Road and address data is being increasingly used for many applications which are an important part of building smart cities and smart cars. November’s Spatial Data Infrastructure blog talks about how this data is collected and used today, but in addition, what needs to happen in the future to ensure you get the most return on your road and address data investments.
Canada’s Minister of Transport, recently attended the Intelligent Transportation Systems (ITS) World Congress in Montreal to highlight and discuss how leading-edge technologies are being developed to improve transportation around the world. The Minister indicated that transportation innovation is key to achieving the Government's commitment to reduce greenhouse gas emissions and fight climate change while ensuring safety, efficiency and economic growth.
This got me thinking – traffic congestion, fuel costs, reduced air quality and infrastructure expenditures are just some of the transportation issues that are directly affecting Canadians every day and everywhere. Many visionaries see this as an opportunity to deploy digital technology to improve the transportation network. As a result, a number of companies are making huge investments to create a “smarter” transportation system using connected and autonomous vehicles (CAV). The question arises – while we rush to digitize and electrify the transportation system, how will we manage the road and address data and especially the sharing and communication of this data? Let’s have a look.
Traffic congestion is a serious impediment to economic productivity and to personal wellbeing. Current and accurate road and address data is an essential component of applications that improve road transportation.
A real no-brainer and the most popular application of road and address data is for location finding. You may wish to know where you are at a given moment or where a business or attraction is; you may want to explore a certain neighbourhood, narrow down accident-prone areas, find out transit locations and timings, or simply share your current location and activity with others on social media.
Another major use of mapping data is routing or navigation. Today, GPS and communication technology easily enables a variety of transportation applications that can be used at your fingertips. These applications not only provide users with a route but even turn-by-turn directions to reach their destination comfortably. Such applications require current and accurate geospatial data. For example, when using an in-car navigation system, its road and address data needs continuous updates or its performance may be compromised - leading to inaccurate routes or destinations and longer travel times. Many people rely on their smart phone to ensure they have the most up-to-date data for routing. However, even though smart phones provide near real-time map routes, they can use up a significant amount of cellular data.
When we are talking transportation, we can’t ignore traffic congestion. One of the major impediments in your quest to get from A to B by car is traffic congestion of any cause or type. Certain applications have exploited this obstruction by allowing users to report congestion, so others can avoid those clogged roads by taking alternate routes. One of the major players in user-generated traffic reports for routing is Waze, which is the world's largest community-based traffic and navigation app. Waze allows other drivers to automatically share real-time traffic and road information to avoid congestion, thus saving everyone’s time and fuel on their daily commutes.
So where do these locations and route-finding applications get their base road and address information? While many companies collect this data themselves, others might use commercial spatial data suppliers or any available source. Governments, in particular, collect road and address information in order to provide services effectively to their citizenry. Often, they make this data available for all to use in the form of open data.
Currently, due to decades of working independently, the data produced and made available by the federal, provincial and municipal levels of government, and others, is sometimes characterized by low spatial accuracy or geometrical uniformity. Check how this image below demonstrates spatial disparity among several road networks for a Canadian city.
Esri imagery basemap of a Canadian city overlaid with the street network data from the federal government (red), the provincial government (green), the city government (blue) and Open Street Map (white). Note that the data is reasonably accurate, but each street network dataset is slightly different.
Many important government applications use this road and address data on a daily basis. These include police, fire, ambulance, city planning, environmental assessments, demography, public works, public transit, cycling routes, and ticketing. While it is well known that the data collected and used by government is not perfect, it is sufficiently accurate for the applications it is being used for (fit for purpose).
Experience has shown that aggregating transportation data from all levels of government to produce a single authoritative road network using technology such as the GeoFoundation Exchange (GFX) is quite feasible and efficient. While it may not be possible to create a perfect geospatial road and address database, it is quite possible to make a very accurate database plus keep it current. For instance, the New Brunswick Road Network is an excellent example of how the Province of New Brunswick uses the GFX to maintain its digital road network, and it sets the pattern for using the GFX across the country and across different data layers. Read more about it in the 2017 fall issue of ArcNorth News.
The in-vehicle applications of the road and address data are time and money savers for the public and the best applications are based on the most accurate and trustworthy data. This calls for a single, current, accurate and complete road and address database for the nation.
While still under development, connected and autonomous vehicles (CAVs) need map data to find the best route from location A to location B, plus stay on the road. However, the level of spatial data accuracy required for CAVs is much higher than for retail navigation systems or government requirements. Like Waze, these CAVs will share map and traffic data in real time via communication links plus much of the vehicle’s sensor data will be geocoded to the map data. These CAV high definition maps will be very accurate and self-healing to support safe and efficient autonomous driving.
To allow a seamless transition into the new era of CAVs, we need to ask ourselves: are our road and address maps accurate, trustworthy and effective enough to facilitate computerized driving and ensure complete safety? The key is to make sure that as new roads are built, lanes get closed, traffic is jammed or new bridges are opened, road and address information is collected and communicated to all the vehicles (including yours) in near real time.
About the Author
Gordon Plunkett is the Spatial Data Infrastructure (SDI) Director at Esri Canada. He has more than 30 years of experience in GIS and Remote Sensing in both the public and private sectors. He currently sits as a member of the Community Map of Canada Steering Committee, GeoAlliance Canada Interim Board of Directors, the Open Geospatial Consortium (OGC) Technical Committee, the Canadian General Standards Board (CGSB) Committee on Geomatics, the University of Laval Convergence Network Advisory Committee and the Advisory Board to the Carleton University Geomatics and Cartographic Research Centre. During his career, Gordon has worked on projects in more than 20 countries and has contributed to numerous scientific conferences and publications. At Esri Canada, he is responsible for developing and supporting the company’s SDI vision, initiatives and outreach, including producing content for the SDI blog.More Content by Gordon Plunkett