90 results about "Requirements elicitation" patented technology

The invention relates to a bionics-based automatic driving vehicle operation control method. The method makes collective behaviors be in analogy with vehicle operation control on the basis of bionics principles, and the method comprises the following steps that 1, each individual vehicle is defined as a decision vehicle, and demands of the decision vehicles themselves are obtained; 2, an optimal individual is found through decision vehicle V2V communication and defined as a target vehicle, the optimal individual is configured to be the vehicle which is the best in current operation state in vehicle groups with the same demands as the decision vehicles; 3, operation strategies of the decision vehicles are obtained according to the positions between the target vehicles and the decision vehicles and demands of the vehicles in front of the decision vehicles. Compared with the prior art, by means of the bionics-based automatic driving vehicle operation control method, the vehicles can achieve the demand target rapidly within 30 seconds and run in a stable vehicle fleet mode, the time-space source fragmentation degree is lowered, the road access capacity is effectively improved, and the automatic driving vehicle can efficiently operate in a clustering mode in an Internet of Vehicles environment.

The invention discloses a data-driven urban road network traffic zone multi-level division method. The method comprises the following steps: S1, clearing out a division region, and acquiring travelingdata of the division region, wherein the travelling data comprises origin-destination attribute information of the traveling; S2, extracting effective traveling data in combination with an actual demand through the traveling data of the S1; S3, counting a traveling origin-destination pair and the corresponding traveling quantity based on the effective traveling data; S4, constructing a travellingnetwork of the division region by applying the traveling origin-destination pair and the corresponding traveling quantity data; and S5, performing traffic zone division on the division region by applying the community discovery algorithm by combining the traveling network of the S4. Based on the traveling data, the data size is large, the research space-time range is large, and the traveling activity of the whole urban road network can be comprehensively and really reflected, the analysis result is more real; secondly, the corresponding traveling data is acquired according to actual demand to accomplish the multi-level dynamic division of the specific traffic zone, and the flexibility and the pertinence of the method are strong.