This dynamic map service provodes a a linear representation of speed limit changes based on signs in the field or speed zones established by an Official Order.

Speed limit information for most of Queensland's roads. Includes state and locally controlled roads. Point-in-time data as per date of collection in dataset.

It contains the full detail layer of the extents for certified speed limit records from 26 May 2022 onwards, and their associated attribute data.Previously, 68 different road controlling authorities (RCAs) published this information in multiple formats.You can use the data for:time-based analysisanalysis against other datasets, for example addressesbuilding additional datasets.The data is extracted from the NSLR on a nightly basis.New emergency speed limits are updated in this dataset shortly after being created in the NSLR.Note: speed limit record geometries (shapefiles) will overlap. This will be in addition to overpasses, underpasses, intersections, bus lanes, opposing speed differences and multiple speeds in the same direction. For example, if you have an overpass one speed limit will be given for the top level (bridge) and the second overlapping geometry for the bottom level (I.e. road under bridge).Permanent speed limit: A speed limit that’s in force except when a seasonal, variable, temporary - emergency or other temporary speed limit is in force.Variable speed limit: A speed limit that changes under certain conditions (excluding seasonal), for example due to the presence of a school where the speed limit is different at certain times of the day depending on the school activity.Seasonal speed limit: A speed limit that applies on a seasonal basis, for example during a holiday period. Seasonal speed limits can be one-off or recurring.Emergency speed limit: A speed limit put in place due to an emergency, for example an earthquake, tsunami or epidemic.The principles for how the speed limits interact with each other are as follows.Permanent and variable speed limits cannot overlap one another.A seasonal speed limit can overlap permanent and variable speed limits.A seasonal speed limit can overlap another seasonal speed limit, as long as the speed limit is not active at the same time as the record it is overlapping (i.e.one seasonal speed limit cannot overlap another seasonal speed limit).An emergency record can overlap a seasonal record but cannot overlap another emergency record.Temporary speed limits, other than emergency, are not included in this dataset.Members of the public can search for speed limits on New Zealand roads, obtain details of specific speed limits and obtain certified copies of speed limits through the NSLR web application. NSLR web browser applicationData reuse caveatsAs per license.Data quality statementRCAs signed off that the data in the NSLR is a true and accurate reflection of their bylaw. There is a high level of confidence in data quality, and we welcome user feedback.Data quality caveatsThe data has been migrated as provided by respective RCAs according to their current bylaw. There are errors as a result of having to migrate the legal speed limits as per the bylaw rather than what is signed on the ground. Many (but not all) of these were identified and RCAs can apply for Director’s approval to fix them.There is two known issues with the display of this data in Open Data, these are display issues within the Open Data application and do not impact the data when downloaded or used via API:Where there is no date 'December 31, 1969' is shown.Where there is no text 'null' is shown

This map provides information on speed limits that are posted on state-maintained roadways in Virginia. Cities and towns set their own speed limits and these are not available to show on the map. Zoom in on the map to display the speed limits. Speed limits exist for all roads however; where this information is not available for mapping, they are not displayed. Most roads where speed limits are not shown are either rural, secondary roads (routes numbered 600 or greater) where a statutory 55 mph speed limit typically applies, or subdivision streets where a statutory 25 mph speed limit usually applies. These statutory speed limits are often are not posted on these roads. Click on any roadway to display the speed limit information.

Esri ArcGIS Online (AGOL) Hosted, View Feature Layer which provides access to the MDOT SHA Roadway Posted Speed Limit Signs data product.MDOT SHA Roadway Posted Speed Limit Signs data consists of point geometric features which represent the geographic locations of posted speed limit signs along MDOT SHA-maintained roadways throughout the State of Maryland. This layer is a hosted, view layer showing only Posted Speed Limit signage from the comprehensive MDOT SHA Roadway Sign Inventory. Roadway signs that share a sign support structure will be represented as stacked geometry.MDOT SHA Roadway Sign Inventory data is owned by the MDOT SHA Office of Traffic & Safety (OOTS). This data is currently updated on an annual basis. This is the latest version of the data, which was last updated in November 2019 (11/04/2019).MDOT SHA Roadway Sign Inventory data is published on ArcGIS Online for Maryland as a publicly available Hosted Feature Layer with Non-Restricted Access. Download / Export of the data is available in a variety of formats.For additional information, contact MDOT SHA OIT Enterprise Information Services:GIS@mdot.maryland.gov

