Could 2017 be the year ride sharing surpasses taxis? How will advances in automated ride-sharing vehicle technology and AI (artificial intelligence) impact the future of transportation? This year will likely be an important one for new partnerships between automakers and technology companies to collaborate on safety and connectivity, as they simultaneously continue to push toward autonomous driving.
Already, the traditional transportation system has been upended, for instance, by smartphone-enabled ride sharing systems. A recent study from MIT’s (Massachusetts Institute of Technology’s) CSAIL (Computer Science and Artificial Intelligence Laboratory), www.csail.mit.edu, says ride sharing services like Uber, www.uber.com, and Lyft, www.lyft.com, could reduce the number of taxis on the road by 75% without significantly impacting travel time. In fact, MIT researchers’ algorithm suggests 3,000 four-passenger cars could serve 98% of taxi demand in New York City, with an average wait time of just under three minutes.
The algorithm, which leverages data from 3 million taxi rides, works in realtime to reroute cars based on incoming requests. MIT also says the algorithm can proactively send idle cars to areas with high demand. Researchers believe continued innovation and advancement of ride sharing technology and adoption will cut traffic congestion and fuel consumption, which will free up people’s time from long commutes and result in cleaner air.
AI will also play an increasingly important role in how ride sharing evolves in the near to long-term future. The undisputed market leader, Uber, launched Uber AI Labs in December to focus on AI and machine learning research. The goings-on at Uber’s AI division will likely result in new advancements in intelligent, perhaps even automated ride sharing in the coming years. Additionally, Uber has acquired a small AI research startup called Geometric Intelligence, and the company has announced it will work with cities to give away some of its ride sharing data to help improve roads and other transportation infrastructure, as well as transportation planning. Both moves on Uber’s part signal trends in the space, which will only become more complex and sophisticated with time.
The other elephant in the room when it comes to discussing the intersection between ride sharing, autonomous vehicle technology, and AI is Honda, www.honda.com. This year at CES, Honda unveiled NeuV (pronounced “new-vee”), a miniature autonomous EV (electric vehicle) that can not only function as a mode of personal transportation but also as an autonomous ride sharing vehicle. The concept car integrates HANA (Honda Automated Network Assistant), Honda’s AI that learns from drivers and takes actions based on feedback to improve the driving or riding experience.
Honda’s idea is that the NeuV could be actively driven by a human or autonomously driven by a computer depending on the driver’s preference that day. The vehicle could also make its owner money by making itself available for autonomous ride sharing while the owner doesn’t require NeuV for him or herself. The idea is an interesting one—one that seems a lot more plausible in today’s urban environments than it would have seemed just five or 10 years ago. With self-driving fleets now being piloted in cities such as Pittsburgh, Penn., it’s likely that autonomous ride sharing driven by AI and advanced machine learning will be a reality in this century.