CN110033614A - A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things - Google Patents
A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things Download PDFInfo
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- CN110033614A CN110033614A CN201910220599.2A CN201910220599A CN110033614A CN 110033614 A CN110033614 A CN 110033614A CN 201910220599 A CN201910220599 A CN 201910220599A CN 110033614 A CN110033614 A CN 110033614A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0816—Indicating performance data, e.g. occurrence of a malfunction
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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Abstract
The road hazard cargo transport dynamic risk early warning system based on technology of Internet of things that the invention discloses a kind of, including on board unit, out vehicle waybill module, risk assessment unit.Wherein on board unit includes vehicle localization module, vehicle operating parameters acquisition unit, driver parameter's acquisition module, Information procession and communication module and alarm module；Vehicle waybill module includes vehicle basic information module, driver's basic information module, goods information module and transit route information module out；Risk assessment unit includes geography information parsing module, and shipping accident probability assessment database, transport consequence assessment database and risk in transit assess database.According to Risk Results, with risk acceptability threshold value comparison, if it exceeds risk acceptable thresholds, system issues alarm, the present invention can assess Road Hazardous Materials Transportation dynamic risk in real time simultaneously, early warning when exceeding acceptance to risk realizes intelligence auxiliary supervision risk in transit, promotes Dangerous Goods Transport management level.
Description
Technical field
The invention belongs to road safety technical field, in particular to a kind of road hazard cargo fortune based on technology of Internet of things
Defeated dynamic risk early warning system.
Technical background
In recent years, China's dangerous cargo year highway transport volume increased year by year.For example same flowing of vehicle transport dangerous goods
" bomb ", life security and property safety to the people cause potential danger.In recent years, a lot of dangerous goods have been recurred
Object transports special major accident, as the especially great road at 10 meters of the tunnel face Jincheng, Shanxi Duan Yanhou occurs in March, 2014
Traffic harmful influence blast accident causes the vehicle in the fiery tunnel that ignites of methanol trickling, causes more people dead, what 42 vehicles were burned out
Serious consequence.This not only hinders the sound development of industry, seriously threatens people life property safety, more to social stability and certainly
Right environment adversely affects.
Safety of China department and transportation department require that transport enterprise reinforces the supervision of Dangerous Goods Transport process dynamics, according to
Monitoring equipment is equipped with special monitor to transport dynamic parameter supervision.However existing monitoring is mostly manually to monitor, and is monitored simultaneously
Tens vehicles, working strength is larger, and some monitoring personnel work are half-hearted in addition, monitors help lacking Risk-warning auxiliary
Under, being easy to cause risk, there are loopholes.Therefore urgently study based on Internet of Things acquisition transport dynamic parameter, to risk in transit into
Row assessment in real time, intelligent early-warning technology.
Summary of the invention
It is an object of the invention to overcome above-mentioned the deficiencies in the prior art, the present invention is based on technology of Internet of things, building transports
Venture influence dynamic parameter acquisition system develops the risk in transit real-time evaluation system based on dynamic parameter and according to risk assessment
As a result early warning is carried out.
Technical solution is as follows:
A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things, which is characterized in that including
On board unit, out vehicle waybill module, risk assessment unit.Vehicle waybill module and risk assessment unit are integrated into server out, lead to
It crosses wireless telecommunications and on board unit communicates.On board unit includes vehicle localization module, vehicle operating parameters acquisition unit, is driven
Member's parameter collection module, Information procession and communication module and alarm module；Out vehicle waybill module include vehicle basic information module,
Driver's basic information module, goods information module and transit route information module；Risk assessment unit includes geography information solution
Module, shipping accident probability assessment database are analysed, transport consequence assessment database and risk in transit assess database.According to risk
As a result, if it exceeds risk acceptable thresholds, system issues control instruction, on board unit with risk acceptability threshold value comparison
Alarm module issue alarm.Wherein, alarm module includes loudspeaker and emergency warning lamp.