Roadway Posted Speed Limit Signs data consists of point feature geometry which represents the geographic location of posted speed limit signs along public roadways in the State of Maryland. PLEASE NOTE: This layer is now deprecated as of September, 2020 and will be removed in September 2021.Data has been replaced with the following https://maryland.maps.arcgis.com/home/item.html?id=7549d74e31df427a82a64ab5a19d74e3#overviewRoadway Posted Speed Limit Signs data is developed as part of the Highway Performance Monitoring System (HPMS) which maintains and reports transportation related information to the Federal Highway Administration (FHWA) on an annual basis. HPMS is maintained by the Maryland Department of Transportation State Highway Administration (MDOT SHA), under the Office of Planning and Preliminary Engineering (OPPE) Data Services Division (DSD). This data is used by various business units throughout MDOT, as well as many other Federal, State and local government agencies. Roadway Posted Speed Limit Signs data is key to understanding the location of posted speed limit signs throughout the State of Maryland. Roadway Posted Speed Limit Signs data is updated and published on an annual basis for the prior year. This data is for the year 2017.For additional information, contact the MDOT SHA Geospatial Technologies Email: GIS@mdot.state.md.us For additional information related to the Maryland Department of Transportation (MDOT) Website: https://www.mdot.maryland.gov/ For additional information related to the Maryland Department of Transportation State Highway Administration (MDOT SHA) Website: https://roads.maryland.gov/Home.aspx Data Legal Disclaimer: The Maryland Department of Transportation State Highway Administration (MDOT SHA) makes no warranty, expressed or implied, as to the use or appropriateness of geospatial data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in geospatial data is from publicly available sources, but no representation is made as to the accuracy or completeness of geospatial data. MDOT SHA shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. MDOT SHA shall not be liable for any lost profits, consequential damages, or claims against MDOT SHA by third parties.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Link:https://geodata.md.gov/imap/rest/services/Transportation/MD_RoadwayPostedSpeedLimits/FeatureServer/0

This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. For a more detailed description, go to: http://bit.ly/Q9AZAD.

The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (nonfreeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every ten minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimate by traffic segments gives the observed speed typically for one-half mile of a street in one direction of traffic.

Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). This dataset contains the current estimated speed for about 1250 segments covering 300 miles of arterial roads. There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.

The map layers in this service provide color-coded maps of the traffic conditions you can expect for the present time (the default). The map shows present traffic as a blend of live and typical information. Live speeds are used wherever available and are established from real-time sensor readings. Typical speeds come from a record of average speeds, which are collected over several weeks within the last year or so. Layers also show current incident locations where available. By changing the map time, the service can also provide past and future conditions. Live readings from sensors are saved for 12 hours, so setting the map time back within 12 hours allows you to see a actual recorded traffic speeds, supplemented with typical averages by default. You can choose to turn off the average speeds and see only the recorded live traffic speeds for any time within the 12-hour window. Predictive traffic conditions are shown for any time in the future.The color-coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation, and field operations. A color-coded traffic map can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes.The map also includes dynamic traffic incidents showing the location of accidents, construction, closures, and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis.Data sourceEsri’s typical speed records and live and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. The real-time and predictive traffic data is updated every five minutes through traffic feeds.Data coverageThe service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. Look at the coverage map to learn whether a country currently supports traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, visit the directions and routing documentation and the ArcGIS Help.SymbologyTraffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%To view live traffic only—that is, excluding typical traffic conditions—enable the Live Traffic layer and disable the Traffic layer. (You can find these layers under World/Traffic > [region] > [region] Traffic). To view more comprehensive traffic information that includes live and typical conditions, disable the Live Traffic layer and enable the Traffic layer.

Statewide Road Network including sealed and unsealed roads. The dataset represents navigable roads, including public and private access roads and tracks. A separate data layer stores 'unformed' DCDB centrelines which do not represent navigable roads. A limited number of associated features are stored separately as point features. Automatically updated when changes occur.

