CN114298518A - Road risk evaluation index system under networked vehicle environment - Google Patents
Road risk evaluation index system under networked vehicle environment Download PDFInfo
- Publication number
- CN114298518A CN114298518A CN202111582446.6A CN202111582446A CN114298518A CN 114298518 A CN114298518 A CN 114298518A CN 202111582446 A CN202111582446 A CN 202111582446A CN 114298518 A CN114298518 A CN 114298518A
- Authority
- CN
- China
- Prior art keywords
- indexes
- road
- index
- vehicle
- risk
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 23
- 230000003068 static effect Effects 0.000 claims abstract description 4
- 238000004891 communication Methods 0.000 claims description 10
- 230000006855 networking Effects 0.000 claims description 8
- 238000013480 data collection Methods 0.000 claims description 4
- 238000000034 method Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 4
- 241001465754 Metazoa Species 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 230000001133 acceleration Effects 0.000 claims description 2
- 238000009825 accumulation Methods 0.000 claims description 2
- 239000000110 cooling liquid Substances 0.000 claims description 2
- 230000035484 reaction time Effects 0.000 claims description 2
- 238000012502 risk assessment Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 239000002352 surface water Substances 0.000 claims description 2
- 239000003550 marker Substances 0.000 claims 1
- 238000011161 development Methods 0.000 abstract description 3
- 230000006399 behavior Effects 0.000 description 9
- 238000005516 engineering process Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000003595 mist Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000013077 scoring method Methods 0.000 description 1
Images
Landscapes
- Traffic Control Systems (AREA)
Abstract
The invention discloses a road risk evaluation index system under an internet vehicle environment. Firstly, the index system improves traditional road risk evaluation indexes such as road condition indexes, traffic indexes and meteorological indexes. Secondly, the index system establishes new evaluation indexes such as a driver attribute index, a driving behavior index, a vehicle on-road operation index and an internet connection environment index according to the characteristics of the internet connection vehicles and the data acquisition types of the internet connection vehicles. The index system combines the Internet of vehicles and the cooperation of the vehicle roads, solves the problem that the consideration factors of the road risk evaluation indexes are static, and realizes the development of the road risk evaluation system to the dynamic, microscopic and real-time directions.
Description
Technical Field
The invention relates to the field of intelligent traffic safety, in particular to a road risk evaluation index system in an internet vehicle environment.
Background
Road traffic is closely related to the safety of lives and properties of people, and timely and effective evaluation of road traffic risks has very important significance for formulation of risk response measures. Therefore, it is necessary to establish a comprehensive and effective road risk assessment index system.
In the conventional road risk evaluation index system, all indexes are traditional and static indexes, although the road risk can be quantified to a certain extent, the influence of individual vehicle behaviors and networked vehicles on the road risk is not considered, and actually, the road traffic risk and accidents are mostly caused by bad driving behaviors and misoperation of drivers. In recent years, the development of new technologies promotes the rapid development of intelligent traffic, car networking and vehicle road coordination are gradually improved and are applied to actual traffic, and the types of data which can be obtained not only comprise macroscopic traffic flow, but also comprise data such as driving behaviors, vehicle operation parameters and the like. The application of the new technology provides a new idea for the construction of a road risk evaluation index system.
Disclosure of Invention
Aiming at the existing road risk evaluation index system, the invention establishes a road risk grade evaluation index system under the networked vehicle environment so as to optimize the evaluation index system and solve the problem that the existing evaluation index system is lack of dynamic and behavior indexes.
In order to achieve the above purpose, the technical solution disclosed by the invention is as follows:
a road risk level evaluation index system in an internet vehicle environment comprises two parts, wherein the first part is a continuous use supplementary traditional index system and comprises a road condition index, a traffic condition index and a meteorological condition index. The second part is road risk level evaluation indexes under the networking environment, including driving behavior indexes, driver indexes, vehicle in-transit indexes and networking indexes.
