Developing Better Curb Management Strategies through Understanding Commercial Vehicle Driver Parking Behavior in a Simulated Environment
| 项目名称： | Developing Better Curb Management Strategies through Understanding Commercial Vehicle Driver Parking Behavior in a Simulated Environment |
| 摘要： | As e-commerce and urban deliveries spike, there is an increasing demand for curbside loading/unloading space. At the same time, cities grapple with managing urban freight more actively, and need to better understand commercial vehicle (CV) driver behaviors and factors affecting their parking decisions. CV drivers face numerous challenges and have to adopt different travel and parking behaviors to perform deliveries and pick-ups efficiently. A recent study by the Urban Freight Lab (UFL) identified three main criteria CV drivers use when choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other road users, and competition with other CV drivers. UFL researchers also found that in response to the lack of available parking, drivers take one of the following actions: unauthorized parking, cruising for parking, queueing, and re-routing. The literature on decision-making process and parking behavior of CV drivers is scarce, and the data for such studies usually come from empirical field studies, while there are only limited situations that can be observed in existing situations, and even with those, driver characteristics remain mostly unknown. The proposed study will simulate several parking situations for CV drivers and analyze their reactions. The simulation will be designed in a quarter-cab truck simulator at Oregon State University. Various simulation environments will be defined by changing road characteristics (e.g. land use, number of travel lanes, nearby signals), curb allocations and their availability (e.g. paid parking, passenger and commercial load zones), and other road users. Drivers from various categories of age, gender, experience level (less experiences vs. seasoned) and goods type (documents, packages, or heavy goods) will be invited to operate the simulator and make a parking decision in a few simulated environments. The simulator can also monitor distraction (through eye tracking) and the stress level of drivers (through galvanic skin response) when making these decisions and interacting with other road users. Analyzing parking decisions and driver stress levels based on roadway and driver characteristics will provide insights on travel behaviors and the parking decision-making process of CV drivers, and will help city planners develop better curb management policies to accommodate safe and efficient operations in a shared urban roadway environment. |
| 状态： | Active |
| 资金： | 360000 |
| 资助组织： | Pacific Northwest Transportation Consortium<==>Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Goodchild, Anne |
| 执行机构： | University of Washington, Seattle<==>Oregon State University, Corvallis |
| 开始时间： | 20210316 |
| 预计完成日期： | 20220315 |
| 主题领域： | Freight Transportation；Operations and Traffic Management；Safety and Human Factors |
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