The main dataset is a 304 MB file of trajectory data (I90_94_stationary_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) vehicles and non-automated vehicles on a highway in an urban environment. Supporting files include aerial reference images for six distinct data collection “Runs” (I90_94_Stationary_Run_X_ref_image.png, where X equals 1, 2, 3, 4, 5, and 6). Associated centerline files are also provided for each “Run” (I-90-stationary-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see “TGSIM – Centerline Data Dictionary – I90_94Stationary.csv” for more details). The dataset defines six northbound lanes using these centerline files. Twelve different numerical IDs are used to define the six northbound lanes (1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, and 15) depending on the run. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled “Annotation on Regions.zip”. Lane IDs are provided in the reference images in red text for each data collection run (I90_94_Stationary_Run_X_ref_image_annotated.jpg, where X equals 1, 2, 3, 4, 5, and 6).

This dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using the fixed location aerial videography approach with one high-resolution 8K camera mounted on a helicopter hovering over a short segment of I-94 focusing on the merge and diverge points in Chicago, IL. The altitude of the helicopter (approximately 213 meters) enabled the camera to capture 1.3 km of highway driving and a major weaving section in each direction (where I-90 and I-94 diverge in the northbound direction and merge in the southbound direction). The segment has two off-ramps and two on-ramps in the northbound direction. All roads have 88 kph (55 mph) speed limits. The camera captured footage during the evening rush hour (4:00 PM-6:00 PM CT) on a cloudy day. During this period, two SAE Level 2 ADAS-equipped vehicles drove through the segment, entering the northbound direction upstream of the target section, exiting the target section on the right through I-94, and attempting to perform a total of three lane-changing maneuvers (if safe to do so). These vehicles are indicated in the dataset.

As part of this dataset, the following files were provided:

• I90_94_stationary_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.
• I90_94_Stationary_Run_X_ref_image.png are the aerial reference images that define the geographic region for each run X.
• I-90-stationary-Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. The "x" and "y" columns represent the horizontal and ve

The ORN is a provincewide geographic database of over 250,000 kilometres of municipal roads, provincial highways, and resource and recreational roads. The ORN is the authoritative source of roads data for the Government of Ontario. Road names in the ORN are the official names provided by the authoritative jurisdiction for each road segment, such as a municipality or the Ontario Government. The list of authoritative sources used for the ORN is in the “Ontario Road Network - List of Partners” document in the Supporting Files section below. You can also find the authoritative jurisdiction for a specific road feature in the Jurisdiction table in ORN Road Net Element. ORN Road Net Element requires an advanced knowledge of GIS including LRS and complex table relationships. This dataset contains the following related tables: * official street name * alternate street name * address information * road classification * number of lanes * road surface * speed limit * structure * toll point * blocked passage * route name * route number * jurisdiction * source * underpass * junction

The WYSP uses devices called speed display signs or driver feedback signs which contain a radar device and an LED display. These signs are installed against an existing hydro pole or streetlight. The radar measures the speeds of oncoming vehicles and the LED sign displays their speeds to the passing motorists, thereby reminding them to check their speeds and to obey speed limits. The City’s permanent units are installed in Safety Zones. This dataset contains the monthly summary of observed speeds for these signs. See Detailed Speed Counts for hourly speed counts recorded by these signs and Location Data for details on where and when signs were installed.

Web Mapping Application containing all layers from the Office of the State Traffic Administration that enables the user to visually review, search, and query OSTA data, including; State, Local, and School Zone Speed Limits, Major Traffic Generators at defined points within the approval process, No Thru Truck designations, and Parkway Restrictions on height, width, and weight.

The increased usage of navigation technologies has caused conflicts in local traffic management, resulting in congested residential areas among other challenges for residents. This paper uses content analysis to investigate such negative social externalities within local communities and neighbourhoods. Through a corpus of 90 news articles about traffic incidents caused by navigation technologies, we identified negative traffic and safety-related externalities, including congestion, damage, pollution, and accidents. We also report on countermeasures by local communities and governments, including street closures, speed limit reduction, and turn bans. Based on our results, we discuss the implications for designing mobile navigation technologies that reduce negative social externalities.

This Gallup poll seeks to collect the opinions of Canadians on issues of importance to the country. Questions relating to such issues as politics, health, highways and Russia are incuded in this survey. Respondents were also asked questions so that they could be grouped according to geographic, demographic and social variables. Topics of interest include: the Canadian Broadcasting Corporation (CBC); car ownership; cremation; drivers license possesion; exercise and walking; family budget; federal elections; highway speedlimit; hospital costs; St. Laurent's performance as Prime Minister; phone ownership; preferred political parties; Russia's desire to dominate; smoking habits; speed limit; Stalin affecting Russian policy towards to west; television ownershp; Trans-Canada pipeline; union membership; voting behaviour; and world leaders. Basic demographics variables are also included.

