ROAD SAFETY DATA UK

Overview
The strategic road network (SRN) is a vital national asset, supporting economic growth, regional development, and employment opportunities across England and the rest of the UK. It connects families, communities and businesses, enriching the lives of many citizens. Billions of miles are traveled on the SRN each year. The vast majority of these are safe and reliable journeys.
Table of Contents
Every death or serious injury on our roads is a tragedy. Improving safety on the roads reduces physical, mental and emotional harm to individuals. A safer network also improves journey time reliability, providing economic benefits.
The road safety data provide details about the circumstances of personal injury road accidents in GB from 1979, the types of vehicles involved and the consequential casualties. The statistics relate only to personal injury accidents on public roads that are reported to the police, and subsequently recorded, using the STATS19 accident reporting form.
STATS19 is a code designating the protocol which outlines information to be collected whenever an injury crash is reported to the Police. This code is also frequently used to refer to Britain’s official Road Accident Statistics, which are derived from Police STATS19 returns and compiled by the Department for Transport.
STATS19 information is of great value to road safety practitioners, but cannot be made public in its entirety for reasons of personal confidentiality. However, information derived from analysis of STATS19 data forms the basis for the annual publication of Road Casualties Great Britain, and is also a key component of the data analysis.
Predicting traffic accidents is a crucial problem to improving transportation and public safety as well as safe routing. The problem is also challenging due to the rareness of accidents in space and time and spatial heterogeneity of the environment (e.g., urban vs. rural)
Our system consists of three parts in which we first cluster Casualty incidents in an interactive data map to highlight some hotspots and then narratively dive into accident attributes to uncover potentially related factors about the Accident.
- Accident
- Vehicle
- Casualty
Insights from the data: By this we could explore and analyze accidents on various combination of features such as
- Analyze by collision factors (location, junctions, weather, lighting conditions)
- Analyse by casualty factors (class, severity, sex & type)
- Analyze by time factors (time of day, day of week)
- Analyze by road factors (type, class, surface condition, speed limit)
- Analyze by vehicle involvement (vehicle type, towing, maneuver)
- Cross-compare vehicle, casualty and collision factors.
Accident Data
In Road Safety, an Accident is an incident occurring on the public highway which involved at least one vehicle. Any accident which resulted in human death or personal injury (an injury crash), and which has been notified to the Police.
Road traffic accidents (RTA) is a big issue to our society due to it being among the main causes of traffic congestion, human death, health problems, environmental pollution, and economic losses. Facing these fatal and unexpected traffic accidents, understanding what happened and discovering factors that relate to them and then making alarms in advance play critical roles for possibly effective traffic management and reduction of accidents.
Because an injury crash may result in more than one casualty, the total numbers of crashes and casualties cannot be expected to be the same. Great care should be taken to distinguish between numbers of incidents which occurred (crashes) and the number of people injured as a result (casualties).
The severity of a crash is defined as the highest severity of injury suffered by any resultant casualty. Consequently, it is meaningful to refer to a slight casualty which was suffered as a result of a serious crash, but not vice versa.
Data linkage and it’s description
The RSD_ACCIDENT_DETAILS contains the information on accidents. It contains all kinds of various attributes about the whole accident.
The Accident_Index is a unique value for each accident. The accident_index combines the accident_year and accident_ref_no to form a unique ID. It can be used to join Vehicle and Casualty tables.
The severity of an Accident is defined as the highest severity of injury suffered by any resultant casualty. Consequently, it is meaningful to refer to a slight casualty which was suffered as a result of a serious crash, but not vice versa.
Accident Severity can be shown as a separate table based on , Vehicles or Casualties. It should not be confused with Casualty Severity, which is shown only in reports based on Casualties.
The Longitude and Latitude data is based on WGS 1984. All the Accident attributes have lookup tables related to them which refers to the meaning of each field.
SQLDBM data modeling and visualization

Accident Look up tables
- ACCIDENT_ADJUSTMENT
- ACCIDENT_CARRIAGEWAY_HAZARDS
- ACCIDENT_DAY_OF_WEEK
- ACCIDENT_DID_POLICE_OFFICER_ATTEND_SCENE_OF_ACCIDENT
- ACCIDENT_FIRST_ROAD_CLASS
