3D road models, a digital map with pavement-texture attributes and an HD map from a high-resolution archive or a UAV survey.
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What the service is used for
3D model of the route
A 3D model of urban road conditions or a complex surrounding environment, and digital elevation models.
Lane digitization
Digitization of road-traffic map objects in urban conditions, scale 1:200.
Polygons and trajectories
Roadway polygons, boundaries, unmanned-vehicle trajectories and outlining of maneuvers at intersections.
Sub-meter accuracy
High positional accuracy (sub-meter error), system-wide synchronization to the millisecond from position sensors.
Road maps from UAV
UAVs produce complex digital maps of roads and road conditions, including digital elevation models.
Need an HD map?
Send the area (coordinates, district, shp) and the end task — we will assess feasibility and the map composition.
What you will receive as a result of the work
01
3D road models
A 3D model of urban road conditions or a complex surrounding environment of the route, and digital elevation models.
The model is required by the unmanned-vehicle control system: sensors and on-board systems build a three-dimensional picture of the surroundings, while a high-accuracy road-network map defines lanes, intersections and obstacles.
What you get
- 3D road models
- digital elevation models for the agreed site
- a base for the HD map and lane digitization
Model composition, coordinate system and export format are fixed in the terms of reference.
02
Digital pavement map
A digital map with road-texture attributes — a pavement layer and roadway properties.
The map describes roadway polygons, boundaries and pavement properties. It is used together with the 3D model and the HD map for unmanned-vehicle navigation.
What you get
- a digital map with road-texture attributes
- roadway polygons and boundaries per the ToR scope
- export to agreed coordinate systems and projections
The set of pavement attributes and the layer format are agreed before the contract.
03
HD map
A high-accuracy road-network map for unmanned vehicles: lanes, maneuvers and traffic objects.
The HD map includes digitization of road-traffic map objects in urban conditions at 1:200 scale, movement trajectories of unmanned vehicles and outlining of maneuvers at intersections.
What you get
- HD map of the road network
- digitization of lanes and traffic-map objects at 1:200 scale
- movement trajectories and maneuvers at intersections — per the ToR scope
The completeness of lane digitization and the list of centerline breaks are set by the terms of reference.
How the work goes
Cost and timeline
Cost depends on the site area (urban streets) or route length, the configuration of the autonomous vehicle, the time to assemble technical equipment, and testing.
- consultation — free of charge
- selection of the technical solution and preparation of the terms of reference — paid
- data ordering and survey provision — paid
- data processing — paid
- cost of digitization of 1 km² (including creation of a 3D model) — from 500 USD
- price from 40 000 RUB (1 sq. km of 3D model) and is calculated individually for each client
- timeline on the card — from 5 days; in the timeline block — from 15 (fifteen) working days and is calculated individually
- the timeline depends on the site area (urban streets) or route length, the configuration of the autonomous vehicle, the time to assemble technical equipment, and testing
Price from 40 000 ₽ per 1 sq. km of 3D model
Timeline — from 15 working days (on the card — from 5 days)
Consultation — free of charge
What is needed for a quote
To agree feasibility, cost and timeline, please provide:
- the mapping area: coordinates, district or region name, or an shp file
- the end task to be solved using geospatial technologies
- archive high-resolution satellite imagery or UAV imagery of the territory or autonomous-driving route — if already available
- if no data are available — information on the intended use of the RS materials: specialists will analyse the requirements and propose an option
If imagery has not yet been collected, describing the area and the task is enough — specialists will assess service feasibility (yes/no).
Specify the outline or shp and the end task — we will calculate the survey and HD map composition.
Why Innoter
Prompt access to archives
Suitable archive imagery can be obtained faster when the required area and date are already available from operators.
No aviation clearances
A new satellite survey does not require the flight clearances typical of aerial surveys.
Large and remote areas
A single satellite pass covers large areas and makes it possible to work in hard-to-reach regions.
Direct agreements with operators
Distribution agreements help select archive imagery and order new surveys from different providers.
Software and server infrastructure
Modern software and computing capacity for quality control and processing of large data volumes.
Experienced specialist team
Years of experience on complex projects and specialists in cartography, photogrammetry and remote sensing.
HD map composition, survey and source data
Composition depends on street area or route length, the high-resolution archive or UAV data, and lane-digitization requirements.
1
Unmanned transport (autonomous transport, self-driving transport, driverless transport or robotic transport) is transport capable of moving without human involvement. An unmanned vehicle is a highly or fully automated vehicle that operates without human intervention (in unmanned mode) (Order of the Government of the Russian Federation dated 25.03.2020 No. 724-r).
Unmanned transport uses environment-perception sensors: thermal cameras, radar, LiDAR, sonar, GPS, odometry and inertial measurement units. Control systems interpret the sensor information, build a three-dimensional model of the surroundings and select navigation paths. High-accuracy road-network maps — HD maps — are an integral part of this stack.