The on board unit includes vehicle localization module, geographical location and the speed parameter of vehicle is acquired, for parsing
Geography information issues position command, the linear dimensions based on location information analysis road；Vehicle operating parameters acquisition module, passes through
CAN line reads engine speed, error code, acquires turning angle of steering wheel, throttle valve angle, indicating brake action, wheel by sensor
Tire pressure and temperature these parameters；Driver parameter's acquisition unit, including image collecting device and identification module, drive for identification
The person's of sailing fatigue state and driver's mood；Information procession and communication module, including information processing and storage unit and information are led to
Module is interrogated, for processing and cache information, reduces the data traffic of communication module and server background communication；
The vehicle waybill module out includes vehicle basic information module, driver's basic information module, goods information module
And routing information module.Wherein, vehicle basic information module mainly inputs the industrial grade of vehicle, annual test qualification situation, vehicle
Annual test parameter, lights of vehicle annual test parameter are braked, vehicle annual test safety devices are equipped with as a result, vehicle appearance testing result, it is proposed that
Safeguard item, comprehensive oil consumption；Driver's basic information module mainly inputs the violation information of driver, accident information, personality information
With driving age information；Goods information module inputs title, the classification of cargo, international code, combustion heat value, emergency measure information；Line
Road information module inputs beginning and end, transportation route and fence, each road section speed limit information.
The Risk-warning process are as follows: according to vehicle position information, geographical parsing information, onboard sensor information and CAN
The vehicle operating information that line is read, after acquisition parameter is processed as requested, is sent to server background by communication module, after
Platform parses geographical environmental information according to location information, in conjunction with the input information of waybill, in risk in transit accident probability and consequence number
The quantized value that different parameters corresponding accident probability and damage sequence is transferred according to library is transported by risk assessment database model logic
It calculates, calculates the risk in transit of collection process, and the accumulative risk in transit for obtaining entire transportational process or the risk in transit in certain section.
The risk in transit for certain transportation route that risk evaluation module assessment is set according to waybill module, and judge whether to be more than that risk can connect
It is spent, if it exceeds being issued warning signal to risk warning module.Wherein, accident probability and category of roads, road linearity parameter,
Road track number, road construction object, weather, temperature, speed, the volume of traffic, road speed limit are related.In damage sequence radius of vulnerability with
Goods information is related, population exposed amount and the volume of traffic, densely populated place area quantity, and surrounding car quantity and traffic composition are related.
Risk in transit is offset related to driver safety, technology state of vehicle and enterprise security manager level joint.
The safety of the driver is evaluated according to following information parameter, vehicle operating parameters: engine speed, steering wheel
Steering angle, throttle valve angle, indicating brake action sensor information, driver status information: driver fatigue state and driver drive
Sail mood, driver's essential information: violation information, accident information, personality information and the driving age information of driver, driving behavior are dynamic
State information: transportational process hypervelocity, time-out and not press link travel；Technology state of vehicle is according to following information evaluation, engine event
Barrier, tyre temperature and air pressure, vehicle essential information: the industrial grade of vehicle, annual test qualification situation, vehicle braking annual test parameter,
Lights of vehicle annual test parameter, vehicle annual test safety devices are equipped with result, vehicle appearance testing result, suggest maintenance item, comprehensive oily
Consume information；Enterprise security manager level is evaluated according to driver safety and technology state of vehicle evaluation result.
The invention has the following beneficial effects:
The present invention is based on existing technology of Internet of things to acquire road hazard cargo transport dynamic parameter, and further passes through vehicle
The perfect information acquisition system of the increased sensor of loading system, meanwhile, necessary information is subjected to input by waybill module and is adopted
Collection.The Risk Evaluating System of exploitation is according to the dynamic parameter of acquisition, the corresponding risk in transit quantization of each parameter in called data library
Index realizes the real-time intelligent assessment of risk in transit, based on Risk Results and acceptable degree threshold value comparison, reaches transport dynamic
The function of risk intelligent evaluation and early warning.The accuracy that risk in transit is improved by dynamic acquisition variable element, improves
Road Dangerous Goods Transport safety management level.