This Eurobarometer contains the following main survey focus:

1. General attitudes to political and social questions

2. Attitudes to Europe

3. Use of various means of transport and traffic regulations in Europe

4. Judgement on energy problems

Topics: 1. Political and social attitudes: general prospects for the next year; expected increase or decrease in strikes; prospects for peace; danger of world war (scale); judgement on the general economic situation of the country and of one´s own financial situation; general contentment with life; satisfaction with democracy in the country; personal opinion leadership; frequency of political discussions; contact with representatives in parliament; postmaterialism; frequency of watching news broadcasts on television, reading news in daily newspapers and listening to information broadcasts on the radio; most important areas of interest; national pride; feeling of of being exploited by the powerful and being excluded; government does not concern itself with the ordinary people and the rich become richer; self-assessment on a left-right continuum; attitude to social change; support of nature protection associations, ecology, anti-nuclear power and peace movements; party allegiance; general feeling of happiness; preference for living in the country or in the city.

1. Attitudes to Europe: feeling of being a citizen of Europe; assessment of the development of harmony among the member countries; attitude to unification of Western Europe; interest in problems of the European Community and assessment of their significance; attitude to appearance of the national team under the European and national flag at the Olympic Games; attitude to free selection of place of residence within the EC; attitude to the right to vote in municipal elections for EC citizens; positive or negative impression from the last media publications about the European Parliament; the significance of the role played by the European Parliament at the moment and that it should have in the future; contacts with a member of the European Parliament; attitude to membership of the country in the EC; advantages for the country from membership; areas with particular advantages; regret at a failure of the EC and economic consequences of a withdrawal of the country from the EC.

2. Use of various means of transport and traffic regulations in Europe: frequency of use of motorcycle or motor-assisted bicycle; length of possession of drivers license; most frequently used means of transport; visit to an EC country in the last two years; perceived disturbances from different traffic regulations; frequency of not using seat belts, exceeding speed limits and driving under the influence of alcohol; significance of these offenses as cause of accidents; traffic regulations that should be made uniform Europe-wide and more strongly enforced; attitude to speed limits on freeways; preferred maximum speed limits on freeways, highways and in built-up areas; general attitude to standardization of traffic regulations in the EC; personal involvement in an accident; family members or friends as victim of traffic accidents.

3. Judgement on energy problems: judgement on current and future energy situation as a problem; alternative solutions for future energy problems; most important, most reliable and most environmentally friendly type of energy for the future; judgement on the latest and future development of gasoline prices; industrial facilities with the greatest risk; attitude to research on nuclear energy; attitude to nuclear power (scale); construction of nuclear power plants or reduction of electricity consumption; judgement on the dangers of nuclear power; self-assessment of extent to which informed about the way nuclear power plants work; knowledge about the nuclear power plant accident in the Soviet Union and feeling of personal jeopardy; adequate preparation of German authorities for a nuclear power plant accident; possession of durable economic goods; possession of moped and car; central heating.

Indices: cognitive and political mobility; postmaterialism; typeology of political orientation; EC support.

The following question was posed in the Federal Republic of Germany: associations with the European Community.

The following questions were additionally posed in France, Italy, Spain and Portugal: familiarity of a bicycle tour in Southern Europe; familiarity of the Tour de l´avenir; attitude to financial support of sporting event...

