Dynamic Routing Engine for On-Demand Transport
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Solution Overview
Problem
Existing on-demand network systems face inefficiencies in vehicle routing due to dynamically determined start and end locations, leading to delays caused by road topology, traffic conditions, safety concerns, and other factors.
Innovation Solution
The system dynamically determines start and end locations for service requests by using a dynamic routing engine that selects candidate points based on location and directionality constraints, and then determines routes and ETAs for each combination of candidate points, optimizing for efficiency and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the vehicle follows the requested origin and destination locations directly, then the routing simplicity is maintained, but the service efficiency deteriorates due to delays caused by road topology, traffic conditions, and safety concerns
Solution Approach 1:
The requested route is segmented into multiple candidate points (waypoints) along the path. The system divides the journey into segments between consecutive candidate points, allowing each segment to be optimized independently for safety, traffic conditions, and road topology while maintaining overall routing simplicity.
Solution Approach 2:
The system dynamically determines optimal candidate points and routes based on real-time conditions including traffic data, road topology, and safety constraints. The routing solution adapts dynamically to changing conditions rather than following a fixed predetermined path, improving service efficiency while managing complexity through automated decision-making.
2Measurement precision
If the system provides precise GPS location and street address to the vehicle, then the location accuracy is improved, but the routing optimization capability deteriorates due to inability to account for real-time conditions
Solution Approach 1:
The system performs preliminary actions by pre-identifying multiple candidate points along the requested route before the vehicle arrives. These candidate points are pre-evaluated based on road topology, safety constraints, and potential traffic conditions, allowing the vehicle to follow an optimized path without requiring real-time complex decision-making during transit.
Solution Approach 2:
The system introduces intermediary candidate points (waypoints) between the requested origin and destination. These intermediary points serve as mediators that break down the direct route into manageable segments, each optimized for local conditions while maintaining connection to the overall destination, thus combining location accuracy with routing optimization.
3Loss of time
If the vehicle travels directly between requested origin and destination, then the trip time is minimized theoretically, but the actual trip time increases due to delays from road topology and traffic conditions
Solution Approach 1:
The system incorporates feedback mechanisms that monitor traffic conditions, road topology, and vehicle status throughout the journey. Based on this feedback, the system can dynamically adjust the route by selecting alternative candidate points that reduce delays while maintaining relatively simple vehicle operations, thus minimizing actual trip time without significantly complicating driver tasks.
Data Source
AI summary
A network system dynamically determines a route, including start and end points, for vehicles in a transportation network. The transportation network receives a service request from a user of the transportation network including an origin location for the trip and a destination location for the trip. The transportation network then generates a waypoint plan for one or more vehicles, which includes the requested origin and destination in addition to any previously requested origins and destinations included in the vehicles current route. The network system then determines a directionality for each of the waypoints in the waypoint plan and retrieves candidate start and end points that have an associated directionality within a threshold angle of the directionality of each waypoint and are proximate to the waypoint. The network system evaluates each combination of retrieved candidate points to select a route for the vehicle.