Detailed description of the invention
Fig. 1 is a kind of structure of the road hazard cargo transport dynamic risk early warning system based on technology of Internet of things of the present invention
Figure.
Fig. 2 is a kind of early warning of the road hazard cargo transport dynamic risk early warning system based on technology of Internet of things of the present invention
Flow chart.
Specific embodiment
To make those skilled in the art more fully understand technical solution of the present invention, the present invention is mentioned with reference to the accompanying drawing
A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things supplied, is described in detail.Following reality
It applies example and is merely to illustrate the range of the present invention and is not intended to limit the present invention.
Embodiment 1
A kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things, including on board unit 2, out
Vehicle waybill module 9, risk assessment unit 8.Vehicle waybill module 9 and risk assessment unit 8 are integrated into server out, pass through channel radio
News are communicated on board unit.On board unit includes vehicle localization module 1, vehicle operating parameters acquisition unit, and driver parameter adopts
Collect module, Information procession and communication module 3 and alarm module 14；Vehicle waybill module includes vehicle basic information module 12, drives out
The person's of sailing basic information module 13, goods information module 11 and transit route information module 10；Risk assessment unit includes geographical letter
Parsing module 4, shipping accident probability assessment database 5 are ceased, transport consequence assessment database 6 and risk in transit assess database 7.
According to Risk Results, with risk acceptability threshold value comparison, if it exceeds risk acceptable thresholds, system issues control instruction,
The alarm module 14 of on board unit issues alarm.Wherein, alarm module 14 includes loudspeaker and emergency warning lamp.
The on board unit includes vehicle localization module, geographical location and the speed parameter of vehicle is acquired, for parsing
Geography information issues position command, the linear dimensions based on location information analysis road；Vehicle operating parameters acquisition module, passes through
CAN line 19 reads engine speed, error code, passes through sensor orientation disk steering angle sensor 17, throttle angle sensor
16, brake pedal dynamics sensor 15, tire pressure and temperature sensor 18 acquire each parameter；Driver parameter's acquisition unit,
Including image collecting device and identification module 20, driver fatigue state and driver's mood for identification；Information procession and logical
Module 3, including information processing and storage unit and information communication module are interrogated, for processing and cache information, reduces communication mould
The data traffic of block and server background communication；
The vehicle waybill module out includes vehicle basic information module 12, driver's basic information module 13, goods information
Module 11 and routing information module 10.Wherein, vehicle basic information module 12 mainly inputs the industrial grade of vehicle, and annual test is qualified
Situation, vehicle braking annual test parameter, lights of vehicle annual test parameter, vehicle annual test safety devices are equipped with as a result, vehicle appearance detects
As a result, it is proposed that maintenance item, comprehensive oil consumption；Driver's basic information module 13 mainly inputs the violation information of driver, accident letter
Breath, personality information and driving age information；Goods information module 11 inputs title, the classification of cargo, international code, and combustion heat value is answered
Anxious Action Message；Routing information module 10 inputs beginning and end, transportation route and fence, each road section speed limit information.
The Risk-warning process are as follows: according to vehicle position information, geographical parsing information, onboard sensor information and CAN
The vehicle operating information that line is read, after acquisition parameter is processed as requested, is sent to server background by communication module, after
Platform parses geographical environmental information according to location information, in conjunction with the input information of waybill, in risk in transit accident probability and consequence number
The quantized value that different parameters corresponding accident probability and damage sequence is transferred according to library is transported by risk assessment database model logic
It calculates, calculates the risk in transit of collection process, and the accumulative risk in transit for obtaining entire transportational process or the risk in transit in certain section.
