The distance before lane-changing greatly affects the road capacity, and the road capacity of the diversion area enhances by 9.6%-10.6% when the distance before lane-changing increases from 100 m to 150 m. The impact of the number of off-ramp lanes on the road capacity is not significant, and the road capacity of two off-ramp lanes improves by about 3%, compared with that of one off-ramp lane. The penetration rate of AVs on the main road has the most significant impact on the road capacity, and the road capacity under the environment with fully AVs is twice that under the environment with fully HVs.
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Analysis results show that the road capacity improves as the free lane-changing rate of off-ramp vehicles in the diversion area increases. On the basis of the variable distance before lane-changing, a strategy for improving the road capacity of the diversion area with mixed traffic flows was proposed. The influences of indicators including the free lane-changing rate and average distance before lane-changing of off-ramp vehicles were compared and analyzed under multi-factor coupling actions, and change rules of road capacity of the urban expressway diversion area were studied. The lane-changing simulation experiments in the diversion area were designed by considering the coupling influence of factors such as the penetration rate of AVs on the main road, proportion of large vehicles, penetration rate of off-ramp AVs, rate of off-ramp vehicles, number of off-ramp lanes, and distance before lane-changing. Paste to End 1.2.9.According to the mixed traffic flow characteristics of vehicles including different types of automatic vehicles (AVs) and human-driven vehicles (HVs) in the urban expressway diversion area under a vehicle-infrastructure cooperative environment, the dynamic acceleration and variable lane-changing probability were introduced to improve the traffic flow rules of a cellular automata model. Data Formats common to multiple Fields 2.4.1. Title/Songname/Content Description 2.1.27. Split the Filename using these words 3.4. Remove whitespace at start or end of value 2.4.3.2. Split into Words using these values 2.4.3. Ignore words in this list when matching 2.4.2.5. Match words that appear misspelt 2.4.2.2. Cross Referencing Correct - Correct Artists/Albums/Titles/Genres/Recording Times/Composers 2.4.1. It has the same MB Id and Acoustid as another song 2.2.2. It has the same MB Id and Album Id as another song 2.2.1.5. It has the same Acoustid as another song 2.2.1.4. It has the same MB Id, Album Id and Acoustid as another song 2.2.1.3. It has the same MB Id as another song 2.2.1.2. Remove from your MusicBrainz Collection 2. Add to your MusicBrainz Collection 1.20.8. Match Songs to MusicBrainz Album by Catno. Match Songs to MusicBrainz Album by Barcode. Match Songs to Specified MusicBrainz Album. Match Songs to one MusicBrainz Album 1.13.
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Manual Correct Metadata from MusicBrainz 1.9.1. Auto correct Metadata from MusicBrainz 1.7.1. How Does Jaikoz Use MusicBrainz and Acoustic Fingerprinting ? 1.6. View this Original Album at MusicBrainz 9.7. View this Album Group at MusicBrainz 9.5. Duplicate MusicBrainz Recording Id and Acoustid 6. MusicBrainz Recording Id does not Exist 5.4.
Duplicate MusicBrainz Recording Id 4.2.2.
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