- ACCIDENT_FIRST_ROAD_NUMBER
- ACCIDENT_JUNCTION_CONTROL
- ACCIDENT_JUNCTION_DETAIL
- ACCIDENT_LIGHT_CONDITIONS
- ACCIDENT_LOCAL_AUTHORITY_DISTRICT
- ACCIDENT_LOCAL_AUTHORITY_HIGHWAY
- ACCIDENT_LOCAL_AUTHORITY_ONS_DISTRICT
- ACCIDENT_PEDESTRIAN_CROSSING_HUMAN_CONTROL
- ACCIDENT_PEDESTRIAN_CROSSING_PHYSICAL_FACILITIES
- ACCIDENT_POLICE_FORCE
- ACCIDENT_ROAD_SURFACE_CONDITIONS
- ACCIDENT_ROAD_TYPE
- ACCIDENT_SECOND_ROAD_CLASS
- ACCIDENT_SECOND_ROAD_NUMBER
- ACCIDENT_SEVERITY
- ACCIDENT_SPECIAL_CONDITIONS_AT_SITE
- ACCIDENT_SPEED_LIMIT
- ACCIDENT_TRUNK_ROAD_FLAG
- ACCIDENT_URBAN_OR_RURAL_AREA
- ACCIDENT_WEATHER_CONDITIONS
RSD_ACCIDENT_DETAILS
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
ACCIDENT_SEVERITY | NUMBER | REFERS TO THE SEVERITY CLASS OF ACCIDENT |
FIRST_ROAD_CLASS | NUMBER | REFERS TO THE FIRST ROAD CLASS ON WHICH ACCIDENT TOOK PLACE |
LOCAL_AUTHORITY_DISTRICT | NUMBER | LOOKS UP THE LOCAL AUTHORITY DISTRICT AT WHICH ACCIDENT TOOK PLACE |
NUMBER_OF_CASUALTIES | NUMBER | NUMBER OF CASUALTIES INVOLVED IN ACCIDENT |
SECOND_ROAD_CLASS | NUMBER | REFERS TO THE SECOND ROAD CLASS ON WHICH ACCIDENT TOOK PLACE |
JUNCTION_CONTROL | NUMBER | REFERS TO THE JUNCTION CONTROL AT WHICH ACCIDENT TOOK PLACE |
POLICE_FORCE | NUMBER | LOOKS UP THE POLICE FORCE AT WHICH ACCIDENT TOOK PLACE |
ACCIDENT_TIME | TIMESTAMP_NTZ | TIME AT WHICH ACCIDENT TOOK PLACE |
URBAN_OR_RURAL_AREA | NUMBER | REFERS TO THE TYPE OF AREA WHERE THE ACCIDENT TOOK PLACE |
ACCIDENT_DATE | TIMESTAMP_NTZ | DATE ON WHICH ACCIDENT TOOK PLACE |
ACCIDENT_YEAR | NUMBER | YEAR ON WHICH ACCIDENT TOOK PLACE |
DAY_OF_WEEK | NUMBER | DAY OF WEEK ON WHICH ACCIDENT TOOK PLACE |
LIGHT_CONDITIONS | NUMBER | LIGHT CONDITIONS OF THE SCENE WHILE ACCIDENT TOOK PLACE |
ROAD_SURFACE_CONDITIONS | NUMBER | ROAD SURFACE CONDITIONS OF THE SCENE WHILE ACCIDENT TOOK PLACE |
SPEED_LIMIT | NUMBER | SPEED LIMIT OF ROAD ON WHICH ACCIDENT TOOK PLACE |
VALIDATION_STATUS | TEXT | TELLS IF THE DATA IS VALIDATED BY SRN |
NUMBER_OF_VEHICLES | NUMBER | NUMBER OF VEHICLE INVOLVED IN THE ACCIDENT |
PEDESTRIAN_CROSSING_HUMAN_CONTROL | NUMBER | CATEGORY OF PEDESTRIAN CROSSING HUMAN CONTROL |
WEATHER_CONDITIONS | NUMBER | WEATHER CONDITIONS WHILE ACCIDENT TOOK PLACE |
SECOND_ROAD_NUMBER | TEXT | REFERS TO THE SECOND ROAD NUMBER ON WHICH ACCIDENT TOOK PLACE |
LOCAL_AUTHORITY_HIGHWAY | TEXT | LOOKS UP THE LOCAL AUTHORITY HIGHWAY AT WHICH ACCIDENT TOOK PLACE |
JUNCTION_DETAIL | NUMBER | DESCRIBES THE JUNCTION AT WHICH ACCIDENT OCCURRED |
ACCIDENT_REFERENCE | TEXT | UNIQUE VALUE FOR EACH ACCIDENT. THE ACCIDENT_INDEX COMBINES THE ACCIDENT_YEAR AND ACCIDENT_REF_NO TO FORM A UNIQUE ID. IT CAN BE USED TO JOIN TO VEHICLE AND CASUALTY |
LATITUDE | TEXT | LATITUDE OF LOCATION AT WHICH ACCIDENT TOOK PLACE |
SPECIAL_CONDITIONS_AT_SITE | NUMBER | DESCRIBES THE SPECIAL CONDITIONS IF ANY AT WHICH ACCIDENT OCCURRED |
LOCATION_NORTHING_OSGR | TEXT | LOCATION NORTHING ON ORDNANCE SURVEY NATIONAL GRID |
PEDESTRIAN_CROSSING_PHYSICAL_FACILITIES | TEXT | DESCRIBES THE PEDESTRIAN CROSSING PHYSICAL FACILITIES AT WHICH ACCIDENT THE ACCIDENT OCCURED |
TRUNK_ROAD_FLAG | NUMBER | CHECKS IF THE ACCIDENT OCCURRED IS ON TRUNK ROAD |
CARRIAGEWAY_HAZARDS | NUMBER | DETAILS ON THE CARRIAGEWAY HAZARDS CAUSED BY ACCIDENT |
DID_POLICE_OFFICER_ATTEND_SCENE_OF_ACCIDENT | NUMBER | CHECKS IF THE POLICE OFFICER ATTEND SCENE OF ACCIDENT |
FIRST_ROAD_NUMBER | NUMBER | REFERS TO THE FIRST ROAD NUMBER ON WHICH ACCIDENT TOOK PLACE |
LOCATION_EASTING_OSGR | TEXT | LOCATION EASTING ON ORDNANCE SURVEY NATIONAL GRID |
LONGITUDE | TEXT | LONGITUDE OF LOCATION AT WHICH ACCIDENT TOOK PLACE |
LSOA_OF_ACCIDENT_LOCATION | TEXT | ONS LOCATION OF ENGLAND AND WALES ONLY. |
ACCIDENT_INDEX | TEXT | UNIQUE VALUE FOR EACH ACCIDENT |
LOCAL_AUTHORITY_ONS_DISTRICT | TEXT | LOOKS UP THE LOCAL AUTHORITY DISTRICT AT WHICH ACCIDENT TOOK PLACE(ONS DATA ) |
ROAD_TYPE | NUMBER | REFERS TO THE ROAD TYPE ON WHICH ACCIDENT TOOK PLACE |
Sample SQL Query on Accident data
Usage
Example 1
How many total accidents happened in the year 2015 at a Roundabout
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SELECT COUNT(ACCIDENT_INDEX) AS NUMBER_OF_ACCIDENTS FROM RSD_ACCIDENT_DETAILS RAD INNER JOIN ACCIDENT_ROAD_TYPE ART ON RAD.ROAD_TYPE=ART.ACCIDENT_ROAD_TYPE_CODE WHERE RAD.ACCIDENT_YEAR = '2015' AND ART.ACCIDENT_ROAD_TYPE_VALUE='ROUNDABOUT' |
Example 2
Count total number of severity for each category in the year 2019
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SELECT ACCIDENT_SEVERITY, COUNT(ACCIDENT_SEVERITY) AS SEVERITY_COUNT FROM RSD_ACCIDENT_DETAILS WHERE ACCIDENT_YEAR = '2019' GROUP BY ACCIDENT_SEVERITY |
Vehicle Accident Data
The term vehicle refers to any means of transport involved in a crash, whether powered by engine, pedal or animal.
In STATS19 reporting, any record relating to an attended vehicle includes the Vehicle Type, and details of the driver or rider who was in control of it at the time of the crash. It is also related to details of any passenger in that vehicle who was a casualty of the crash, and any pedestrian who became a casualty as a result of collision with it.
