Select optimal pickup spot for delivery to that spot
Choose and place order using partner APIs
Select a task to perform on the way
We are a team of 4 current and aspiring entrepreneurs united by a common interest to promote environmental sustainability and solve challenging problems in the mobility space using technology and innovative business models. The rideshare industry is plagued with problems of financial unsustainability, with the primary lever to profits being improvements in operational efficiency. We believe we have a workable solution that addresses the largest friction, which takes place during the driver’s delivery to the destination. An example is in food delivery: by eliminating the need for drivers to wait for the customer to collect the food, access the customer’s apartment, etc, we increase the turnaround time for driver jobs and profitability for the driver. These ultimately support the rideshare platform companies’ bottom lines, through improving driver retention and profits per trip.
What it does
OTW is an intelligent goods delivery platform that allows car owners to efficiently pick up goods (e.g. hot meals, urgent packages) by optimizing for the most convenient pick-up location along the car owner’s journey from point A to B.
How we built it
Prototyped the algorithm using jupyter notebooks and openstreetmap and Here APIs. Implemented the backend server and API calls using the Here maps API and Flask server. Frontend was built using Vue.js. It uses Here Maps API to render an interactive map.s
Challenges we ran into
On the technical side, balancing the trade-off of carbon footprint vs route time; picking optimal drop-off locations to ensure seamless customer service experience; optimal algorithms for route computation. On the business side, forming partnerships with Uber (and Uber Eats) and Amazon might be a challenge as they may be focusing on building this out as extensions of their own platforms. However we foresee the benefit of a platform agnostic approach which can reduce costs and improve operational efficiencies for all players.
Accomplishments that we're proud of
Achievements that we're proud of: Fast and agile working, ability to come together quickly and work super cohesively throughout the hackathon, capitalizing on our individual strengths in both technical and business areas. Creation of the optimization algorithm over night.
What we learned
With the industry moving towards a "delivery-first" approach, we will need to optimize the deliveries and pickups. We learnt that creating and leveraging popular pickup locations (hotspots), not only will improve the customer experience but also saves operations costs of the businesses. With the future of last mile mobility and pick-up lockers, generating a trend of optimal pickups opens opportunities for Nuros and Autonomous Vehicles.
What's next for On The Way
Immediate term (2019-2021): Roll-out Last Mile API to enable B2C deliveries of goods to locations for customer pick up en route, optimized by time, distance and amount of carbon emissions. Integrate with rideshare and food delivery platforms (Uber, Uber Eats, DoorDash, etc). Partner with smart locker companies. Medium term (2022-2024): Upsell gas station / auto shop services that are also en route e.g. refuelling, predictive maintenance (using machine learning), EV charging using connected vehicle APIs. B2B deliveries of packages for pick up by carriers for last mile delivery. Longer term (2025+): Deliveries of goods and packages to/by autonomous vehicles operating on fixed routes at designated pick up points.