The risk in transit for certain transportation route that risk evaluation module assessment is set according to waybill module, and judge whether to be more than that risk can connect
It is spent, if it exceeds being issued warning signal to risk warning module.Wherein, accident probability and category of roads, road linearity parameter,
Road track number, road construction object, weather, temperature, speed, the volume of traffic, road speed limit are related.In damage sequence radius of vulnerability with
Goods information is related, population exposed amount and the volume of traffic, densely populated place area quantity, and surrounding car quantity and traffic composition are related.
Risk in transit is offset related to driver safety, technology state of vehicle and enterprise security manager level joint.
The safety of the driver is evaluated according to following information parameter, vehicle operating parameters: engine speed, steering wheel
Steering angle, throttle valve angle, indicating brake action sensor information, driver status information: driver fatigue state and driver drive
Sail mood, driver's essential information: violation information, accident information, personality information and the driving age information of driver, driving behavior are dynamic
State information: transportational process hypervelocity, time-out and not press link travel；Technology state of vehicle is according to following information evaluation, engine event
Barrier, tyre temperature and air pressure, vehicle essential information: the industrial grade of vehicle, annual test qualification situation, vehicle braking annual test parameter,
Lights of vehicle annual test parameter, vehicle annual test safety devices are equipped with result, vehicle appearance testing result, suggest maintenance item, comprehensive oily
Consume information；Enterprise security manager level is evaluated according to driver safety and technology state of vehicle evaluation result.
The present invention is based on existing technology of Internet of things to acquire road hazard cargo transport dynamic parameter, and further passes through vehicle
The perfect information acquisition system of the increased sensor of loading system, meanwhile, necessary information is subjected to input by waybill module and is adopted
Collection.The Risk Evaluating System of exploitation is according to the dynamic parameter of acquisition, the corresponding risk in transit quantization of each parameter in called data library
Index realizes the real-time intelligent assessment of risk in transit, based on Risk Results and acceptable degree threshold value comparison, reaches transport dynamic
The function of risk intelligent evaluation and early warning.The accuracy that risk in transit is improved by dynamic acquisition variable element, improves
Road Dangerous Goods Transport safety management level.
Above-mentioned Dangerous Goods Transport dynamic risk early warning system can should be with the following method, comprising the following steps:
The first step acquires current transportation process dynamics parameter, including goods information, vehicle fortune based on technology of Internet of things in real time
Row information, road information, traffic information, environmental information.
S11 goods information includes: the classification of cargo, quality, combustion heat value；
S12 vehicle operating information includes: vehicle position information, vehicle speed information, speed acceleration information, vehicle startup
Machine information, vehicle operation temporal information, automotive comprehensive performance detection information；
S13 road information includes: the classification of road, and grade, number of track-lines, region, speed limit, lane is wide, ground surface material
Information, road construction object；
S14 traffic information includes: the magnitude of traffic flow, traffic congestion situation, traffic average speed, traffic composition, car position
Information；
S15 environmental information includes: weather, temperature, visibility, environmental sensitive area, dense population areas population amount, region
The density of population.
Second step calculates transportation of dangerous goods leakage accident Probability p j based on dynamic parameter；
S21 is according to road parameters: number of track-lines n, region q, category of roads d, and road speed limit vx determines road traffic thing
Therefore probability.Number of track-lines is divided into bicycle road, two-way traffic, multilane, and region is divided into city, rural area, and category of roads is divided into high speed
With level-one, second level, three and level Four, etc. it is outer, speed limit is divided into 120km/h, 100km/h, 80km/h, 70km/h, 60km/h, 50km/
H, 50km/h or less；
S22 is according to haulage time t, the accounting b of cart, weather T, temperature in road width D, volume of traffic Q and traffic composition
K, visibility S, road curve radius R, road grade P respectively correct traffic accident probability, and determine correction factor ki；
S23 determines the dangerous cargo leakage probability under traffic accident occurrence condition according to category of roads and region
px；
Third step determines the extent of injury of accident, including radius of vulnerability, population exposed amount based on dynamic parameter.