It doesn’t include roller skates, prams, children riding toys on the footpath and other similar items. The term does cover all other means of transport, including motorcycles, pedal cycles, mopeds, ridden horses, animal drawn carts, self propelled invalid carriages, tractors, trams, quad bikes, tanks, and street barrows.
A driver is a person who was in control of a vehicle at the moment when it became involved in a crash. In STATS19 data, vehicles include those which are pedal or animal powered. Consequently this term generally includes riders of pedal cycles and horses, as well as motorcycle riders.
Because information about drivers and riders is stored as part of a vehicle record, reports which relate to them typically use the Vehicles Measure. Drivers who suffered an injury as a result of a crash are also separately recorded as casualties, distinguished from other casualties by the Driver casualty class.
People who are in, on, or in the act of alighting from a vehicle at the time of a crash, but are not in control of it, are considered to be passengers rather than drivers. A pedestrian using roller skates or similar, and children in prams or riding toys on the footpath, are also not considered to be drivers.
STATS19 returns include information about drivers in the vehicle records associated with each crash. This includes Gender, Age and Postcode data. The driver postcode recorded by STATS19 is used to derive the location where drivers reside, as shown in the Driver Home dimension.
The RSD_VEHICLES_DETAILS contains the information on all the vehicles involved in the accident. It contains all kinds of various attributes linking from the vehicle’s direction to details about the vehicle.The ACCIDENT_INDEX is further divided into various VEHICLE_REFERENCE numbers to identify each vehicle involved in the accident uniquely. This VEHICLE_REFERENCE is appended with the accident index to form the VEHICLE_ACCIDENT_INDEX which serves as the primary key for this table. All the vehicle attributes have lookup tables related to them which refers to the meaning of each field.
Data linkage and it’s description
SQLDBM data modeling and visualization
Vehicle data Look up tables
- VEHICLE_AGE_BAND_OF_DRIVER
- VEHICLE_AGE_OF_DRIVER
- VEHICLE_DRIVER_HOME_AREA_TYPE
- VEHICLE_DRIVER_IMD_DECILE
- VEHICLE_ENGINE_CAPACITY_CC
- VEHICLE_FIRST_POINT_OF_IMPACT
- VEHICLE_GENERIC_MAKE_MODEL
- VEHICLE_HIT_OBJECT_IN_CARRIAGEWAY
- VEHICLE_HIT_OBJECT_OFF_CARRIAGEWAY
- VEHICLE_JOURNEY_PURPOSE_OF_DRIVER
- VEHICLE_JUNCTION_LOCATION
- VEHICLE_PROPULSION_CODE
- VEHICLE_SEX_OF_DRIVER
- VEHICLE_SKIDDING_AND_OVERTURNING
- VEHICLE_TOWING_AND_ARTICULATION
- VEHICLE_VEHICLE_DIRECTION_FROM
- VEHICLE_VEHICLE_DIRECTION_TO
- VEHICLE_VEHICLE_LEAVING_CARRIAGEWAY
- VEHICLE_VEHICLE_LEFT_HAND_DRIVE
- VEHICLE_VEHICLE_LOCATION_RESTRICTED_LANE
- VEHICLE_VEHICLE_MANOEUVRE
- VEHICLE_VEHICLE_TYPE
RSD_VEHICLE_DETAILS
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
AGE_OF_DRIVER | NUMBER | AGE OF THE DRIVER IN NUMBER |
JOURNEY_PURPOSE_OF_DRIVER | NUMBER | JOURNEY PURPOSE OF DRIVER |
VEHICLE_REFERENCE | NUMBER | REFERENCE FOR VEHICLE UNDER AN ACCIDENT |
AGE_BAND_OF_DRIVER | NUMBER | FEATURE ENGINEERED VARIABLE TO FIND THE AGE CATEGORY OF DRIVER |
TOWING_AND_ARTICULATION | NUMBER | DESCRIBES IF THE VEHICLE CARRAIAGE / TRAILER ETC |
VALIDATION_STATUS | TEXT | TELLS IF THE DATA IS VALIDATED BY SRN |
VEHICLE_LEAVING_CARRIAGEWAY | NUMBER | HOW AND WHERE ERRANT VEHICLES TRAVEL AFTER LEAVING THE CARRIAGEWAY |
VEHICLE_LOCATION_RESTRICTED_LANE | NUMBER | VEHICLE LOCATION IN RESTRICTED LANE |
VEHICLE_DIRECTION_FROM | NUMBER | REFERS TO THE DIRECTION FROM WHICH THE VEHICLE IS FROM |
GENERIC_MAKE_MODEL | TEXT | MAKE MODEL OF THE VEHICLE |
JUNCTION_LOCATION | NUMBER | REFERS ABOUT WHICH LOCATION CORRESPONDING TO THE JUNCTION |
SKIDDING_AND_OVERTURNING | NUMBER | REFERS TO THE SKIDDING AND OVERTURNING CHARACTERISTICS OF VEHICLE |
VEHICLE_LEFT_HAND_DRIVE | NUMBER | REFERS OF THE VEHICLE IS LEFT HAND DRIVE |
VEHICLE_TYPE | NUMBER | SPECIFIES THE NATURE OF EACH VEHICLE INVOLVED IN A CRASH. |
PROPULSION_CODE | NUMBER | FUEL ON WHICH VEHICLE OPERATES |
VEHICLE_DIRECTION_TO | NUMBER | REFERS THE DIRECTION TO VEHICLE WAS MOVING |
AGE_OF_VEHICLE | NUMBER | AGE OF THE ACCIDENT VEHICLE |
DRIVER_HOME_AREA_TYPE | NUMBER | REFERS TO THE TYPE OF HOME ARES FROM WHICH THE DRIVER IS FROM |
HIT_OBJECT_IN_CARRIAGEWAY | NUMBER | REFERS TO THE HIT OBJECT IN ON A CARRIAGEWAY |
SEX_OF_DRIVER | NUMBER | SEX OF THE DRIVER |
ACCIDENT_INDEX | TEXT | UNIQUE VALUE FOR EACH ACCIDENT |
ENGINE_CAPACITY_CC | NUMBER | ENGINE CAPACITY OF THE VEHICLE IN LITERS |
VEHICLE_ACCIDENT_INDEX | TEXT | UNIQUE REFERENCE FOR A VEHICLE UNDER A ACCIDENT_INDEX |
FIRST_POINT_OF_IMPACT | NUMBER | FIRST POINT OF IMPACT ON THE VEHICLE |
HIT_OBJECT_OFF_CARRIAGEWAY | NUMBER | REFERS TO THE HIT OBJECT OFF IN A CARRIAGEWAY |
DRIVER_IMD_DECILE | NUMBER | AN INDEX OF MULTIPLE DEPRIVATION (IMD) IS USED TO IDENTIFY HOW DEPRIVED AN AREA IS. IT USES A RANGE OF ECONOMIC, SOCIAL AND HOUSING DATA TO CREATE A SINGLE DEPRIVATION SCORE FOR EACH SMALL AREA OF THE COUNTRY. |
VEHICLE_MANOEUVRE | NUMBER | INDICATES THE ACTIONS TAKEN BY A VEHICLE IMMEDIATELY BEFORE IT BECAME INVOLVED IN A CRASH. |
Sample SQL Queries
Usage
Example 1
What are the vehicle types and number of accidents happened for each category
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SELECT VEHICLE_VEHICLE_TYPE_VALUE, COUNT(VEHICLE_TYPE) FROM RSD_VEHICLE_DETAILS VD INNER JOIN VEHICLE_VEHICLE_TYPE VT ON VD.VEHICLE_TYPE = VT.VEHICLE_VEHICLE_TYPE_CODE GROUP BY VEHICLE_VEHICLE_TYPE_VALUE |