First, the road condition index classification method and criteria include: terrain, road type, alignment, critical road segments and nodes, road surface properties, temporary risk sources.
Further, the topographic condition includes: plain areas, hilly areas, mountain areas; the road types include: highways, urban roads; the line shape includes: a flat curve, a longitudinal curve, a flat longitudinal combination curve; the key segments and nodes include: bridges, tunnels, intersections; the pavement properties include: adhesion coefficient, flatness, damage condition; sources of temporary risk include: surface water accumulation, road construction, animal presence and absence and object throwing.
Further, the road includes: expressways, first-level roads, second-level roads, third-level roads, fourth-level roads and equal-outside roads; the urban road includes: an express way, a main road, a secondary road and a branch; the intersection includes: the control of a signal lamp and the control of no signal lamp are provided.
Second, the traffic condition indicators include: traffic flow, speed difference, specific gravity of large vehicles and special vehicles, and integrity of mark and marking lines.
Thirdly, the meteorological condition indicators include: wind, rain, snow, fog, sunshine.
Further, the wind includes: wind power and wind direction; the rain includes: light rain, medium rain, heavy rain; the snow includes: small snow, medium snow, big snow, snowstorm; the mist includes: light fog (visibility is more than or equal to 1km and less than 10km), fog (visibility is more than or equal to 0.5km and less than 1km), heavy fog (visibility is more than or equal to 0.2km and less than 0.5km), dense fog (visibility is more than or equal to 0.05km and less than 0.2km) and strong dense fog (visibility is less than 0.05 km); the sunshine includes: day, night, dawn, dusk.
Fourth, the driving behavior index includes: longitudinal risk indicators, transverse risk indicators, other risk indicators.
Further, the longitudinal risk indicators include: collision time (TTC > 0), headway; the lateral risk indicators include: the lane changing time (the safety value: 3-10 s) of the vehicle and the acceptable gap of the lane changing; other risk indicators include: the lane change rate of every hundred vehicles (safety value: 0.2), frequent lane change (safety value: < 3 times/min), continuous driving time (safety value: 4 hours), frequent acceleration and deceleration (safety value: < 3 times/min), line pressing driving (safety value: < 10s), lane departure (safety value: < 10s) and steering wheel turning angle.
TABLE 1 lower side turning-over steering wheel corner at different vehicle speeds
| Running speed km/h of vehicle | Steering wheel angle at side turn (°) |
| 40 | 261 |
| 60 | 116 |
| 80 | 65 |
| 100 | 41 |
| 120 | 29 |
Fifth, the driver index includes: age, driver's license state, reaction time (safety value 0.3-1.0 s, danger value > 1.0 s).
Further, the age includes: the driver is young (18-35 years old), middle-aged (36-50 years old) and old (more than 50 years old).
Sixth, the vehicle in-transit indicator includes: the closed state of the vehicle door, the temperature of cooling liquid, the tire pressure, the wheel hub, the brake hub, the service brake, the steering wheel corner and the side-tipping stable angle.
TABLE 2 vehicle in-transit indicator safety value
Seventh, the networking environment index includes: road side end coverage rate, network connection vehicle proportion, vehicle-road communication mode and vehicle-vehicle communication.
Further, the vehicle-road communication mode includes: one-way communication and two-way communication.
Drawings
FIG. 1 is a flow chart of the use of the index system
FIG. 2 road condition index
FIG. 3 traffic condition index
FIG. 4 weather Condition index
FIG. 5 Driving behavior index
FIG. 6 driver index
FIG. 7 in-transit vehicle index
FIG. 8 Internet environmental indicators
Detailed Description
In order to express the purpose and technical scheme of the present invention in more detail, the following detailed description of the implementation steps of the present invention is provided with reference to the accompanying drawings, and the implementation steps are only used for explaining the present invention in more detail and are not used for limiting the present invention.
