notes from the field: enabling new last-mile services with autonomous delivery vehicles

last-mile services

Autonomous delivery vehicles have the potential to be much more than a replacement or extension of existing delivery services. With a powerful computing system inside them, they will be able to go beyond simply transporting goods or meals from a logistics hub to a consumer’s home to providing a wealth of new last-mile services that improve convenience, security, and health for individual consumers and the community at large.

In addition to core navigation and safety functionality such as 360° surround view video, long and short-range radar, and LiDAR, autonomous delivery vehicles will be able to support a huge selection of additional features and applications to meet individual and community needs – such as facial recognition to ensure that the right person is picking up the delivery and even thermal sensors for scanning the temperature of workers and other people who come close to the vehicle.

Integration with sophisticated cloud-based management systems will open up even more opportunities for enhancing the quality and convenience of last-mile services, such as ensuring the timely arrival of deliveries when the customer is at home to receive them. By building up a deep understanding of the community they operate in, the vehicles will also be able to act as virtual neighborhood monitors that send out alerts when they identify suspicious activities or notice that an elderly resident hasn’t walked their dog according to their usual schedule.

As the cost of developing and building autonomous delivery vehicles continues to go down, a growing number of established companies and startups will enter the market. A particularly promising test bed for initial deployments will be in “geofenced” areas such as universities, retirement communities, and industrial estates, where the operation of the vehicles can be more easily managed. The experience and knowledge gained from these projects will prove invaluable when it comes to tackling larger scale implementations.

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