Casualty Accident Data
Changes to the ways in which collisions are recorded by some police forces has increased the number of serious injuries identified. This makes interpreting recent trends less certain. The recording of fatalities is unaffected. The number of fatalities in 2019 was 210, two fifths lower than the 2005-2009 baseline. However, since 2012, the overall trend in fatalities has been fairly flat, ranging between 210 and 250 per year, with the highest in this period being in 2018. Apart from the difference in reporting for the most recent years, there are wider factors affecting the number of casualties on the SRN. People are traveling further, there are more vehicles on the road and a wider mix of vehicle types. Road casualty figures can vary from year to year because of things like a single collision/multiple casualty incident or external factors such as the weather. There are many factors that affect safety on our network, including vehicle safety and improvements to our roads. We are committed to reducing all categories of casualties on the network. This will require a targeted approach with investments informed by evidence.
Reporting of road casualty data
CRASH is the DfT’s collision and reporting and sharing system. It allows police officers to capture and upload collision data from the roadside in real time. Since it was introduced gradually in 2012, there has been an increase in recorded serious casualties in Great Britain. This system has introduced changes in how the severity of an incident is recorded and provides a more consistent basis to classify and report the level of injury severity.
However, the change has meant that in some instances injuries previously classified as slight are now classified as serious. By 2019, the system was being used by 21 of the 38 police forces which cover the SRN. These represent approximately 55% of the network. In addition, there were similar severity reporting changes for the Metropolitan Police who adopted the case overview preparation application (COPA) system.
However, the number of collisions on the SRN are low compared to those on local authority or Transport for London roads. The DfT commissioned the Office for National Statistics (ONS), to estimate adjustment factors for historic KSI data. This enables the production of consistent numbers over a time period which are independent of the reporting method being used. The work is complete and the methodology paper Estimating and adjusting for changes in the method of severity reporting for road accidents and casualty data: final report was published in July 2019.
It is complemented by the Annex: Update to severity adjustment methodology which was published in September 2019. The DfT is inviting users to adopt the methodology and to provide feedback on it and the way in which the statistics are being used, including any challenges faced. The model is likely to be updated annually and as experienced in 2019, there may be a resulting uplift in the adjusted serious injuries. This is at least in part due to new forces joining CRASH in 2019 and not having a full year of CRASH data.
Data linkage and it’s description
The RSD_CASUALITY_DETAILS contains the information on accidents. It contains all kinds of various attributes about the Casualty.Note should be taken care that One accident might have more than one casualty and this could be identified uniquely by looking into the CASUALTY_REFERENCE under the same ACCIDENT_INDEX.
This CASUALTY_REFERENCE is appended with the ACCIDENT_INDEX to form the CASUALTY_ACCIDENT_INDEX which serves as the primary key for this table. All the vehicle attributes have lookup tables related to them which refers to the meaning of each field.
Since STATS19 permits to contain an estimated age, the age information may not always be exactly accurate.
- An value of ninety-nine reported in STATS19 indicates that age data for an individual is missing or unknown, and is not used for persons aged 99 years
- An age of ninety-eight years reported in STATS19 refers to any person aged 98 years or older at the time of the crash
- An value of zero reported in STATS19 refers to a person aged less than 12 months old, and is not used for unknown ages
- Children unborn at the time of a crash are not included
The levels of the Age hierarchy are defined as follows:
- Child refers to any person aged under 16
- Child_Preschool refers to any child aged 4 years or under
- Child_School refers to any child aged between 5 and 15 years (inclusive)
- The upper age band within this level covers a six year age range, including children aged between 10 and 15 years (inclusive)
- Adult refers to any person aged 16 or over
- Adult_Young refers to any adult aged between 16 and 24 years (inclusive)
- The lower age band within this level covers a four year age range, including young adults aged between 16 and 19 years (inclusive)
- Adult_Mid refers to any adult aged between 25 and 64 years (inclusive)
- Adult_Senior refers to any adult aged 65 years or over
- The upper age band within this level includes all persons aged 85 years or over
- The upper age band at the level below this includes all persons aged 90 years or over
SQLDBM data modeling and visualization
Casualty data Look up tables
- CASUALTY_ADJUSTMENT
- CASUALTY_AGE_BAND_OF_CASUALTY
- CASUALTY_AGE_OF_CASUALTY
- CASUALTY_BUS_OR_COACH_PASSENGER