The method comprises the following steps: static data collection
And for the target road section, acquiring data according to the specific indexes of the road condition index, the meteorological condition index and the networking environment index.
Step two: dynamic data collection
For vehicles in a target road section, vehicle-mounted end and road side end equipment are utilized to acquire and obtain in-transit vehicle indexes, driver indexes and behavior indexes in real time. The data sampling frequency is 5 s/time, and the data is transmitted to a road side end or a cloud end through a wireless network.
Step three: calculating road risk level
The road risk value R may be calculated by:
R＝∑i∑jbiBij×(∑i∑jriRij+∑i∑jmiMij+∑i∑jtiTij+∑i∑jdiDij +∑i∑jciCij+∑i∑jniNij)
in the formula:
Bij: a driving behavior index weight.
Rij: road condition index weight.
Mij: weather condition indicator weight.
Tij: traffic condition index weight.
Dij: driver index weight.
Cij: an in-transit vehicle index weight.
Nij: and networking environment index weight.
bi、ri、mi、ti、di、ci、niAnd determining the category weight by an expert scoring method, wherein the value range of i is the number of the categories of the monitoring indexes under each condition, and the value range of j is the number of the indexes under each monitoring index.
When the method is used, experts can be scored according to local conditions so as to calibrate each index in an evaluation system. The calibration steps are as follows: the first level index system is scored and normalized,
for example, a middle-aged driver (0.2) with a normal (0.0) driving license continuously drives a vehicle (0.0) with a normal state for 5 hours (0.6) in the daytime (0.1) and runs in a straight line section of an expressway (0.4) of a mountain road section (0.5), the lane change rate of the vehicle in the road section is 0.3(0.8), the road surface is smooth, animals are occasionally shown and absent, the road section is in traffic flow (0.5), speed difference (0.2), mark and line rationality (0.1), 4-level wind power (0.4) and cross wind direction (0.7). Calculating the R value from formula one as: 0.461. the greater the value, the higher the risk level, and the greater the severity of the accident.
Claims (9)
1. A road risk evaluation index system under the environment of networked vehicles comprises road condition indexes, traffic condition indexes and meteorological condition indexes;
the road risk level evaluation method is characterized by further comprising road risk level evaluation indexes in the internet environment, wherein the road risk level evaluation indexes comprise driving behavior indexes, driver indexes, vehicle in-transit indexes and internet indexes.
2. The system of road risk assessment indexes in the networked vehicle environment of claim 1, wherein the road condition indexes include key road section and node indexes, temporary risk source indexes and general indexes; the vertical combination type index is newly increased in the linear index in the general indexes; the pavement performance indexes are added with flatness and damage conditions; the newly added temporary risk sources comprise the road construction of surface water accumulation, the animal submergence and the object throwing.
3. The system of claim 1, wherein the traffic condition indicator is additionally provided with a marker marking integrity indicator.
4. The system of claim 1, wherein the new wind direction indicators include downwind, upwind and crosswind; two indexes of dusk and dawn are added in the sunshine index.
5. The system of claim 1, wherein the driving behavior index comprises a longitudinal risk index, a transverse risk index and other risk indexes; the longitudinal risk indexes comprise collision time and headway; the transverse risk indexes comprise lane change time of the vehicle and acceptable gaps; other risk indexes comprise lane change rate of more than 0.25 per hundred vehicles, frequent lane change of more than 3 times/min, driving time of more than 4 hours, frequent acceleration and deceleration of more than 3 times/min, line-pressing driving of more than 10s and lane deviation of more than 10 s.
6. The system according to claim 1, wherein the driver index comprises: age, driver's license state, reaction time safety value 0.3 ~ 1.0s, dangerous value: > 1.0 s.
7. The system of claim 1, wherein the system comprises: the closed state of the vehicle door, the temperature of cooling liquid, the tire pressure, the wheel hub, the brake hub, the service brake, the steering wheel corner and the side-tipping stable angle.
