Bicycling is an important way for college students and employees to get around campuses. With a rise in bicycling on campuses there comes a rise in bicycle collisions with pedestrians walking to and from classes and w...Bicycling is an important way for college students and employees to get around campuses. With a rise in bicycling on campuses there comes a rise in bicycle collisions with pedestrians walking to and from classes and work. The literature review showed many papers involving bicycle conflict modeling but on roads with motor vehicles. While some aspects of this research can be applied to non-motorized paths, there is a lack of research strictly focusing on only bicycles and pedestrians. This study aims to fill this knowledge gap by developing a model to identify locations on roads and paths (hotspots) on college campuses that are likely to have a bicycle collision and predict the likelihood of a serious bicycle crash on a non-motorized path based on the characteristics of the path. This study identifies those interactions between bicyclists and pedestrians on non-motorized paths on a suburban college campus in Newark, USA. Findings suggest that pedestrian density of a path is a major factor in the maximum speed bicyclists can achieve. The wider the path is, the higher the maximum speed is that a bicyclist can obtain. This is because a wider path width decreases the pedestrian density. The grade of the path has little effect on bicycle speeds. The results of the models were displayed on a GIS map that is visually appealing to a viewer. The paths were color coded based on their level of safety, so it is easy to observe problematic areas of the network. This technique can be applied to the entire campus network of non-motorized paths to study the whole system. This can then be used by planners and designers to identify areas that need upgrading and improve the overall safety of the non-motorized path system.展开更多
针对自动化集装箱码头上自动引导车(automated guided vehicle,AGV)数量增加导致冲突更频繁。提出一种改进的基于冲突的搜索(conflict based search,CBS)算法。底层采用基于曼哈顿距离的A算法,上层结合二叉树原理建立冲突树对AGV之间的...针对自动化集装箱码头上自动引导车(automated guided vehicle,AGV)数量增加导致冲突更频繁。提出一种改进的基于冲突的搜索(conflict based search,CBS)算法。底层采用基于曼哈顿距离的A算法,上层结合二叉树原理建立冲突树对AGV之间的冲突进行规避。以最小化AGV在岸桥和堆场之间的总路径长度为目标,使用栅格法建立AGV路网模型。考虑AGV之间的点冲突与边冲突,将自动化码头多AGV无冲突路径规划问题规约为多智能体寻径问题。实验结果表明,所提出的算法在保证堵塞率为0%的前提下,缩短总路径长度并提高运算速度,验证算法的有效性。展开更多
文摘Bicycling is an important way for college students and employees to get around campuses. With a rise in bicycling on campuses there comes a rise in bicycle collisions with pedestrians walking to and from classes and work. The literature review showed many papers involving bicycle conflict modeling but on roads with motor vehicles. While some aspects of this research can be applied to non-motorized paths, there is a lack of research strictly focusing on only bicycles and pedestrians. This study aims to fill this knowledge gap by developing a model to identify locations on roads and paths (hotspots) on college campuses that are likely to have a bicycle collision and predict the likelihood of a serious bicycle crash on a non-motorized path based on the characteristics of the path. This study identifies those interactions between bicyclists and pedestrians on non-motorized paths on a suburban college campus in Newark, USA. Findings suggest that pedestrian density of a path is a major factor in the maximum speed bicyclists can achieve. The wider the path is, the higher the maximum speed is that a bicyclist can obtain. This is because a wider path width decreases the pedestrian density. The grade of the path has little effect on bicycle speeds. The results of the models were displayed on a GIS map that is visually appealing to a viewer. The paths were color coded based on their level of safety, so it is easy to observe problematic areas of the network. This technique can be applied to the entire campus network of non-motorized paths to study the whole system. This can then be used by planners and designers to identify areas that need upgrading and improve the overall safety of the non-motorized path system.
文摘针对自动化集装箱码头上自动引导车(automated guided vehicle,AGV)数量增加导致冲突更频繁。提出一种改进的基于冲突的搜索(conflict based search,CBS)算法。底层采用基于曼哈顿距离的A算法,上层结合二叉树原理建立冲突树对AGV之间的冲突进行规避。以最小化AGV在岸桥和堆场之间的总路径长度为目标,使用栅格法建立AGV路网模型。考虑AGV之间的点冲突与边冲突,将自动化码头多AGV无冲突路径规划问题规约为多智能体寻径问题。实验结果表明,所提出的算法在保证堵塞率为0%的前提下,缩短总路径长度并提高运算速度,验证算法的有效性。
