GeoMate: AI-Powered Mapping for Smart Mobility
SAFETY OF AUTONOMOUS VEHICLES: INNOVATION FROM RISK TO REWARD
Self-driving cars are a technological marvel with serious technical hurdles that are causing declines in consumer confidence. But they’re the transportation of the future: so how can the industry solve this?
As the next revolution in the automotive sector, much of the world is abuzz over the development of autonomous vehicles. (Commonly referred to as self-driving cars).
The idea of autonomous driving has always been attractive to many people. Why deal with the difficulties of traffic or unsafe drivers on the road? Why suffer through harsh weather conditions when the computer in the car navigate better? It doesn’t even stop there. As the autonomous vehicle craze can shift the dynamics of car ownership, fleet services could maximize efficiency.
These days, autonomous vehicles are starting to conduct public trials. This includes robotaxis, automation of public transit and partial self-driving in existing vehicles. That said, there remains a great deal of controversy. Many are questioning how companies are bringing these vehicles to market, and whether they’re as reliable as a human driver.
Let’s examine the progress made and figure it out: are self-driving cars safe?
TODAY'S INNOVATORS, TOMORROW'S LEADERS
Today, every major automotive player is looking to develop autonomous products. Established companies like GM and new participants such as Google (Waymo) are pursuing new opportunities in both advanced driver assistance systems (ADAS) and fully autonomous transport. However, delivery of this tech is currently limited to self-driving taxis that operate within specified geographic boundaries.
These products aim to provide residents of trial areas with an affordable, automated, and innovative way to get around their cities. Participating cities to date include San Francisco, CA and Phoenix, AZ. In recent months, this self-driving technology has been cleared to operate within set parameters. Namely, primary operations during evening hours with lower traffic and with specific oversight by administering companies.
For its part, auto innovator Tesla is focusing on upgrading onboard control features. Here, the goal is to ease the responsibilities of the driver at the wheel, while not eliminating them. However, there are significant concerns relating to their use of camera-driven assistance, which offers poor localization in real-time and is vulnerable to harsh weather conditions. As a result, this decision could potentially impact the safety of autonomous vehicles and the reputation of their manufacturers.
ADVANTAGES FOR CITY PLANNERS
In recent months, the use of these pilot projects has been hampered by technical issues, such as the blocking of roads in San Francisco by a large pack of robotaxis. In this instance, there was a large gathering of vehicles on the same street in the city, blocking traffic for two hours in the evening. Likely brought on by localization error, this poses challenges for urban planners and manufacturers alike. Consequently, how can infrastructure be tailored and leveraged for these new autonomous taxi platforms?
As the foremost innovation in navigation technology, high-definition (HD) maps provide high-precision identification of all roadside factors that play a role in autonomous vehicle safety and operation. These maps therefore allow leaders of both community and industry alike can maximize impact value of each dollar spent. Uses could include infrastructure location research, real-time weather tracking and more.
Specialized drop-off areas and avoiding routes with high pedestrian traffic are but some of the proactive features HD maps provide. In addition to this, passengers can feel secure aboard one of these autonomous vehicles. This is done thanks to efficient operation: increased reliability in harsh weather conditions, real-time recognition of everything from signs to sidewalks, and accuracy on road networks.
SAFE & SECURE SELF-DRIVING
Part of the reason self-driving cars have had issues with real-world operation is the consistently-underperforming solution produced for localization. This is the core feature of any autonomous vehicle. The process of localization allows a vehicle to figure out where exactly it is situated in operation zones using real-time data.
Currently, autonomous vehicles produced by major companies are employing either the camera-driven approach or some variation of high-definition maps. As the gold standard for mapping in real-time, HD maps allow for the identification and extrapolation of linear and vertical features on the road. (Defined as anything from lane markers to signage) While this technology has impressed manufacturers, it has long been held back by poor scaling potential and expensive development costs.
As the newest innovator in HD maps, GeoMate seeks to break down the barriers to secure and effective localization for autonomous vehicles. By leveraging geospatial data and machine learning in our processes, we can produce affordable HD maps at any scale, for any vehicle, and in any city. Gone are the days of expensive and environmentally harmful survey vehicles. As we only require simple geospatial imagery, creating a fully-featured digital twin of the urban landscape is significantly easier. Therefore, with our mapping offerings, autonomous vehicle manufacturers can expect localization of a premium quality at a discounted price.
THE ROAD GOING FORWARD
Self-driving vehicles are the next major innovation in the automotive market. They have a unique potential to free us from the pains of vehicle ownership, and also to foster efficiency. That said, the poor localization and navigation product offerings are holding industry leaders back from true progress and consumer confidence. By forcing them into expensive contracts and providing only pitfalls or undermining of trust, someone must step forward.
As such, the future of autonomous vehicles lies in HD maps. They both satisfy the need to conserve meaningful resources and the goal of providing genuinely scalable service to the urban world. Leveraging geospatial data, and turning it into meaningful location intelligence through artificial intelligence, is the key to realistic and safe self-driving technology. Guaranteeing safety of autonomous vehicles is paramount in ensuring that our society can progress past negligent drivers and endless gridlock.
If you’re interested in being part of the solution, contact us with your needs!