- CASUALTY_CAR_PASSENGER
- CASUALTY_CASUALTY_CLASS
- CASUALTY_CASUALTY_HOME_AREA_TYPE
- CASUALTY_CASUALTY_IMD_DECILE
- CASUALTY_CASUALTY_SEVERITY
- CASUALTY_CASUALTY_TYPE
- CASUALTY_PEDESTRIAN_LOCATION
- CASUALTY_PEDESTRIAN_MOVEMENT
- CASUALTY_PEDESTRIAN_ROAD_MAINTENANCE_WORKER
- CASUALTY_SEX_OF_CASUALTY
RSD_CASUALTY_DETAILS
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
SEX_OF_CASUALTY | NUMBER | REFERS TO THE SEX OF CASUALTY |
VEHICLE_ACCIDENT_INDEX | TEXT | UNIQUE REFERENCE FOR A VEHICLE UNDER A ACCIDENT_INDEX |
BUS_OR_COACH_PASSENGER | NUMBER | REFERS IF THE CASUALTY IS A BUS OR COACH PASSENGER |
CASUALTY_IMD_DECILE | NUMBER | DEPRIVATION SCORES OF INDIVIDUAL AREAS INTO ONE OF TEN GROUPS OF EQUAL FREQUENCY |
AGE_OF_CASUALTY | NUMBER | REFERS TO THE AGE OF CASUALTY |
PEDESTRIAN_ROAD_MAINTENANCE_WORKER | NUMBER | REFERS IF THE CASUALTY BELONGS TO THE CATEGORY IF THE PEDESTRIAN IS A ROAD MAINTENANCE WORKER |
CAR_PASSENGER | NUMBER | REFERS IF THE CASUALTY IS A CAR PASSENGER |
CASUALTY_CLASS | NUMBER | REFERS TO THE CLASS OF CASUALTY SUCH AS PEDESTRIAN OR DRIVER ETC |
CASUALTY_HOME_AREA_TYPE | NUMBER | REFERS TO THE TYPE OF HOME ARES FROM WHICH THE CASUALTY IS FROM |
CASUALTY_REFERENCE | NUMBER | REFERS TO THE CASUALTY UNDER A ACCIDENT |
VALIDATION_STATUS | TEXT | TELLS IF THE DATA IS VALIDATED BY SRN |
CASUALTY_SEVERITY | NUMBER | REFERS TO THE SEVERITY CLASS OF CASUALTY |
AGE_BAND_OF_CASUALTY | NUMBER | REFERS TO THE AGE BAND OF CASUALTY |
PEDESTRIAN_LOCATION | NUMBER | PEDESTRIAN LOCATION WHILE THE ACCIDENT TOOK PLACE |
VEHICLE_REFERENCE | NUMBER | REFERS TO THE VEHICLE UNDER A ACCIDENT |
ACCIDENT_INDEX | TEXT | UNIQUE VALUE FOR EACH ACCIDENT |
CASUALTY_ACCIDENT_INDEX | TEXT | UNIQUE REFERENCE FOR A CASUALTY UNDER A ACCIDENT_INDEX |
CASUALTY_TYPE | NUMBER | REFERS TO WHICH CASUALTY TYPE CATEGORY THE CASUALTY IS ASSOCIATED |
PEDESTRIAN_MOVEMENT | NUMBER | PEDESTRIAN MOVEMENT WHILE THE ACCIDENT TOOK PLACE |
Sample SQL Queries
Usage
Example 1
What are the casualty class and number of accidents happened for each class
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SELECT CASUALTY_CASUALTY_CLASS_VALUE, COUNT(CASUALTY_CASUALTY_CLASS_CODE) FROM RSD_CASUALTY_DETAILS CD INNER JOIN CASUALTY_CASUALTY_CLASS CC ON CD.CASUALTY_CLASS = CC.CASUALTY_CASUALTY_CLASS_CODE GROUP BY CASUALTY_CASUALTY_CLASS_VALUE |
ACCIDENT AND CASUALTY ADJUSTMENT DATA
We have record-level severity adjustment data on the road safety data.gov website alongside the 2019 annual report to facilitate severity adjustment analyses. At both casualty and accident level, these look-ups contain the model probabilities for them being serious or slight under injury-based reporting systems (IBRS) since 2004, i.e. as if all forces were using injury-based reporting systems. The look ups contain adjustments for all non-fatal casualties and accidents. Fatal casualties and accidents are excluded as they are not given an adjustment probability. Accident_adjustment and casualty_adjustment can be linked back to the main accident and casualty datasets respectively and aggregated to produce adjusted totals. The accident values can be derived from the casualty look-up.
NOTE : 2004 adjustments were calculated using variables collected from an older STATS19 specification. There are differences in the way variables were recorded and categorized in 2004. Therefore, 2004 adjustment figures are indicative, and it is recommended to use adjustment figures from 2005 onwards only.
The accident and casualty adjustment probabilities provided can be linked to the available yearly data extracts using the “Accident_Index” variable (as well as “Vehicle_Reference” and “Casualty_Reference” for the casualty dataset). To get the adjusted slight or serious totals for an aggregate, the values in the appropriate column need to be summed (“Adjusted_Serious” or “Adjusted_Slight”). A flag for whether the casualty or accident was originally recorded on an injury based reporting system (“Injury_Based”) has also been included.
Data linkage and it’s description
SQLDBM data modeling and visualization

Adjustment data Look up tables
- ACCIDENT_ADJUSTMENT
- CASUALTY_ADJUSTMENT
ACCIDENT ADJUSTMENT_DETAILS
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
ADJUSTED_SERIOUS | FLOAT | ADJUSTED SERIOUSNESS PROBABILITY OF THE ACCIDENT |
ACCIDENT_INDEX | TEXT | UNIQUE VALUE FOR EACH ACCIDENT. |
ADJUSTED_SLIGHT | FLOAT | ADJUSTED SLIGHTNESS PROBABILITY OF THE ACCIDENT |
INJURY_BASED | NUMBER | A FLAG FOR WHETHER THE CASUALTY OR ACCIDENT WAS ORIGINALLY RECORDED ON AN INJURY BASED REPORTING SYSTEM |
CASUALTY ADJUSTMENT_DETAILS
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
VEHICLE_REFERENCE | NUMBER | REFERS TO THE VEHICLE UNDER A ACCIDENT |
ADJUSTED_SLIGHT | FLOAT | ADJUSTED SLIGHTNESS PROBABILITY OF THE CAUSALITY |
CASUALTY_ACCIDENT_INDEX | TEXT | UNIQUE REFERENCE FOR A CASUALTY UNDER A ACCIDENT_INDEX |
INJURY_BASED | NUMBER | A FLAG FOR WHETHER THE CASUALTY OR ACCIDENT WAS ORIGINALLY RECORDED ON AN INJURY BASED REPORTING SYSTEM |
ACCIDENT_INDEX | TEXT | UNIQUE VALUE FOR EACH ACCIDENT. |
ADJUSTED_SERIOUS | FLOAT | ADJUSTED SERIOUSNESS PROBABILITY OF THE CAUSALITY |
CASUALTY_REFERENCE | NUMBER | REFERS TO THE CASUALTY UNDER A ACCIDENT |
VEHICLE_ACCIDENT_INDEX | TEXT | UNIQUE REFERENCE FOR A VEHICLE UNDER A ACCIDENT_INDEX |
Sample SQL Queries
Usage
Example 1(Accident Adjustment)
What is the total number of serious accidents happened in 2020 with a seriousness above 0.8 ?