8. The vehicle in-transit index is characterized by comprising: road side end coverage rate, network connection vehicle proportion, vehicle-road communication mode and vehicle-vehicle communication; the vehicle-road communication mode comprises one-way communication and two-way communication.
9. The application of the road risk evaluation index system in the networked vehicle environment according to claim 1 is characterized by comprising the following steps:
the method comprises the following steps: static data collection
For a target road section, acquiring data according to specific indexes of road condition indexes, meteorological condition indexes and networking environment indexes;
step two: dynamic data collection
For vehicles in a target road section, acquiring and acquiring in-transit vehicle indexes, driver indexes and behavior indexes thereof in real time by utilizing vehicle-mounted end and road side end equipment; the data sampling frequency is 5 s/time, and the data are transmitted to a road side end or a cloud end through a wireless network;
step three: calculating road risk level
The road risk value R may be calculated by:
in the formula:
Bij: a driving behavior index weight;
Rij: road condition index weight;
Mij: weather condition index weight;
Tij: a traffic condition index weight;
Dij: driver index weight;
Cij: an in-transit vehicle index weight;
Nij: networking environment index weight;
bi、ri、mi、ti、di、ci、nithe category weight is monitored, wherein the value range of i is the number of the categories of the monitoring indexes under each condition, and the value range of j is the number of the indexes under each monitoring index.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111582446.6A CN114298518A (en) | 2021-12-22 | 2021-12-22 | Road risk evaluation index system under networked vehicle environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111582446.6A CN114298518A (en) | 2021-12-22 | 2021-12-22 | Road risk evaluation index system under networked vehicle environment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114298518A true CN114298518A (en) | 2022-04-08 |
Family
ID=80969319
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111582446.6A Pending CN114298518A (en) | 2021-12-22 | 2021-12-22 | Road risk evaluation index system under networked vehicle environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114298518A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115223360A (en) * | 2022-06-10 | 2022-10-21 | 长安大学 | Early warning system and method for expressway construction area |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106228499A (en) * | 2016-07-06 | 2016-12-14 | 东南大学 | A kind of cargo security evaluation model based on people's bus or train route goods multi-risk System source |
| CN107618512A (en) * | 2017-08-23 | 2018-01-23 | 清华大学 | Driving behavior safe evaluation method based on people's car environment multi-data source |
| CN108830488A (en) * | 2018-06-21 | 2018-11-16 | 重庆大学 | A kind of road area risk assessment method |
| CN110390451A (en) * | 2018-04-18 | 2019-10-29 | 网帅科技（北京）有限公司 | A kind of road traffic safety risk profile pre-warning indexes system |
| CN110414803A (en) * | 2019-07-08 | 2019-11-05 | 清华大学 | The assessment method and device of automated driving system level of intelligence under different net connection degree |
| CN112037513A (en) * | 2020-09-01 | 2020-12-04 | 清华大学 | Real-time traffic safety index dynamic comprehensive evaluation system and construction method thereof |
| CN112201038A (en) * | 2020-09-28 | 2021-01-08 | 同济大学 | Road network risk assessment method based on risk of bad driving behavior of single vehicle |
| CN113762734A (en) * | 2021-08-17 | 2021-12-07 | 淮阴工学院 | Dangerous chemical vehicle highway driving risk assessment method and system |
| CN113781788A (en) * | 2021-11-15 | 2021-12-10 | 长沙理工大学 | Automatic driving vehicle management method based on stability and safety |
| CN117809458A (en) * | 2024-03-01 | 2024-04-02 | 山东大学 | Real-time assessment method and system for traffic accident risk |
-
2021
- 2021-12-22 CN CN202111582446.6A patent/CN114298518A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106228499A (en) * | 2016-07-06 | 2016-12-14 | 东南大学 | A kind of cargo security evaluation model based on people's bus or train route goods multi-risk System source |