S31 accident injury radius is obtained according to goods information and the database established based on the information；
S32 incident area population exposed amount is divided into: road, under road, compact district population exposed amount.On the road, under road and intensive
Area's population exposed amount calculation formula is respectively as follows:
Soff=[λ+(1- λ) δj](πr2-2rB)ρ；
In formula: Son: road personnel's exposed amount, people；R: venture influence range radius, km；N: vehicle current driving road
Two-way lane number；θ: vehicle is averaged bearing capacity factor, and people/；f(v)i: the traffic density on the i of lane, people/km；Fb: non-motor vehicle
With the ratio S of vehicles numberc: densely populated place area personnel's exposed amount, people on road；P (i): the personnel of road densely populated place area i
Quantity, people；λ: densely populated place area personnel appear in outdoor ratio；δj: jth class cargo leads to the impacted probability of indoor occupant.
Si: i-th car appraises and decides passenger capacity in risk zones；The practical cabin factor of z car.Soff: densely populated place area personnel on road
Exposed amount, people；R: influence area radius, km；B: highway layout overall width, km；ρ: average population density under road, people/km2；
4th step, risk in transit offsets the factor and risk in transit is offset model and determined.
Driver, haulage vehicle and the business administration are offset the factor as risk in transit by s41.According to dynamic parameter,
Driver safety A and technology state of vehicle J are evaluated, and to according to driver safety and technology state of vehicle to it belonging to
The management level G of enterprise is evaluated.
Evaluation result of the s42 according to counteracting factor three, calculation risk cancellation, calculation formula:
A=(1-K1)(1-K2)(1-K3)
K1=K1AV1, K2=K1BV2, K3=K1CV3
In formula: K1, K2, K3: it is respectively vehicle arrangement, transport operation personnel and Transport Enterprises of Road Dangerous Goods bursting tube
Manage correction factor；K1A, K1B, K1C: it is respectively the maximum of vehicle arrangement, transport operation personnel and enterprise security manager modifying factor
Counteracting rate.V1, V2, V3: the actual evaluation of respectively vehicle arrangement, transport operation personnel and enterprise security manager modifying factor obtains
Divide and the ratio of corresponding deserved score value.
5th step calculates risk in transit according to each data collection data and determines each collection process Dangerous Goods Transport
Accident probability, damage sequence and mileage travelled calculate each risk in transit, and the transport in each section of cumulative calculation as needed
Risk.According in way Real-Time Transport Risk Results, it is comprehensively compared for different route risk in transit, it can also be used to Risk-warning.
Each collection process Dangerous Goods Transport Risk Calculation formula are as follows:
In formula: Ri: road hazard cargo road personnel's exposure when i-th information collection；L: i-th data acquired
The distance of journey running car, km；KjRisk in transit offsets the factor；f(v)i: the traffic density in the lane i；R: accident injury radius,
km；The dangerous cargo leakage accident that the non-traffic accident of f causes accounts for the ratio that traffic accident causes leakage accident.
Traffic density, can be by being calculated with the model that traffic flow speed is established, calculation method are as follows:
In formula, f (v): the corresponding traffic density of each vehicle speed range ,/lane km；Kz: when free flow, traffic density
Upper limit value ,/lane km；A, b: when traffic flow is in stationary flow, speed and traffic density linear relationship coefficient；kj: obstruction
Traffic density value ,/lane km；vm: wagon flow reaches the speed value of the traffic capacity, km/h；V: road averagely runs vehicle
Speed, km/h；v1、v2: it is respectively small density, the corresponding average critical speed of medium heavy traffic density, km/h.
The model of different brackets road conditions each parameter kz, a, b, kj、vm、v1、v2It is fitted according to field survey data
It obtains.
