Vehicle Platooning Routing for Overlapping Multi-Vehicle Trips
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Solution Overview
Problem
The increasing number of vehicles on roadways leads to traffic congestion and energy consumption issues, as existing roadways are not efficiently utilized, and platooning, which aims to improve vehicle efficiency by coordinating vehicle travel, is complex to implement effectively.
Innovation Solution
A method and system for generating multi-vehicle aware routing and scheduling that allows vehicles to join and depart from platoons, optimizing routes to maximize efficiency by considering the routes and schedules of other vehicles, using a computer program product with a processor and memory to generate and adjust platooning plans based on real-time data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If vehicles travel independently on their own routes, then each vehicle can optimize its own route efficiency, but overall roadway efficiency is reduced due to lack of coordination
Solution Approach 1:
The patent merges multiple independent vehicle routing problems into a coordinated platoon formation system. The routing engine combines routes of multiple vehicles to create overlapping platoon segments, where vehicles travel together in formation. This merging transforms individual route optimization into group route optimization, improving overall roadway efficiency through coordinated travel while managing complexity through systematic route combination algorithms.
Solution Approach 2:
The routing engine performs multiple functions: it generates individual vehicle routes, identifies overlapping segments for platoon formation, coordinates departure times, and manages platoon dissolution points. This multi-functional approach consolidates what would otherwise require separate systems into a single coordinated platform, improving roadway efficiency while containing complexity within a unified system.
2Use of energy by moving object
If vehicles form platoons to improve fuel efficiency and reduce energy consumption, then energy usage decreases, but the system complexity and difficulty of implementation increase
Solution Approach 1:
The system performs preliminary route planning and platoon formation coordination before vehicles depart. The routing engine pre-identifies overlapping route segments, calculates optimal platoon formation points, and establishes departure schedules in advance. This preliminary action allows vehicles to efficiently form platoons without real-time complexity, reducing energy consumption through pre-coordinated travel while managing system complexity through advance planning.
Solution Approach 2:
The routing engine acts as an intermediary between individual vehicle routing systems and platoon coordination requirements. It receives route requests from multiple vehicles, processes overlapping segment information, and generates coordinated platoon itineraries. This intermediary function simplifies the overall system by centralizing the complex coordination logic in a dedicated component, enabling energy-efficient platooning without distributing complex coordination across all vehicles.
3Productivity
If routes are generated without considering other vehicles, then route generation is simpler and faster, but opportunities for platoon formation and efficiency improvements are lost
Solution Approach 1:
The routing system segments the route generation process into distinct phases: individual route generation, overlap identification, and platoon coordination. By segmenting the computational task, the system can efficiently generate individual routes first (maintaining speed), then identify platoon opportunities in a separate analysis phase (improving efficiency). This segmentation reduces computational time while capturing platoon formation opportunities that would be lost in monolithic route generation.
Solution Approach 2:
The system performs partial platooning coordination by identifying and forming platoons only for route segments where vehicles have overlapping itineraries. Rather than attempting to coordinate all vehicles on all routes, the system focuses computational effort on identifying overlapping segments and forming platoons where beneficial. This partial action approach improves platoon formation efficiency without requiring excessive computational resources to analyze every possible vehicle combination.
Data Source
AI summary
A method, apparatus and computer program products are provided for generating routes for vehicles participating in a platooning plan, where the routes are influenced by one another. Methods may include receiving a first trip request including a first vehicle identification, a first trip origin, and a first trip destination; receiving a second trip request including a second vehicle identification, a second trip origin, and a second trip destination, where the first trip origin, second trip origin, first trip destination, and second trip destination are all different; generating a platooning plan that includes a first route and a second route, where the first route and the second route overlap for at least a portion of the respective route, where at least one of the first route and the second route are generated with an influence from the other of the first route and the second route.