Tech Viewpoint: Three online delivery problems solved by automation
Every week, it seems there are more retailers testing automated delivery of online orders.
Amazon, Walmart, Kroger, and Stop & Shop are just a few recent examples of retailers piloting the use of autonomous vehicles to fulfill online purchases. Autonomous vehicles are not a panacea for all the issues and complexities associated with delivering online orders. But here are three significant delivery problems facing online retailers that automation can help solve.
The case of the disappearing driver
Quite simply, there aren’t enough professional truck drivers to go around. The American Trucking Associations (ATA) predicts a shortage of 175,000 truck drivers in the U.S. by 2026. And the Bureau of Labor Statistics estimates the average U.S. commercial truck driver is 55 years old – Millennials, Gen Zers, and even most Gen Xers are not pursuing careers in trucking.
By utilizing automated delivery vehicles, online retailers can effectively make up for the growing shortfall in professional drivers. Crowdsourced delivery options provided by ride share services can be helpful for smaller, shorter-range deliveries. But they are less feasible for retailers shipping large purchases or making multiple or long-range deliveries.
Also, a growing scarcity in drivers will likely result in higher delivery costs charged by third-party carriers. Online retailers who don’t use automated vehicles as an alternative will have to absorb or pass on these costs to customers.
Crosstown traffic (all you do is slow me down)
Increasingly, online shoppers expect their purchases delivered overnight, if not the same day. This is exacerbating an already abysmal traffic situation in most U.S. metropolitan areas.
Some of the problems posed by heavy traffic volumes can be mitigated with autonomous delivery vehicles that avoid conventional gridlock, such as self-piloting drones. In addition, online retailers can take inspiration from innovative autonomous delivery solutions such as Amazon Scout. Amazon is piloting this six-wheeled device, which is the size of a small cooler and travels on sidewalks at slow speeds, to make select deliveries in Washington.
The Route of the Problem
Despite what they teach in calculus, the shortest distance between two points is not always a straight line. Or at least not if there are accidents, road hazards, construction, inclement weather, special events, or other delivery route impediments.
Thanks to GPS systems and a number of different traffic navigation apps, human drivers can be directed to avoid problems in their route before they encounter them. But this is still not as efficient as feeding an autonomous vehicle a constant stream of data about every conceivable obstacle or delay in its path. The vehicle’s robotic navigation system can then use artificial intelligence and machine learning to instantly change its route in the most beneficial manner possible.
In addition, autonomous vehicles have so far proven much less likely to get into accidents than vehicles with human drivers. Google reports that as of May 2018, its Waymo self-driving car project had driven 5 million miles since 2009, with one minor at-fault crash in that time. This means autonomous vehicles are also effective at avoiding hazards that GPS systems and traffic apps cannot detect, such as the car ahead stopping short or a pedestrian suddenly darting into a vehicle’s path.
Amazon, Walmart, Kroger, and Stop & Shop are just a few recent examples of retailers piloting the use of autonomous vehicles to fulfill online purchases. Autonomous vehicles are not a panacea for all the issues and complexities associated with delivering online orders. But here are three significant delivery problems facing online retailers that automation can help solve.
The case of the disappearing driver
Quite simply, there aren’t enough professional truck drivers to go around. The American Trucking Associations (ATA) predicts a shortage of 175,000 truck drivers in the U.S. by 2026. And the Bureau of Labor Statistics estimates the average U.S. commercial truck driver is 55 years old – Millennials, Gen Zers, and even most Gen Xers are not pursuing careers in trucking.
By utilizing automated delivery vehicles, online retailers can effectively make up for the growing shortfall in professional drivers. Crowdsourced delivery options provided by ride share services can be helpful for smaller, shorter-range deliveries. But they are less feasible for retailers shipping large purchases or making multiple or long-range deliveries.
Also, a growing scarcity in drivers will likely result in higher delivery costs charged by third-party carriers. Online retailers who don’t use automated vehicles as an alternative will have to absorb or pass on these costs to customers.
Crosstown traffic (all you do is slow me down)
Increasingly, online shoppers expect their purchases delivered overnight, if not the same day. This is exacerbating an already abysmal traffic situation in most U.S. metropolitan areas.
Some of the problems posed by heavy traffic volumes can be mitigated with autonomous delivery vehicles that avoid conventional gridlock, such as self-piloting drones. In addition, online retailers can take inspiration from innovative autonomous delivery solutions such as Amazon Scout. Amazon is piloting this six-wheeled device, which is the size of a small cooler and travels on sidewalks at slow speeds, to make select deliveries in Washington.
The Route of the Problem
Despite what they teach in calculus, the shortest distance between two points is not always a straight line. Or at least not if there are accidents, road hazards, construction, inclement weather, special events, or other delivery route impediments.
Thanks to GPS systems and a number of different traffic navigation apps, human drivers can be directed to avoid problems in their route before they encounter them. But this is still not as efficient as feeding an autonomous vehicle a constant stream of data about every conceivable obstacle or delay in its path. The vehicle’s robotic navigation system can then use artificial intelligence and machine learning to instantly change its route in the most beneficial manner possible.
In addition, autonomous vehicles have so far proven much less likely to get into accidents than vehicles with human drivers. Google reports that as of May 2018, its Waymo self-driving car project had driven 5 million miles since 2009, with one minor at-fault crash in that time. This means autonomous vehicles are also effective at avoiding hazards that GPS systems and traffic apps cannot detect, such as the car ahead stopping short or a pedestrian suddenly darting into a vehicle’s path.