The map layers in this service provide color-coded maps of the traffic conditions you can expect for the present time (the default). The map shows present traffic as a blend of live and typical information. Live speeds are used wherever available and are established from real-time sensor readings. Typical speeds come from a record of average speeds, which are collected over several weeks within the last year or so. Layers also show current incident locations where available. By changing the map time, the service can also provide past and future conditions. Live readings from sensors are saved for 12 hours, so setting the map time back within 12 hours allows you to see a actual recorded traffic speeds, supplemented with typical averages by default. You can choose to turn off the average speeds and see only the recorded live traffic speeds for any time within the 12-hour window. Predictive traffic conditions are shown for any time in the future.The color-coded traffic map layer can be used to represent relative traffic speeds; this is a common type of a map for online services and is used to provide context for routing, navigation, and field operations. A color-coded traffic map can be requested for the current time and any time in the future. A map for a future request might be used for planning purposes.The map also includes dynamic traffic incidents showing the location of accidents, construction, closures, and other issues that could potentially impact the flow of traffic. Traffic incidents are commonly used to provide context for routing, navigation and field operations. Incidents are not features; they cannot be exported and stored for later use or additional analysis.Data sourceEsri’s typical speed records and live and predictive traffic feeds come directly from HERE (www.HERE.com). HERE collects billions of GPS and cell phone probe records per month and, where available, uses sensor and toll-tag data to augment the probe data collected. An advanced algorithm compiles the data and computes accurate speeds. The real-time and predictive traffic data is updated every five minutes through traffic feeds.Data coverageThe service works globally and can be used to visualize traffic speeds and incidents in many countries. Check the service coverage web map to determine availability in your area of interest. Look at the coverage map to learn whether a country currently supports traffic. The support for traffic incidents can be determined by identifying a country. For detailed information on this service, visit the directions and routing documentation and the ArcGIS Help.SymbologyTraffic speeds are displayed as a percentage of free-flow speeds, which is frequently the speed limit or how fast cars tend to travel when unencumbered by other vehicles. The streets are color coded as follows:Green (fast): 85 - 100% of free flow speedsYellow (moderate): 65 - 85%Orange (slow); 45 - 65%Red (stop and go): 0 - 45%To view live traffic only—that is, excluding typical traffic conditions—enable the Live Traffic layer and disable the Traffic layer. (You can find these layers under World/Traffic > [region] > [region] Traffic). To view more comprehensive traffic information that includes live and typical conditions, disable the Live Traffic layer and enable the Traffic layer.ArcGIS Online organization subscriptionImportant Note:The World Traffic map service is available for users with an ArcGIS Online organizational subscription. To access this map service, you'll need to sign in with an account that is a member of an organizational subscription. If you don't have an organizational subscription, you can create a new account and then sign up for a 30-day trial of ArcGIS Online.

A list of speed limiter centres where vehicles can have a speed limiter tested or repaired. Data includes addresses, postcodes and WGS84 Latitude, WGS84 Longitude Date extracted on 2014-05-27 from www.gov.uk Licence: None

This dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using the fixed location aerial videography approach with one high-resolution 8K camera mounted on a helicopter hovering over a short segment of I-94 focusing on the merge and diverge points in Chicago, IL. The altitude of the helicopter (approximately 213 meters) enabled the camera to capture 1.3 km of highway driving and a major weaving section in each direction (where I-90 and I-94 diverge in the northbound direction and merge in the southbound direction). The segment has two off-ramps and two on-ramps in the northbound direction. All roads have 88 kph (55 mph) speed limits. The camera captured footage during the evening rush hour (4:00 PM-6:00 PM CT) on a cloudy day. During this period, two SAE Level 2 ADAS-equipped vehicles drove through the segment, entering the northbound direction upstream of the target section, exiting the target section on the right through I-94, and attempting to perform a total of three lane-changing maneuvers (if safe to do so). These vehicles are indicated in the dataset. As part of this dataset, the following files were provided: I90_94_stationary_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion. I90_94_Stationary_Run_X_ref_image.png are the aerial reference images that define the geographic region for each run X. I-90-stationary-Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. The "x" and "y" columns represent the horizontal and vertical locations (in meters) in the reference image, respectively. The "ramp" columns define the type of roadway segment (0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments). In total, the centerline files define six northbound lanes (using twelve numerical IDs depending on the run).

Street segments of the road network.attributes:ID - Unique identifierToponymy - Full street nameNorte - Road numberCivic NumberOriginLeft - Civic number that originated the segment on the left side according to the direction of digitalizationNumberCivicOriginRight - Civic number that originated the segment on the right side according to the direction of digitalizationCivic NumberDestinationLeft - Civic number destined for segment on the left side according to the direction of digitalizationCivic NumberDestinationRight - Civic number to the segment on the right side according to the direction of DigitalNameGeneric - Short name of the streetType - Street typeStreet typeStreet typeSegmentStreet - Hierarchical class of the segment in the networkSpeed - Speed limit displayTypesUnique - Indication relating to the presence of a one-way wayMunicipal - Municipal code - Municipal codeHeavy traffic - Indication relating to heavy traffic**This third party metadata element was translated using an automated translation tool (Amazon Translate).**