Cooperative Automated Vehicle Gap Creation
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Solution Overview
Problem
Traffic congestion makes it difficult for vehicles, cyclists, pedestrians, and other objects to enter or merge into a travel lane, especially in high-traffic zones, as existing systems do not effectively manage host-vehicle motion to create safe gaps for others.
Innovation Solution
A cooperative-vehicle system equipped with an object-detector and controller that adjusts the host-vehicle's motion to allow other vehicles, cyclists, or pedestrians to enter the travel lane by detecting wait times, traffic density, and other factors, using sensors like cameras, radar, and V2X communications to control speed and lane changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the host-vehicle maintains its current speed and position in congested traffic, then the host-vehicle's travel efficiency is maintained, but other vehicles cannot enter the travel-lane from side streets or parking areas
Solution Approach 1:
The system performs preliminary detection of other vehicles waiting to enter the travel-lane using object-detectors before the host-vehicle reaches their location. The controller then proactively adjusts the host-vehicle's motion (speeding up or slowing down) to create a gap in traffic before the other-vehicle needs to enter, rather than reacting after congestion has formed. This preliminary action resolves the contradiction by enabling other-vehicles to enter smoothly while maintaining overall travel efficiency through coordinated motion adjustments.
2Ease of operation
If the host-vehicle adjusts its motion to create gaps for other-vehicles to merge, then entry ease for other-vehicles is improved, but the host-vehicle's travel time increases
Solution Approach 1:
The system dynamically adjusts the host-vehicle's motion vector based on real-time detection of other-vehicles and traffic conditions. The controller continuously modifies speed and position to create optimal merge gaps, then returns to the original trajectory. This dynamic adjustment minimizes travel time loss by only deviating when necessary and for the minimum duration required to facilitate safe merging, rather than maintaining reduced speed continuously.
Solution Approach 2:
The object-detectors provide continuous feedback about other-vehicles waiting to enter and traffic density conditions. The controller uses this feedback to determine when and how to adjust the motion vector, monitoring the effectiveness of each adjustment. This feedback loop ensures that motion adjustments are made only when beneficial, optimizing the balance between facilitating merges and maintaining travel efficiency.
3Measurement precision
If the system uses multiple sensors and detection methods to accurately identify other-vehicles and traffic conditions, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system merges data from multiple object-detectors (cameras, radar, LIDAR) and V2X communication sources into a unified detection framework. The controller integrates information about other-vehicle positions, speeds, and intentions from these diverse sources to make coordinated motion decisions. This merging approach achieves high detection accuracy by combining complementary sensor data while managing complexity through integrated processing rather than separate independent systems.
Data Source
AI summary
A cooperative-vehicle system suitable to operate an automated vehicle in a courteous or cooperative manner includes an object-detector and a controller. The object-detector is used by the host-vehicle to detect an other-vehicle attempting to enter a travel-lane traveled by the host-vehicle. The controller is in communication with the object-detector. The controller is configured to control motion of the host-vehicle. The controller is also configured to adjust a present-vector of the host-vehicle to allow the other-vehicle to enter the travel-lane. The decision to take some action to allow the other vehicle to enter the travel-lane may be further based on secondary considerations such as how long the other-vehicle has waited, a classification of the other-vehicle (e.g. an ambulance), an assessment of how any action by the host-vehicle would affect nearby vehicles, the intent of the other-vehicle, and/or a measure traffic-density proximate to the host-vehicle.