Considering the rapid speed with which technology is advancing it’s not surprising that the geospatial industry is regularly adjusting its course. While GIS is, due to its flexible nature used in a wide range of industries there is arguably none which relies on it more today than the transportation industry.
Smart Transportation Systems is, together with IoT, Smart Cities and Big Data, the buzzword of 2016. With Uber deciding to invest a cool $500 billion into its very own mapping system it’s apparent that maps are a priority for innovative organisations. The demand for functional, powerful and accurate transit maps has also spawned a new type of technologically savvy GIS-er who has terms such as GPS, GTFS, CityGML and pgrouting on his mind.
It's important to emphasise that transit route mapping is a complex process. The whole process requires that attention be paid to creating, checking and validating data feeds together with the compression of data for easy downloading to devices. Transit mappers prioritise diagrammatic clarity regarding issues such as overlapping lines and intersections and spend much time integrating often inconsistently structured data with available web mapping platforms. Segmentation, snapping, linear programming, parallel linear rendering and bezier curves are all included in the terminology of today's transit mapper.
It is intended that these transit maps will underpin the predictive decision-making navigation systems of driverless cars. Single lane road navigation maps will soon be replaced by hi-definition maps consisting of multiple lanes incorporating usage rules and assets such as shoulders, curbs, signage, and guardrails. In the future smart cars will use these maps to safely bypass slow-moving traffic, accommodate merging traffic, negotiate interchanges and select the correct exit lane - all while you sip your morning latte and read the newspaper.
But the technology doesn't stop there. These maps will be supplemented by enormous data collection capabilities. Billions of pixels and lidar points will be aggregated and processed with live data from fixed sensors, GPS systems, Wifi signals, and even the data collected by other cars. In the future it is expected that autonomous vehicles will be capable of redrawing the transit maps as they travel the roads.
Smart transportation systems aside, it has been suggested that indoor and outdoor navigation mapping will completely revolutionise the geospatial world. This is especially true considering the potential for applying navigation systems to industries such as retail, government, security and manufacturing.
However, all of that is another days work!