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SELECT COUNT(*) FROM ACCIDENT_ADJUSTMENT AA INNER JOIN RSD_ACCIDENT_DETAILS RAD ON AA.ACCIDENT_INDEX = RAD.ACCIDENT_INDEX WHERE RAD.ACCIDENT_YEAR=2020 AND AA.ADJUSTED_SERIOUS >0.8 |
Example 2(Casualty Adjustment)
What is the total number of casualties with minimal injuries below 0.3 slightness in 2019 ?
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SELECT COUNT(*) FROM CASUALTY_ADJUSTMENT CA INNER JOIN RSD_CASUALTY_DETAILS RCD ON CA.CASUALTY_ACCIDENT_INDEX =RCD.CASUALTY_ACCIDENT_INDEX INNER JOIN RSD_ACCIDENT_DETAILS RAD ON RCD.ACCIDENT_INDEX = RAD.ACCIDENT_INDEX WHERE RAD.ACCIDENT_YEAR=2019 AND CA.ADJUSTED_SLIGHT < 0.3 |
Road Traffic Statistics
What traffic data is available?
All the datasets have been produced using the methods described in the guidance notes. We have the following categories of data
Road level Annual Average Daily Flow (AADF) estimates
- AADF Data by direction
- AADF Data
Raw manual counts data collected by our trained enumerators
- Raw count data
Summary road traffic estimates
- Local authority level traffic estimates
- Regional traffic estimates by vehicle type
- Regional traffic estimates by road type
Major roads model geography
- Major road network – shape file format
Contents of Datasets
Estimated Annual average daily flows (AADFs) by direction
An AADF is the average over a full year of the number of vehicles passing a point in the road network each day. The file has the same structure to the major roads AADF file with the additional column ‘Direction_of_travel’. Different directions can be summed up to give a total combined flow. However, for methodological reasons, the AADFs for different count points should not be added together.
The “AADF data by direction” file contains the following variables
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
ALL_HGVS | NUMBER | AADF FOR ALL HGVS. |
COUNT_POINT_ID | TEXT | A UNIQUE REFERENCE FOR THE ROAD LINK THAT LINKS THE AADFS TO THE ROAD NETWORK |
HGVS_3_OR_4_ARTICULATED_AXLE | NUMBER | AADF FOR THREE OR FOUR-ARTICULATED AXLE HGVS |
HGVS_3_RIGID_AXLE | NUMBER | AADF FOR THREE-RIGID AXLE HGVS. |
HGVS_5_ARTICULATED_AXLE | NUMBER | AADF FOR FIVE-ARTICULATED AXLE HGVS. |
LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN KILOMETERS). |
LGVS | NUMBER | AADF FOR LGVS. |
ALL_MOTOR_VEHICLES | NUMBER | AADF FOR ALL MOTOR VEHICLES |
DIRECTION_OF_TRAVEL | TEXT | DIRECTION OF TRAVEL. |
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER |
LONGITUDE | FLOAT | LONGITUDE OF THE CP LOCATION. |
START_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE START JUNCTION OF THE LINK |
EASTING | NUMBER | EASTING COORDINATES OF THE CP LOCATION. |
PEDAL_CYCLES | NUMBER | AADF FOR PEDAL CYCLES. |
ROAD_TYPE | TEXT | WHETHER THE ROAD IS A ‘MAJOR’ OR ‘MINOR’ ROAD. |
ID | TEXT | PRIMAR KEY |
ESTIMATION_METHOD | TEXT | THE METHOD USED TO ESTIMATE THE AADF, FOR EACH CP AND YEAR. |
HGVS_2_RIGID_AXLE | NUMBER | AADF FOR TWO-RIGID AXLE HGVS. |
LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN MILES). |
ROAD_NAME | TEXT | THIS IS THE ROAD NAME (FOR INSTANCE M25 OR A3). |
CARS_AND_TAXIS | NUMBER | AADF FOR CARS AND TAXIS. |
HGVS_4_OR_MORE_RIGID_AXLE | NUMBER | AADF FOR FOUR OR MORE RIGID AXLE HGVS. |
LATITUDE | FLOAT | LATITUDE OF THE CP LOCATION. |
NORTHING | NUMBER | NORTHING COORDINATES OF THE CP LOCATION. |
TWO_WHEELED_MOTOR_VEHICLES | NUMBER | AADF FOR TWO-WHEELED MOTOR VEHICLES. |
HGVS_6_ARTICULATED_AXLE | NUMBER | AADF FOR SIX-ARTICULATED AXLE HGVS. |
SEQUENCE | NUMBER | |
BUSES_AND_COACHES | NUMBER | AADF FOR BUSES AND COACHES |
ESTIMATION_METHOD_DETAILED | TEXT | THE DETAILED METHOD USED TO ESTIMATE THE AADF |
LOCAL_AUTHORITY_ID | NUMBER | WEBSITE LOCAL AUTHORITY IDENTIFIER. |
YEAR | NUMBER | AADFS ARE SHOWN FOR EACH YEAR FROM 2000 ONWARDS. |
END_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE END JUNCTION OF THE LINK |
ROAD_CATEGORY | TEXT | THE CLASSIFICATION OF THE ROAD TYPE. |
RAMP | NUMBER | RAMP IS PRESENT OR NOT |
Estimated Annual average daily flows (AADFs)
An AADF is the average over a full year of the number of vehicles passing a point in the road network each day. For methodological reasons, the AADFs for different count points should not be added together.