Driver safety evaluation method are as follows: the awareness of safety of driver and the operation of driver are horizontal.Driver safety meaning
Know by hypervelocity behavior, the driving behavior of driver's time-out and driver's uneasiness route driving behavior evaluation；Driver operates horizontal branch
According to driver's downhill running behavior, driver's descending not drag-down behavior and driver's speed estimation of stability.
Wherein, driver's generation awareness of safety corresponds to behavior, deducts corresponding score value；Driver's operation behavior: lower hill wash
Capable or low-grade descending auxiliary braking behavior, judges according to link location information, speed and rotary speed information；When in descending process
In, speed and revolving speed are judged to sliding or non-low-grade behavior beyond threshold value set by each behavior, deduct corresponding safe score.
Driver's speed stability, differentiates according to speed standard deviation.The standard deviation of speed is denoted as J in 20km/h or less21,
Score 100 is divided；Speed standard deviation is denoted as J22 in 20-40km/h, and score 80 is divided, speed standard deviation be greater than 40km/h or 3 time with
Upper speed standard deviation is denoted as J in 20-40km/h23, score 60 divides.
Technology state of vehicle judges according to automotive comprehensive performance detection data, is equipped with situation, braking according to safety device
Energy detection data, tire specification data evaluate technology state of vehicle.
Offset the Weight Determination of each evaluation index of the factor are as follows: by Dangerous Goods Transport accident by counteracting factor accident
Reason statistical analysis, and expert analysis mode opinion is combined, finally obtain the weight of each factor.
The population exposed amount calculation formula of the dense population areas service area are as follows:
In formula: the impacted personnel's exposed amount of P (i): i-th service area, people；Q: the road-section average volume of traffic per hour ,/
h；S: rate, value 0.15 are driven into；T: average down time, value 30min.
The systems and methods realize Risk Evaluation Factors fining, and mobilism objectifies.It has fully considered and had transported
The retrievable dynamic parameter number of journey constructs the dynamic indicator such as volume of traffic, compact district population to the quantization influence of risk in transit
The dynamic indicators assessment models such as exposed amount.Use objective quantized data estimated risk evaluation index such as driver safety, vehicle
Technology status, so that risk assessment index refines.It is intelligent, real-time that the systems and methods also achieve risk assessment
Change, based on the transport dynamic parameter that technology of Internet of things acquires in real time, using database parameter threshold value, directly transfers risk in transit and comment
Valence index parameter threshold value assesses risk in transit value in real time, realizes that risk in transit is assessed in real time, the purpose of intelligent evaluation.Improve road
The management level of Dangerous Goods Transport.
Example of the invention is explained in detail above in conjunction with embodiment, but the present invention is not limited to examples detailed above,
Within the knowledge of a person skilled in the art, it can also make without departing from the purpose of the present invention
Various change also should be regarded as protection scope of the present invention.
Claims (5)
1. a kind of road hazard cargo transport dynamic risk early warning system based on technology of Internet of things, which is characterized in that including vehicle
Carrier unit, out vehicle waybill module, risk assessment unit；Vehicle waybill module and risk assessment unit are integrated into server out, pass through
Wireless telecommunications and on board unit communicate；On board unit includes vehicle localization module, vehicle operating parameters acquisition unit, driver
Parameter collection module, Information procession and communication module and alarm module；Vehicle waybill module includes vehicle basic information module, drives out
The person's of sailing basic information module, goods information module and transit route information module；Risk assessment unit includes geography information parsing
Module, shipping accident probability assessment database, transport consequence assessment database and risk in transit assess database；According to risk knot
Fruit, with risk acceptability threshold value comparison, if it exceeds risk acceptable thresholds, system issues control instruction, on board unit
Alarm module issues alarm, wherein alarm module includes loudspeaker and emergency warning lamp.
