Dynamic Ridehail Vehicle Assignment via Digital Identity
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Solution Overview
Problem
Current ridehail services face challenges in connecting vehicles to customers, particularly in congested areas, unfamiliar locations, and dynamic customer movements, leading to difficulties in vehicle location and accessibility.
Innovation Solution
The system uses digital identifiers, such as facial recognition and geolocation data, to dynamically connect customers with ridehail vehicles, allowing for real-time reassignment to more accessible vehicles and assisting drivers in locating customers through shared data from infrastructure and vehicle sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If ridehail vehicles are connected to customers based on relative location proximity, then connection speed is improved, but vehicle accessibility deteriorates in congested areas
Solution Approach 1:
The system dynamically reassigns ridehail vehicles to customers based on real-time location data and accessibility conditions. Instead of static proximity-based assignment, the system continuously monitors and adjusts vehicle-customer connections, allowing customers to be reassigned to more accessible vehicles as they move or as traffic conditions change.
Solution Approach 2:
The system implements feedback loops where customer location data, vehicle position data, and accessibility information are continuously collected and processed. This feedback enables the system to identify when a originally assigned vehicle is no longer optimally accessible and triggers reassignment to alternative vehicles that better meet current accessibility needs.
2Loss of time
If customers are assigned to nearby ridehail vehicles, then wait time is reduced, but customer location detection difficulty increases in unfamiliar or impaired scenarios
Solution Approach 1:
The system employs multiple identification methods including facial recognition, geofencing, and mobile device location tracking. These multi-functional detection capabilities allow the system to identify and locate customers through various means, ensuring reliable detection whether customers are stationary, moving, have impairments, or are in unfamiliar locations.
Solution Approach 2:
The system uses intermediate technologies such as facial recognition systems, geofencing boundaries, and mobile device intermediaries to detect and track customer locations. These intermediaries bridge the gap between customers and the ridehail matching system, enabling accurate location detection without requiring direct customer-vehicle communication.
3Device complexity
If static vehicle-customer connections are maintained, then system complexity is reduced, but adaptability to dynamic customer needs deteriorates
Solution Approach 1:
The system transitions from static to dynamic vehicle-customer connections by continuously monitoring customer location, vehicle availability, and accessibility conditions. This dynamic approach allows automatic reassignment when customers move to new locations or when more suitable vehicles become available, enhancing adaptability while managing complexity through automated decision-making algorithms.
Data Source
AI summary
Systems and methods are provided herein for connecting a transportation vehicle to a customer. This process may involve receiving a digital identifier of a user at a particular location, where the digital identifier may be obtained by one or more video capture devices. Such devices may be located in an environment of the one or more ridehail vehicles and the user and/or located on the one or more ridehail vehicles themselves. The process may also involve determining a ridehail vehicle to assign to the user based on the digital identifier indicating the user is at the particular location.