Highway Construction Productivity Measurement with a Wireless Real-Time Productivity Measurement System

Improving the quality of construction schedules calls for development of an advanced productivity measurement system. Existing on-site construction productivity measurement methods have some common limitations, such as not providing data necessary for engineers and project managers to conduct real-time analyses and share data with other project participants. A wireless real-time productivity measurement (WRITE) system was developed to address those shortfalls. The field experiment was conducted at two different stages: asphalt paving projects, including hot-mix asphalt and hot-in-place recycling, and a bridge reconstruction project. Productivity data collected from the WRITE system were also compared with productivity data collected from construction documents, such as contractors\u27 daily logs and pay estimate documents, to identify the feasibility of this system for measuring the performance of construction projects. For data analyses, statistical methods such as normality test, paired t-test, and Wilcoxon signed-rank test were used. The result of statistical analyses proved that the developed system generated identical productivity measurements compared with the stopwatch method and construction documents. The success of this research project made several major contributions to the advancement of the construction industry. First, the research advanced the application of wireless technology in highway construction operations. Second, it provided an advanced technology for engineers and project managers to determine productivity in real time. Third, productivity data can be shared between project participants via the Internet. With these advancements, communication and coordination will be improved at construction sites. Consequently, the WRITE system will enhance owners\u27 and contractors\u27 ability to manage construction projects

A Multi-Agent Driving-Simulation Approach for Characterizing Hazardous Vehicle Interactions between Autonomous Vehicles and Manual Vehicles

The advent of autonomous vehicles (AVs) in the traffic stream is expected to innovatively prevent crashes resulting from human errors in manually driven vehicles (MVs). However, substantial safety benefits due to AVs are not achievable quickly because the mixed-traffic conditions in which AVs and MVs coexist in the current road infrastructure will continue for a considerably long period of time. The purpose of this study is to develop a methodology to evaluate the driving safety of mixed car-following situations between AVs and MVs on freeways based on a multi-agent driving-simulation (MADS) technique. Evaluation results were used to answer the question ‘What road condition would make the mixed car-following situations hazardous?’ Three safety indicators, including the acceleration noise, the standard deviation of the lane position, and the headway, were used to characterize the maneuvering behavior of the mixed car-following pairs in terms of driving safety. It was found that the inter-vehicle safety of mixed pairs was poor when they drove on a road section with a horizontal curve length of 1000 m and downhill slope of 1% or 3%. A set of road sections were identified, using the proposed evaluation method, as hazardous conditions for mixed car-following pairs consisting of AVs and MVs. The outcome of this study will be useful for supporting the establishment of safer road environments and developing novel V2X-based trafficsafetyinformation content that enables the enhancement of mixed-traffic safety