The in-vehicle assistance system informs drivers of the speed limit, warns them if they exceed it and may even prevent them from speeding. This is particularly helpful when drivers are distracted, have missed traffic signs or warnings, have impaired visibility in bad weather or have difficulty recognizing situational speed limits. However, implementing the driver aid requires a well-thought-out system that combines cameras, an electronic horizon and digital maps.
A key challenge for driver aids such as intelligent speed assistance and autonomous driving is that vehicle cameras cannot detect all speed limits. In some countries, signs are more explicit than in others. Some roads also have speed limits that vary depending on time of day, weather conditions and type of vehicle. As such, speed limits are not always perceptible to cameras.
For advanced driver-assistance systems to remain effective, automakers should consider investing in map data that provides the speed limits and conditions for every road segment, regardless of visibility or availability of signs, weather, vehicle type and time of day.
Intelligent speed-assistance systems access various data points to determine the permitted speed. Forward-facing cameras, global navigation satellite systems for positioning the vehicle on the road, an electronic horizon and map data that includes all speed limits — whether sign-posted or not — are the minimum requirement for intelligent speed-assistance systems today.
The electronic horizon is a software that combines digital map data with information about position and road conditions from sensors to create a model of the road ahead. Data from the electronic horizon is made available to the speed-assistance system to ensure it functions without error, meeting system requirements that cannot be done purely via sensors.
The map data the electronic horizon consumes is built and constantly maintained using a highly diverse mix of Here Technologies' and third-party sources. We have local field experts, a global organization with diverse backgrounds that source and add local road rules and unobservable data to our map. We use vehicles to gather highly precise data, more precise than production vehicle sensors can provide.
To maintain the data and identify changes, we use a growing pool of sensor and probe data that all feed into our mapmaking process. Highly automated mapmaking and publication pipelines allow real-world changes to publish faster — thus creating stronger intelligent speed-assistance solutions.