Abstract:
The need to establish safe, accessible, and inclusive pedestrian routes is considered one of the European Union\'s main priorities. We have developed a method of assessing pedestrian mobility in the surroundings of urban public buildings to evaluate the level of accessibility and inclusion, especially for people with reduced mobility. In the first stage of assessment, artificial intelligence algorithms were used to identify pedestrian crossings and the precise geographical location was determined by deep learning-based object detection with satellite or aerial orthoimagery. In the second stage, Geographic Information System techniques were used to create network models. This approach enabled the verification of the level of accessibility for wheelchair users in the selected study area and the identification of the most suitable route for wheelchair transit between two points of interest. The data obtained were verified using inertial sensors to corroborate the horizontal continuity of the routes. The study findings are of direct benefit to the users of these routes and are also valuable for the entities responsible for ensuring and maintaining the accessibility of pedestrian routes.
摘要:
需要建立安全,可访问,和包容性的步行路线被认为是欧盟的主要优先事项之一。我们开发了一种评估城市公共建筑周围环境中行人流动性的方法,以评估可达性和包容性水平,特别是对于行动不便的人。在评估的第一阶段,人工智能算法用于识别行人过路,并通过基于深度学习的物体检测与卫星或航空正射图像确定精确的地理位置。在第二阶段,地理信息系统技术用于创建网络模型。这种方法可以验证选定研究区域中轮椅使用者的可及性水平,并确定两个兴趣点之间最合适的轮椅过境路线。使用惯性传感器对获得的数据进行了验证,以证实路线的水平连续性。研究结果对这些路线的使用者有直接的好处,对于负责确保和维护行人路线的可达性的实体也很有价值。