RouteValet are solving urban congestion. Though over $110 Billion have been spent on mobility technology since 2010, traffic continues to get worse. Our cities are coming to a standstill. Traffic is frequently the number one factor of quality of life in a city.
We have created a navigation app which creates seamless routes across all modes of transportation, based on unique user preferences. The user enters their desired destination, and route valet collects real time information of all mobility options in the city. We then create seamless routes, optimized for the user’s preferences, including car, public transit, ridehail, rideshare, walking and cycling. These routes are shown to the user in the format of a navigation app.
Traffic is a severe economic burden in of terms fuel, maintenance and parking. It also severely limits the GDP of a city by reducing productivity. Arriving at work after sitting in traffic for an hour, decreases employee effectiveness.
At RouteValet, we solve traffic by focusing on people, rather than vehicles. We use Behavioral Economics and Machine Learning to understand what drivers are really looking for. Then, we create personalized routes, combining cars with public transit, delivering the best of both worlds.
Consider the simple case of driving a car to a parking lot and then riding a train to your final destination. The key is combining public transit options with private vehicle options such as car and ridehail. Now, users whose usual mode of transit is a private vehicle are enabled to reduce their private vehicle usage by advantageously combining public transit. In this way, we increase user delight, satisfaction with their city and simultaneously reduce traffic.
RouteValet is unique for two distinct reasons. Firstly, we are the only routing system we know of, which is creating personalized routes, based on behavioral economics and machine learning.
Secondly, we have succeeded in combining private vehicles with public transportation in integrated, seamless routes.
Public transit apps are based on ‘Raptor’ algorithms. Developed by Microsoft engineers in the early 2000s, they are now open source. Raptor creates routes by synchronizing the schedules of vehicles with both fixed routes and timetables. These algorithms are suited for fixed route and schedule vehicles only, and not private cars.
Car navigation apps are based on ‘Shortest Path’ algorithms. The first of these was invented by Dijkstra in the 1970s. Since then, other improved versions have been developed, such as A Star. These algorithms are optimized for a single, dynamic vehicle, and cannot integrate with a fixed route vehicle, such as a train or bus.
In contrast, leveraging Behavioral Economics and Machine Learning, RouteValet has succeeded in creating algorithms which integrate and optimize routing across both private vehicle and public transit mobility options. Further, these routes are made considering the full user profile. RouteValet are the first to create personalized, integrated routes.