Accurate traffic speed forecasting not only can help traffic management departments make better judgments and improve the efficacy of road monitoring but also can help drivers plan their driving routes and arrive safely and smoothly at their destination. This paper focuses on the lack of traffic speed data and proposes a method for traffic speed forecasting based on the multitemporal traffic flow volume of the previous and later moment states. First, according to traffic flow volume data, the different traffic patterns of previous and later moment states were extracted. Second, the performance of five forecasting models, namely, long short-term memory (LSTM), backpropagation (BP), classification and regression trees, k-nearest neighbor, and support vector regression, were compared. Finally, the model with the best prediction results was used to conduct sensitivity analysis experiments for different traffic patterns. Through a real-data case study, we found that the LSTM model has the highest prediction accuracy compared to other models in both time and space. This traffic pattern "previous = 3 and later = 3" can forecast traffic speed more accurately, and its forecasting ability is robust across a range of scenarios.
The huge waste of urban road resources caused by large turning radii of intersections has become a universal concern in traffic engineering. Here, an approach for determining curb radius at intersections is proposed using lateral acceleration to reflect ride perceptions, bringing human-oriented concepts into urban intersection design. First, we classified three kinds of ride perceptions into comfortable/uncomfortable but acceptable/unacceptable, after which the lateral acceleration and ride perceptions were obtained by ride perception experiments. The lateral acceleration critical values for each ride perception were obtained using the Raff critical gap method. Finally, we calculated the intersection curb radius based on the critical values, and verified vehicle safety under the recommended intersection curb radius. The results showed that the intersection curb radius based on the proposed approach was less than the specified value and safety was verified, indicating that enormous land resources could be saved were this methodology applied to intersection design.
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