DROMOS TECHNOLOGIES AG (20240304086). Method for mixing scheduled and unscheduled vehicles simplified abstract
Method for mixing scheduled and unscheduled vehicles
Organization Name
Inventor(s)
[[:Category:Martin D�rr of München (DE)|Martin D�rr of München (DE)]][[Category:Martin D�rr of München (DE)]]
Method for mixing scheduled and unscheduled vehicles - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240304086 titled 'Method for mixing scheduled and unscheduled vehicles
Simplified Explanation: The patent application describes a method for allowing both scheduled vehicles and unscheduled autonomous vehicles to use a reserved road space in a transportation network. The method involves determining routes for the autonomous vehicles, predicting conflicts with scheduled vehicles, and generating instructions to avoid these conflicts.
- Key Features and Innovation:
- Method for parallel use of reserved road space by scheduled and unscheduled vehicles - Route determination for unscheduled autonomous vehicles in the transportation network - Prediction of conflicts with scheduled vehicles using interaction data - Generation of conflict avoidance instructions for autonomous vehicles
- Potential Applications:
- Efficient utilization of road space in transportation networks - Improved traffic flow and safety for both scheduled and autonomous vehicles - Integration of autonomous vehicles into existing transportation systems
- Problems Solved:
- Conflict resolution between scheduled and autonomous vehicles in reserved road spaces - Optimization of traffic flow and safety in transportation networks
- Benefits:
- Enhanced efficiency and safety in transportation systems - Reduction of potential conflicts and accidents on the road - Seamless integration of autonomous vehicles into existing traffic patterns
- Commercial Applications:
- "Method for Parallel Use of Reserved Road Space in Transportation Networks" can be applied in smart city infrastructure projects, autonomous vehicle development, and transportation management systems.
- Prior Art:
- Prior research may include studies on autonomous vehicle integration into existing transportation systems, conflict prediction algorithms, and traffic flow optimization methods.
- Frequently Updated Research:
- Ongoing research in the field of autonomous vehicle technology, traffic management systems, and smart city infrastructure development may provide further insights into the implementation of the described method.
Questions about the Method for Parallel Use of Reserved Road Space in Transportation Networks:
1. What are the potential challenges in implementing this method in real-world transportation networks?
- Implementing this method may face challenges related to infrastructure compatibility, regulatory frameworks, and public acceptance of autonomous vehicles.
2. How can the conflict avoidance instructions be effectively communicated to unscheduled autonomous vehicles in real-time?
- Real-time communication systems, such as vehicle-to-vehicle communication or centralized control systems, could be used to relay conflict avoidance instructions to autonomous vehicles.
Original Abstract Submitted
a method for parallel use of a reserved road space in a transportation network by a plurality of scheduled vehicles and a plurality of unscheduled autonomous vehicles is disclosed. the method comprises determining a route for the unscheduled autonomous vehicles travelling in the transportation network. the route is use for travelling from an origin to a destination in the transportation network. the method further comprises predicting conflicts for the unscheduled autonomous vehicles with the scheduled vehicles when travelling in the reserved road space. predicting the conflicts is done using the selected route and items of the interaction data for the plurality of scheduled vehicles. the method also comprises generating conflict avoidance instructions for the unscheduled autonomous vehicles in order to avoid the predicted conflicts with the scheduled vehicles.