2
A self-driving car consists of five main components:
- computer vision — identification and classification of objects from cameras;
- sensor fusion — multiple sensors to improve perception of the surroundings;
- localization;
- trajectory planning;
- control.
Vehicle automation includes levels 0–5: no driving automation, driver assistance, partial, conditional, high and full driving automation. As of 2022, the leading countries (China, Germany, South Korea and the USA) use Level 4 unmanned vehicles: autonomous driving with the option of manual override, in limited areas and under strict restrictions.
3
The vehicle’s autonomous driving system includes, in particular:
- adaptive cruise control (ACC);
- adaptive front lighting (AFL);
- automatic emergency braking (AEB);
- blind spot detection (BSD);
- cross-traffic alert (CTA);
- driver monitoring system (DMS);
- forward collision warning (FCW);
- intelligent parking assist (IPA);
- lane departure warning (LDW);
- night vision system;
- pedestrian detection system (PDS);
- road sign recognition (RSR);
- tire pressure monitoring system (TPMS);
- traffic jam assistant (TJA).
4
Preparatory geospatial work includes a 3D model of urban road conditions or a complex surrounding environment, digital elevation models, and digitization of road-traffic map objects in urban conditions at 1:200 scale: lane-map objects, roadway polygons, boundaries, movement trajectories of unmanned vehicles and outlining of maneuvers at intersections.
Lane centerlines are split into separate objects in the following cases: a change of marking on the right or left of the lane; merging with another lane; lane split; a change in lane width; a change of vehicle speed on the lane; entry to an intersection and exit from an intersection; entry to a pedestrian crossing and exit from it; a stop line; a change from a straight segment to a curved one; entry to a speed bump and exit from it; a change in stopping or parking possibility in the lane.
5
Practical data preparation for an unmanned vehicle relies on geospatial survey from UAVs and Earth-observation satellites. What is needed is coverage along highways, high detail in cities, transition from occluded sections (tunnels, mountains) to open terrain, and allowance for weather conditions; field geodetic and texture work is combined with platforms from satellites and airborne (UAV) systems through to mobile RS laboratories.
- high positional accuracy (sub-meter error) in time synchronized for the entire system to the millisecond, from recordings of position and control sensors;
- UAVs can produce complex digital maps of roads and road conditions, including digital elevation models;
- precise geospatial descriptions of movement — a legal basis for disputes and insurance cases.
6
Order of the Government of the Russian Federation dated 25.03.2020 No. 724-r — “Concept for ensuring road traffic safety involving unmanned vehicles on public roads”. Resolution of the Government of the Russian Federation dated 29.12.2022 No. 2495 establishes an experimental legal regime in digital innovation for transport services with highly automated vehicles in selected constituent entities of the Russian Federation. From the end of 2022, Resolution dated 29.12.2022 No. 2495 is in force on launching an experimental legal regime (ELR) for the operation of unmanned passenger and freight vehicles in cities and suburbs in 38 regions of Russia.
Before the contract: express assessment of the terrain, the stated timeline and result, and a check of whether work on the client’s territory is possible (result — feasibility yes/no); then agreement of requirements for the result and source data, roles, labour input, timeline and cost (result — contract). Execution: receipt of the advance, a prototype and agreement with the client, roll-out across the full site, export into coordinate systems and projections.
Frequently asked questions
Answers to key questions about service parameters, timelines, deliverable formats and workflow. If you did not find what you need — contact us and we will help.
Unmanned cars use sensors, actuators, complex algorithms and optimized processors to execute software. Based on this system, autonomous cars build and update a map of their environment and determine how to navigate through it.
The software analyzes all the sensory data from the car, draws a path and issues commands to actuators in the car that control acceleration, braking and steering. The software helps you follow traffic rules and avoid obstacles through the use of hard-coded rules, obstacle avoidance algorithms, predictive modeling and object identification
- Traffic management.
- Bureaucracy.
- Infrastructure.
- Revenue.
- Liability insurance.
- Police and emergency response.
The biggest benefit of using an unmanned vehicle is significantly fewer traffic accidents. More than 90% of all accidents are caused in some way by human error, including distraction, impaired driving or poor decision making.
Knowledge of GPS and wayfinding algorithms. Control is perhaps the most important building block of an autonomous vehicle. It includes guidance, navigation, and motion control systems and requires knowledge of math, engineering, and programming to build this function.
Unmanned vehicles using on-board sensors and evaluation equipment will always have a 360-degree view of their surroundings. Removing the driver from the controls will also reduce the element of human error in driving, which today is responsible for 90% of all accidents.
Need satellite imagery or help choosing the right data?
Describe your task, area of interest, and desired outcome. We will check data
availability, assess new acquisition options, and propose the optimal solution in terms of timelines, cost,
and quality.
Discuss the project
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