Abstract
There have a large number of pedestrian-vehicle accidents on the pedestrian crossing area in China every year, causing huge loss of life and property. In view of different road conditions, it's crucial to establish a more accurate crossing intention recognition model to improve the safety of pedestrians. In this work, a pedestrian crossing area was chosen. Due to construction reasons, two road conditions appeared in the same crossing area at different periods, namely a condition with a zebra crossing and that without a zebra crossing. We compared pedestrian crossing intention parameters under two road conditions in the same crossing area. The results found that there was a great difference in the characterization parameters of pedestrian crossing intention when the site with and without a zebra crossing. Additionally, a more comprehensive crossing intention characteristic parameters set was established. The characteristic parameters were pedestrian speed, the distance between vehicle and crossing area, time to collision (TTC), and safe vehicle deceleration (SVD), pedestrian age, pedestrian gender, group, respectively. The pedestrian intention recognition model for the site with a and without a zebra crossing were established by long short-term memory network integrated with the attention mechanism (AT-LSTM). When the model recognized pedestrian crossing intention 0.6 seconds in advance, the recognition accuracies were 93.05% and 93.89% respectively. The research results are of great significance for improving the safety of autonomous vehicles in the future, and there are also important to improve pedestrian safety.
Highlights
In recent years, with the rapid development of China's economy and the continuous improvement of its urbanization level, its urban skeleton has continued to expand and its road networks have continued to extend; simultaneously, residents' consumption ability has been constantly enhanced, and the number of motor vehicles continues to increase rapidly
According to the annual report on road traffic accident statistics released by the Traffic Administration Bureau of the Ministry of Public Security in 2017, the number of pedestrian walking injuries in traffic accidents accounted for 16.72% of all traffic-related injuries, and the number of injured pedestrians was 35,058
In this paper, the safe vehicle deceleration (SVD) and time to collision (TTC) were introduced based on original research, and it was found that both parameters can significantly affect pedestrian crossing intention
Summary
With the rapid development of China's economy and the continuous improvement of its urbanization level, its urban skeleton has continued to expand and its road networks have continued to extend; simultaneously, residents' consumption ability has been constantly enhanced, and the number of motor vehicles continues to increase rapidly. The construction of supporting facilities related to road traffic is relatively lagging, residents' awareness and experience of traffic safety are relatively insufficient, and the conflict between pedestrians and vehicles on the zebra crossing is becoming more and more serious. There are many zebra crossings without traffic signal control, and traffic accidents caused by pedestrians at these zebra crossings are common [1]. As a vulnerable group of traffic participants, pedestrians are the most susceptible to injury. The death toll accounted for 27.11% of all traffic-related deaths, with a total of 17,286 deceased pedestrians [2]
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