The ‘AADF data’ file contains the following variables
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
LOCAL_AUTHORITY_ID | NUMBER | WEBSITE LOCAL AUTHORITY IDENTIFIER. |
YEAR | NUMBER | AADFS ARE SHOWN FOR EACH YEAR FROM 2000 ONWARDS. |
ROAD_NAME | TEXT | THIS IS THE ROAD NAME (FOR INSTANCE M25 OR A3). |
ALL_HGVS | NUMBER | AADF FOR ALL HGVS. |
EASTING | NUMBER | EASTING COORDINATES OF THE CP LOCATION. |
HGVS_3_OR_4_ARTICULATED_AXLE | NUMBER | AADF FOR THREE OR FOUR-ARTICULATED AXLE HGVS. |
LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN MILES). |
LONGITUDE | FLOAT | LONGITUDE OF THE CP LOCATION. |
START_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE START JUNCTION OF THE LINK |
TWO_WHEELED_MOTOR_VEHICLES | NUMBER | AADF FOR TWO-WHEELED MOTOR VEHICLES. |
CARS_AND_TAXIS | NUMBER | AADF FOR CARS AND TAXIS. |
END_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE END JUNCTION OF THE LINK |
ESTIMATION_METHOD | TEXT | THE METHOD USED TO ESTIMATE THE AADF, FOR EACH CP AND YEAR. |
HGVS_5_ARTICULATED_AXLE | NUMBER | AADF FOR FIVE-ARTICULATED AXLE HGVS. |
NORTHING | NUMBER | NORTHING COORDINATES OF THE CP LOCATION. |
PEDAL_CYCLES | NUMBER | AADF FOR PEDAL CYCLES. |
RAMP | NUMBER | RAMP IS PRESENT OR NOT |
ROAD_CATEGORY | TEXT | THE CLASSIFICATION OF THE ROAD TYPE. |
SEQUENCE | NUMBER | |
COUNT_POINT_ID | NUMBER | A UNIQUE REFERENCE FOR THE ROAD LINK THAT LINKS THE AADFS TO THE ROAD NETWORK. |
ESTIMATION_METHOD_DETAILED | TEXT | THE DETAILED METHOD USED TO ESTIMATE THE AADF. |
HGVS_2_RIGID_AXLE | NUMBER | AADF FOR TWO-RIGID AXLE HGVS. |
HGVS_4_OR_MORE_RIGID_AXLE | NUMBER | AADF FOR FOUR OR MORE RIGID AXLE HGVS. |
LATITUDE | FLOAT | LATITUDE OF THE CP LOCATION. |
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER |
ROAD_TYPE | TEXT | WHETHER THE ROAD IS A ‘MAJOR’ OR ‘MINOR’ ROAD. |
HGVS_3_RIGID_AXLE | NUMBER | AADF FOR THREE-RIGID AXLE HGVS |
HGVS_6_ARTICULATED_AXLE | NUMBER | AADF FOR SIX-ARTICULATED AXLE HGVS. |
ID | TEXT | PRIMAR KEY |
LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN KILOMETERS). |
BUSES_AND_COACHES | NUMBER | AADF FOR BUSES AND COACHES |
ALL_MOTOR_VEHICLES | NUMBER | AADF FOR ALL MOTOR VEHICLES. |
LGVS | NUMBER | AADF FOR LGVS. |
Raw manual counts data
Raw manual counts dataset is the actual data collected by trained enumerators to feed into road traffic estimates.
The ‘Raw_Count’ file contains the following variables
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
BUSES_AND_COACHES | NUMBER | COUNTS FOR BUSES AND COACHES |
HGVS_3_OR_4_ARTICULATED_AXLE | NUMBER | COUNTS FOR THREE OR FOUR-ARTICULATED AXLE HGVS. |
YEAR | NUMBER | COUNTS ARE SHOWN FOR EACH YEAR FROM 2000 ONWARDS. |
LONGITUDE | FLOAT | LONGITUDE OF THE CP LOCATION. |
COUNT_DATE | TIMESTAMP_NTZ | THE DATE WHEN THE ACTUAL COUNT TOOK PLACE. |
HGVS_6_ARTICULATED_AXLE | NUMBER | COUNTS FOR SIX-ARTICULATED AXLE HGVS. |
ROAD_TYPE | TEXT | WHETHER THE ROAD IS A ‘MAJOR’ OR ‘MINOR’ ROAD. |
HOUR | NUMBER | THE TIME WHEN THE COUNTS IN QUESTIONS TOOK PLACE WHERE 7 REPRESENTS BETWEEN 7AM AND 8AM, AND 17 REPRESENTS BETWEEN 5PM AND 6PM. |
RAMP | NUMBER | RAMP IS PRESENT OR NOT |
HGVS_2_RIGID_AXLE | NUMBER | COUNTS FOR TWO-RIGID AXLE HGVS. |
LGVS | NUMBER | COUNTS FOR LGVS |
LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN KILOMETERS). |
LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT CP (IN MILES). |
PEDAL_CYCLES | NUMBER | COUNTS FOR PEDAL CYCLES. |
SEQUENCE | NUMBER | |
END_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE END JUNCTION OF THE LINK |
HGVS_3_RIGID_AXLE | NUMBER | COUNTS FOR THREE-RIGID AXLE HGVS. |
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER. |
ROAD_NAME | TEXT | THIS IS THE ROAD NAME (FOR INSTANCE M25 OR A3). |
COUNT_POINT_ID | NUMBER | A UNIQUE REFERENCE FOR THE ROAD LINK THAT LINKS THE AADFS TO THE ROAD NETWORK. |
DIRECTION_OF_TRAVEL | TEXT | DIRECTION OF TRAVEL. |
START_JUNCTION_ROAD_NAME | TEXT | THE ROAD NAME OF THE START JUNCTION OF THE LINK |
EASTING | NUMBER | EASTING COORDINATES OF THE CP LOCATION. |
HGVS_4_OR_MORE_RIGID_AXLE | NUMBER | COUNTS FOR FOUR OR MORE RIGID AXLE HGVS. |
LOCAL_AUTHORITY_ID | NUMBER | WEBSITE LOCAL AUTHORITY IDENTIFIER. |
ALL_HGVS | NUMBER | COUNTS FOR ALL HGVS. |
ALL_MOTOR_VEHICLES | NUMBER | COUNTS FOR ALL MOTOR VEHICLES. |
LATITUDE | FLOAT | LATITUDE OF THE CP LOCATION. |
TWO_WHEELED_MOTOR_VEHICLES | NUMBER | COUNTS FOR TWO-WHEELED MOTOR VEHICLES. |
ROAD_CATEGORY | TEXT | THE CLASSIFICATION OF THE ROAD TYPE . |
CARS_AND_TAXIS | NUMBER | COUNTS FOR CARS AND TAXIS. |
HGVS_5_ARTICULATED_AXLE | NUMBER | COUNTS FOR FIVE-ARTICULATED AXLE HGVS. |
NORTHING | NUMBER | NORTHING COORDINATES OF THE CP LOCATION. |
ID | NUMBER | PRIMAR KEY |
Local authority road traffic estimates
Traffic estimates provide the summary statistics on the distance traveled by vehicles on Great Britain’s roads.