2. the road hazard cargo transport dynamic risk early warning system according to claim 1 based on technology of Internet of things,
It is characterized in that, the on board unit includes vehicle localization module, geographical location and the speed parameter of vehicle is acquired, for solving
It analyses geography information and issues position command, the linear dimensions based on location information analysis road；Vehicle operating parameters acquisition module leads to
Cross CAN line read engine speed, error code, by sensor acquire turning angle of steering wheel, throttle valve angle, indicating brake action,
Tire pressure and temperature these parameters；Driver parameter's acquisition unit, including image collecting device and identification module, for identification
Driver fatigue state and driver's mood；Information procession and communication module, including information processing and storage unit and information
Communication module reduces the data traffic of communication module and server background communication for processing and cache information.
3. the road hazard cargo transport dynamic risk early warning system according to claim 2 based on technology of Internet of things,
It is characterized in that, the vehicle waybill module out includes vehicle basic information module, driver's basic information module, goods information module
And routing information module；Wherein, vehicle basic information module mainly inputs the industrial grade of vehicle, annual test qualification situation, vehicle
Annual test parameter, lights of vehicle annual test parameter are braked, vehicle annual test safety devices are equipped with as a result, vehicle appearance testing result, it is proposed that
Safeguard item, comprehensive oil consumption；Driver's basic information module mainly inputs the violation information of driver, accident information, personality information
With driving age information；Goods information module inputs title, the classification of cargo, international code, combustion heat value, emergency measure information；Line
Road information module inputs beginning and end, transportation route and fence, each road section speed limit information.
4. the road hazard cargo transport dynamic risk early warning system according to claim 3 based on technology of Internet of things,
It is characterized in that, the Risk-warning process are as follows: according to vehicle position information, geographical parsing information, onboard sensor information and CAN
The vehicle operating information that line is read, after acquisition parameter is processed as requested, is sent to server background by communication module, after
Platform parses geographical environmental information according to location information, in conjunction with the input information of waybill, in risk in transit accident probability and consequence number
The quantized value that different parameters corresponding accident probability and damage sequence is transferred according to library is transported by risk assessment database model logic
It calculates, calculates the risk in transit of collection process, and the accumulative risk in transit for obtaining entire transportational process or the risk in transit in certain section；
The risk in transit for certain transportation route that risk evaluation module assessment is set according to waybill module, and judge whether to be more than that risk can connect
It is spent, if it exceeds being issued warning signal to risk warning module；Wherein, accident probability and category of roads, road linearity parameter,
Road track number, road construction object, weather, temperature, speed, the volume of traffic, road speed limit are related；In damage sequence radius of vulnerability with
Goods information is related, population exposed amount and the volume of traffic, densely populated place area quantity, and surrounding car quantity and traffic composition are related；
Risk in transit is offset related to driver safety, technology state of vehicle and enterprise security manager level joint.
5. the road hazard cargo transport dynamic risk early warning system according to claim 4 based on technology of Internet of things,
It is characterized in that, the safety of the driver is evaluated according to following information parameter, vehicle operating parameters: engine speed, direction
Disk steering angle, throttle valve angle, indicating brake action sensor information, driver status information: driver fatigue state and driver
Driving mood, driver's essential information: violation information, accident information, personality information and the driving age information of driver, driving behavior
Multidate information: transportational process hypervelocity, time-out and not press link travel；Technology state of vehicle is according to following information evaluation, engine
Failure, tyre temperature and air pressure, vehicle essential information: industrial grade, annual test qualification situation, the vehicle braking annual test ginseng of vehicle
Number, lights of vehicle annual test parameter, vehicle annual test safety devices are equipped with result, vehicle appearance testing result, suggest maintenance item, comprehensive
Fuel consumption information；Enterprise security manager level is evaluated according to driver safety and technology state of vehicle evaluation result.
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| CN110335441A (en) * | 2019-07-30 | 2019-10-15 | 江苏驭道数据科技有限公司 | A kind of road transport vehicle drive behaviorist risk dynamic estimation system |
| CN110428517A (en) * | 2019-07-30 | 2019-11-08 | 江苏驭道数据科技有限公司 | A kind of vehicle transport security management system towards extensive road transport vehicle |
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