| CN107618512A (en) * | 2017-08-23 | 2018-01-23 | 清华大学 | Driving behavior safe evaluation method based on people's car environment multi-data source |
| CN110390451A (en) * | 2018-04-18 | 2019-10-29 | 网帅科技（北京）有限公司 | A kind of road traffic safety risk profile pre-warning indexes system |
| CN108830488A (en) * | 2018-06-21 | 2018-11-16 | 重庆大学 | A kind of road area risk assessment method |
| CN110414803A (en) * | 2019-07-08 | 2019-11-05 | 清华大学 | The assessment method and device of automated driving system level of intelligence under different net connection degree |
| CN112037513A (en) * | 2020-09-01 | 2020-12-04 | 清华大学 | Real-time traffic safety index dynamic comprehensive evaluation system and construction method thereof |
| CN112201038A (en) * | 2020-09-28 | 2021-01-08 | 同济大学 | Road network risk assessment method based on risk of bad driving behavior of single vehicle |
| CN113762734A (en) * | 2021-08-17 | 2021-12-07 | 淮阴工学院 | Dangerous chemical vehicle highway driving risk assessment method and system |
| CN113781788A (en) * | 2021-11-15 | 2021-12-10 | 长沙理工大学 | Automatic driving vehicle management method based on stability and safety |
| CN117809458A (en) * | 2024-03-01 | 2024-04-02 | 山东大学 | Real-time assessment method and system for traffic accident risk |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115223360A (en) * | 2022-06-10 | 2022-10-21 | 长安大学 | Early warning system and method for expressway construction area |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107742432B (en) | Expressway operation speed active early warning system based on vehicle-road cooperation and control method | |
| CN105584485B (en) | It is estimated using participatory sensing system to improve road friction | |
| CN104978853B (en) | A kind of traffic safety appraisal procedure and system | |
| CN208256095U (en) | A kind of highway real-time traffic flow monitoring and shunt induction intelligent and safe management system | |
| CN103413448B (en) | A kind of mountainous area highway continuous Large Longitudinal Slope section lorry intelligent early-warning system | |
| CN207517194U (en) | Highway operating speed active forewarning system based on bus or train route collaboration | |
| CN111383465B (en) | Highway danger early warning and speed control system based on car networking | |
| CN109872554A (en) | A kind of expressway fog zone promotes the bus or train route early warning system of traffic safety | |
| CN113723699B (en) | Method and system for warning correction handle control of expressway safety vehicle speed in severe weather | |
| CN111477005B (en) | Intelligent perception early warning method and system based on vehicle state and driving environment | |
| CN108648490B (en) | Method for testing speed limit information response capability of automatic driving automobile | |
| CN106683453B (en) | A kind of Forewarning System of Freeway | |
| CN212541604U (en) | Highway disaster weather self-adaptation intelligent early warning real-time speed limiting system | |
| CN109389845A (en) | A kind of multifactor integration high speed highway dynamic vehicle speed managing and control system | |
| CN114298518A (en) | Road risk evaluation index system under networked vehicle environment | |
| CN117238139B (en) | Real-time road condition early warning system based on meteorological data | |
| CN108874843B (en) | Method, device and equipment for displaying traffic weather comprehensive information | |
| EP2172377A1 (en) | Assymetrical structures; method for processing collected data to extract road status information | |
| CN202887458U (en) | Highway vehicle speed guidance system | |
| Hassan et al. | Operating speed of vehicles during rainfall at night: Case study in Pontian, Johor | |
| CN104749656A (en) | Real-time highway monitoring system under severe weather condition | |
| CN204288519U (en) | A kind of integrated self-adaptive intelligent traffic warning board | |
| CN114360270B (en) | Method and system for studying and judging maximum allowable speed of highway under adverse weather influence | |
| Thordarson et al. | Weather induced road accidents, winter maintenance and user information | |
| Buddemeyer et al. | Rural variable speed limit system for southeast Wyoming |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |