Investigation of smart work zone technologies using mixed simulator and field studies

Abstract

Safety is the top concern in transportation, especially in work zones, as work zones deviate from regular driving environment and driver behavior is very different. In order to protect workers and create a safer work zone environment, new technologies are proposed by agencies and deployed to work zones, however, some are without scientific study before deployment. Therefore, quantitative studies need to be conducted to show the effectiveness of technologies. Driving simulator is a safe and cost-effective way to test effectiveness of new designs and compare different configurations. Field study is another scientific way of testing, as it provides absolute validity, while simulator study provides relative validity. The synergy of field and simulator studies construct a precise experiment as field study calibrates simulator design and validates simulator results. Two main projects, Evaluation of Automated Flagger Assistance Devices (AFADs), and Evaluation of Green Lights on Truck-Mounted Attenuator (TMA), are discussed in this dissertation to illustrate the investigation of smart work zone technologies using mixed simulator and field studies, along with one simulator project investigating interaction between human driven car and autonomous truck platoon in work zones. Both field and simulator studies indicated that AFADs improved stationary work zone safety by enhancing visibility, isolating workers from immediate traffic, and conveying clear guidance message to traffic. The results of green light on TMAs implied an inverse relationship between visibility/awareness of work zone and arrow board recognition/easy on eyes, but did not show if any of the light configurations is superior. Results anticipated for autonomous truck platoon in work zones are drivers behave more uniformly after being educated about the meaning of signage displayed on the back of truck, and performance measured with signage would be more preferable than those without signage. Applications of statistics are extension of studies, including experimental design, survey design, and data analysis. Data obtained from AFAD and Green Light projects were utilized to illustrate the methodologies of data analysis and model building, which incorporated simulator data, biofeedback and survey response to interpret the relationship among driver perspective and mental status, and driving behavior. From the studies conducted, it could be concluded that mixed simulator and field study is a good fit for smart work zone technologies investigation. Simulators provide a safe environment, flexibility and cost-effectiveness, while field studies calibrate and validate simulator setup and its results. The collaboration of two forms of study generates legitimate and convincing results for investigations. Applying statistical methodologies into transportation simulator and field studies is a good way to make experiment and survey design more rational, and the statistical methods are applicable for further data analysis.