Automated Taxi Alternate Destination Routing for Shared Trips
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Solution Overview
Problem
Automated-taxis face challenges in optimizing routes to minimize travel time and distance while accommodating multiple clients with different destinations, particularly when considering factors like traffic congestion, pedestrian zones, and construction areas, and need to decide whether to drop off clients at their desired or alternate destinations within a certain distance threshold.
Innovation Solution
The system proposes a preferred route that includes an alternate destination close to the client's desired destination, within a specified distance threshold, and requests approval from the client before making the drop-off decision, allowing for real-time adjustments based on traffic and client preferences, while also considering the impact on other passengers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the automated-taxi follows the direct route to the client's desired destination, then the client's travel time is minimized, but the overall route efficiency for multiple clients deteriorates due to unnecessary detours
Solution Approach 1:
The system merges multiple clients' destinations into a unified route optimization problem, identifying alternate destinations that allow multiple clients to be served efficiently in sequence. By combining destination considerations and proposing alternate drop-off points within acceptable distance thresholds, the system achieves better overall route efficiency while maintaining acceptable travel times for individual clients.
Solution Approach 2:
The system introduces an intermediary mechanism (alternate destination proposal) between the client's desired destination and the actual drop-off point. This intermediary approach allows the system to optimize the overall route by routing through alternate destinations that minimize total travel time for multiple clients, while the client can optionally accept the alternate destination or be dropped off at the desired destination.
2Ease of operation
If the automated-taxi drops off the client at the desired destination, then client satisfaction is maximized, but travel distance and time for all clients increases
Solution Approach 1:
The system implements a dynamic decision-making process where the drop-off destination is not fixed but adaptable based on real-time conditions. The system dynamically proposes alternate destinations to clients, allowing them to choose based on their preferences. This dynamic approach enables the system to balance client satisfaction with overall route efficiency, as clients can accept alternate destinations when convenient or insist on their desired destination when necessary.
Solution Approach 2:
The system incorporates feedback from clients regarding their destination preferences and accepts/rejects alternate destination proposals. This feedback mechanism allows the system to learn and adapt to client preferences, improving the balance between client satisfaction and route efficiency over time. The feedback loop enables continuous optimization as the system gathers data on client responses to alternate destination proposals.
3Length of stationary object
If the system optimizes the route by proposing alternate destinations, then overall travel distance is reduced, but route complexity increases due to real-time calculations and client approvals
Solution Approach 1:
The system applies partial optimization by proposing alternate destinations only when beneficial, rather than forcing optimization in all cases. The system calculates whether an alternate destination would reduce total travel distance and only proposes it when the benefit outweighs the complexity cost. This selective approach to optimization reduces unnecessary computational overhead while still achieving meaningful route efficiency improvements.
4Adaptability or versatility
If the automated-taxi adheres strictly to each client's desired destination, then individual client needs are met, but overall productivity and energy efficiency deteriorate
Solution Approach 1:
The system applies different quality standards to different aspects of the routing decision. For each client, the system evaluates whether strict adherence to the desired destination is necessary or whether an alternate destination would be acceptable. This local quality approach allows the system to maintain high adaptability to individual client needs in cases where it matters most, while achieving better overall productivity through strategic use of alternate destinations for other clients.
Data Source
AI summary
A system for operating an automated-taxi includes an input-device and a controller-circuit. The input-device is operable by a client to indicate a desired-destination of the client. The display is viewable by the client. The controller-circuit is in communication with the input-device and the display. The controller-circuit is configured determine a preferred-route in accordance with the desired-destination and a plurality of other-destinations indicated by a plurality of other-clients of an automated-taxi. The preferred-route includes an alternate-destination for the client. The alternate-destination characterized as within a distance-threshold of the desired-destination of the client. The controller-circuit is further configured to operate the display to request a route-approval from the client for the alternate-destination, and, in response to receiving the route-approval, operate the automated-taxi in accordance with the preferred-route to transport the client to the alternate-destination.