in real-time; and a processor, memory and data store configured to receive obstacle data from one or more condition assessing mobile clients, access an infrastructure map where an obstacle is located, mark the location on the infrastructure map where the obstacle is located and assemble an infrastructure quality map showing obstacles that indicate safety risks on the infrastructure map.

20. The system according to claim 19 wherein, the condition assessing processor creates and stores attributes pertaining to each obstacle in a database, the obstacle database attributes comprising: the obstacle's position defined as the center of the obstacle; the obstacle's size based on the obstacle's center position; the vehicle's vector [velocity v_λ,ι\,v, ) when the obstacle is detection; whether the obstacle is: avoidable, if the obstacle is avoidable; unavoidable, if the obstacle is blocking the transportation infrastructure way in the vehicle direction; permanent, if the obstacle is part of the transportation infrastructure determined using an obstacle's detection count and event timestamp (s) ; and a safety factor to calculate a safe speed to negotiate an avoidable obstacle; a detection count of how many times the obstacle has been identified by mobile clients; and the obstacle's timestamp.