2013 Session: 729

2013 Session: 729

  • Multi-objective Optimization Model And Evolutionary Algorithm To Plan Uav Cruise Route For Road Traffic Surveillance
    Abstract: Unmanned Aerial Vehicle (UAV) was used to collect traffic information of road segments not installed with traffic detectors, therefore, it¡¯s necessary to plan UAV cruise route for traffic surveillance so as to minimize UAV cruise cost as much as possible. First, a multi-objective optimization model of planning UAV cruise route was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used respectively. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV cruise route planning problem. Next, a case using UAV to monitor 14 road segments near Tongji University in China was studied, the case results showed that optimized cruise distance and the number of UAVs used were reduced by 38.54% and 33.33% respectively compared to the initial optimal solutions, this demonstrated that the proposed evolutionary algorithm was feasible and effective. Finally, some discussions of using UAVs for traffic surveillance were given.
    Authors: Li, Li
    Authors: Li, Li
    Year: 2013
    Document Type: Paper
    Subject: Construction; Data and Information Technology; Design
    Session: 729
    Paper Number: 13-0735
  • Extracting 3d Transportation Features From Kinect Sensor Array Data
    Abstract: Three-dimensional modeling of transportation infrastructure assets such as roadways, bridges, signage, guard rails, etc., provide engineers an analysis framework that previously was too labor intensive and cost prohibitive to manually collect. The emerging industry standard for point cloud data collection is the use of either airborne or terrestrial based Light Detection and Ranging (LiDAR). The problem is that LiDAR hardware currently costs tens to hundreds of thousands of dollars and requires trained personnel to operate. Described within this paper are examples of how a low cost consumer grade electronic, the Microsoft Kinect sensor, can be used to collect point cloud data similar to terrestrial based LiDAR. For less than two hundred and fifty dollars, a Kinect sensor can be used by engineers to capture a wide range of transportation features such as bridge underpass heights, guard rail features, road signs, and the distance of the nearest roadside object. The approach presented herein automatically locates bridge under-passes with the Kinect Sensor, calculates the lowest clearance, and exports that data in an attributed GIS shapefile. In addition, guard rails and road signs can be identified and measured from Kinect sensor data.
    Authors: Hudnall, Matthew; Graettinger, Andrew J.
    Authors: Hudnall, Matthew; Graettinger, Andrew J.
    Year: 2013
    Document Type: Paper
    Subject: Construction; Data and Information Technology; Design
    Session: 729
    Paper Number: 13-2733