The ‘local authority traffic’ file contains the following variables:
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
ALL_MOTOR_VEHICLES | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR ALL MOTOR VEHICLES IN THE GIVEN LOCAL AUTHORITY |
LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT LOCAL AUTHORITY (IN MILES). |
LOCAL_AUTHORITY_NAME | TEXT | THE NAME OF THE LOCAL AUTHORITY. |
LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE ROAD NETWORK ROAD LINK FOR THAT LOCAL AUTHORITY (IN KILOMETERS). |
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER |
CARS_AND_TAXIS | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR CARS AND TAXIS IN THE GIVEN REGION AND ROAD CATEGORY. |
ID | NUMBER | IPRIMAR KEY |
LOCAL_AUTHORITY_ID | NUMBER | WEBSITE LOCAL AUTHORITY IDENTIFIER. |
ONS_CODE | TEXT | THE OFFICE FOR NATIONAL STATISTICS CODE IDENTIFIER FOR THE LOCAL AUTHORITY. |
YEAR | NUMBER | TRAFFIC ESTIMATES ARE SHOWN FOR EACH YEAR FROM 1993 ONWARDS. |
Regional traffic estimates by vehicle type
Traffic estimates provides the summary statistics on the distance traveled by vehicles on Great Britain’s roads
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
BUSES_AND_COACHES | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR BUSES AND COACHES IN THE GIVEN REGION AND ROAD CATEGORY. |
ID | NUMBER | PRIMAR KEY |
TOTAL_LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE ROAD NETWORK ROAD LINK FOR THAT REGION (IN KILOMETERS). |
YEAR | NUMBER | TRAFFIC ESTIMATES ARE SHOWN FOR EACH YEAR FROM 1993 ONWARDS. |
ALL_MOTOR_VEHICLES | NUMBER | ANNUAL ROAD TRAFFIC ESTIMATE FOR ALL MOTOR VEHICLES IN THE GIVEN REGION AND ROAD CATEGORY. |
ONS_CODE | TEXT | THE OFFICE FOR NATIONAL STATISTICS CODE IDENTIFIER FOR THE REGION. |
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER |
LGVS | NUMBER | ANNUAL ROAD TRAFFIC ESTIMATE FOR LGVS IN THE GIVEN REGION AND ROAD CATEGORY. |
TWO_WHEELED_MOTOR_VEHICLES | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR TWO-WHEELED MOTOR VEHICLES IN THE GIVEN REGION AND ROAD CATEGORY. |
TOTAL_LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT REGION (IN MILES). |
ALL_HGVS | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR ALL HGVS IN THE GIVEN REGION AND ROAD CATEGORY. |
CARS_AND_TAXIS | NUMBER | ANNUAL ROAD TRAFFIC ESTIMATE FOR CARS AND TAXIS IN THE GIVEN REGION AND ROAD CATEGORY. |
PEDAL_CYCLES | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR PEDAL CYCLES IN THE GIVEN REGION AND ROAD CATEGORY. |
Regional traffic estimates by road type
Traffic estimates provides the summary statistics on the distance traveled by vehicles on Great Britain’s roads
COLUMN_NAME | DATA_TYPE | DESCRIPTION |
---|---|---|
REGION_ID | NUMBER | WEBSITE REGION IDENTIFIER |
TOTAL_LINK_LENGTH_MILES | FLOAT | TOTAL LENGTH OF THE NETWORK ROAD LINK FOR THAT REGION (IN MILES). |
YEAR | NUMBER | TRAFFIC ESTIMATES ARE SHOWN FOR EACH YEAR FROM 1993 ONWARDS. |
ROAD_CATEGORY_ID | NUMBER | THE CLASSIFICATION OF THE ROAD TYPE (SEE DATA DEFINITIONS FOR THE FULL LIST). |
TOTAL_LINK_LENGTH_KM | FLOAT | TOTAL LENGTH OF THE ROAD NETWORK ROAD LINK FOR THAT REGION (IN KILOMETERS). |
ALL_MOTOR_VEHICLES | FLOAT | ANNUAL ROAD TRAFFIC ESTIMATE FOR ALL MOTOR VEHICLES IN THE GIVEN REGION AND ROAD CATEGORY |
ID | NUMBER | PRIMAR KEY |
ONS_CODE | TEXT | THE OFFICE FOR NATIONAL STATISTICS CODE IDENTIFIER FOR THE REGION. |
Road types
Category | Category Description |
---|---|
PM | M or Class A Principal Motorway |
PA | Class A Principal road |
TM | M or Class A Trunk Motorway |
TA | Class A Trunk road |
M | Minor road |
MB | Class B road |
MCU | Class C road or Unclassified road |
Direction of flow
Category | Category Description |
---|---|
N | North |
S | South |
E | East |
W | West |
C | Combined (flows separated by the direction of travel unavailable) |
Types of vehicle
Category | Category Description |
---|---|
All_MV | All Motor Vehicles |
2WMV | Two-wheeled motor vehicles (e.g. motorcycles etc) |
Car | Cars and Taxis |
LGV | Light Goods Vans |
HGV | Heavy Goods Vehicle total |
HGVR2 | 2-rigid axle Heavy Goods Vehicle |
HGVR3 | 3-rigid axle Heavy Goods Vehicle |
HGVR4 | 4 or more rigid axle Heavy Goods Vehicle |
HGVA3 | 3 and 4-articulated axle Heavy Goods Vehicle |
HGVA5 | 5-articulated axle Heavy Goods Vehicle |
HGVA6 | 6 or more articulated axle Heavy Goods Vehicle |
PC | Pedal Cycles |
Appendix
Traffic figures at the regional and national level are robust, and are reported as National Statistics. However, DfT’s traffic estimates for individual road links and small areas are less robust, as they are not always based on up-to-date counts made at these locations. Where other more up-to-date sources of traffic data are available (e.g. from local highways authorities), this may provide a more accurate estimate of traffic at these locations.