Insights from Driver Parking Decisions in a Truck Simulator to Inform Curb Management Decisions

Abstract

As e-commerce and urban deliveries spike, there is an increasing demand for curbside loading/unloading space. However, commercial vehicle drivers face numerous challenges while navigating dense urban road networks. Literature on the topic of how commercial vehicle drivers make choices about when and where to park is scarce, and data from those available studies usually come from field studies in which limited situations can be observed, without experimental controls, and there is an absence of known driver characteristics. Therefore, this study used a heavy vehicle driving simulator to examine the behavior of commercial vehicle drivers in various parking and delivery situations. A heavy vehicle driving simulator experiment examined the behaviors of commercial vehicle drivers under various parking and delivery situations. The heavy vehicle experiment was completed by 14 participants. The experiment included 24 scenarios with several independent variables, including number of lanes (two-lane and four-lane roads), with/without a bike lane, available/unavailable passenger vehicle parking space, CVLZs (no CVLZ, occupied CVLZ, and unoccupied CVLZ), and delivery time (3-5 mins and 20-60 mins). By collecting speed, eye-movement, and stress data during the experiment, the project produced results that support the development of more effective curb management strategies that will maintain efficient delivery operations while balancing the needs of all road users.