Abstract
AbstractThis paper presents a bi‐level model to optimize automated‐vehicle‐friendly subnetworks in urban road networks and an efficient algorithm to solve the model, which is relevant for the transition period with vehicles of different automation levels. We formulate the problem as a network design problem, define solution requirements, present an effective solution method that meets those requirements, and compare its performance with two other solution algorithms. Numerical examples for network of Delft are presented to demonstrate the concept and solution algorithm performances. Results indicate that our proposed solution outperforms competing ones in all criteria considered. Furthermore, our findings show that the optimal configuration of these subnetworks depends on the level of demand; lower penetration rates of automated vehicles call for less dense subnetworks, and thereby less investments. Nonetheless, a large proportion of benefits are already achievable with low‐density subnetworks. Denser subnetworks can deliver higher benefits with higher penetration rates.
Highlights
Automated driving (AD) is a trend that will evolve over time, both in the market penetration rate of automated vehicles (AVs) and the level of automation
This paper presents a bi-level model to optimize automated-vehicle-friendly subnetworks in urban road networks and an efficient algorithm to solve the model, which is relevant for the transition period with vehicles of different automation levels
Link travel time is based on a modified Bureau of Public Roads (BPR) function where the total flow is a weighted sum of class-specific flows to capture the correlation between link capacity and the proportion of AVs on the link
Summary
Automated driving (AD) is a trend that will evolve over time, both in the market penetration rate of automated vehicles (AVs) and the level of automation. In order to facilitate safe and efficient AD in mixed traffic on these selected roads, investments are required to ensure that they meet the desirable design standards (e.g., machine-readable and uniform lane markings and road signs, high surface quality, digital maps, and I2V communication infrastructure); there will be trade-offs between these investments and the benefits they provide. This necessitates a network design approach to decide which roads should be selected to facilitate AD in the transition period, and to assess the impacts of this selection. The rest of this manuscript is organized as follows: Section 2 provides a brief background for the problem; Section 3 introduces the concept of subnetworks for AD and the problem formulation; Section 4 describes solution algorithms; two case studies and numerical results are presented in Section 5; and Section 6 includes the discussion and concluding remarks
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