Abstract
Weaving sections are components of highway networks that introduce a heightened likelihood for bottlenecks and collisions. Automated vehicle technology could address this as it holds considerable promise for transportation mobility and safety improvements. However, the implications of combining automated vehicles (AuVs) with traditional human-driven vehicles (HuVs) in weaving freeway sections have not been quantitatively measured. To address this gap, this paper objectively experimented with bidirectional (i.e., longitudinal and lateral) motion dynamics in a microscopic modeling framework to measure the mobility and safety implications for mixed traffic movement in a freeway weaving section. Our research begins by establishing a multilane microscopic model for studied vehicle types (i.e., AuV and HuV) from model predictive control with the provision to form a CACC platoon of AuV vehicles. The proposed modeling framework was tested first with HuV only on a two-lane weaving section and validated using standardized macroscopic parameters from the Highway Capacity Manual. This model was then applied to incrementally expand the AuV share for varying inflow rates of traffic. Simulation results showed that the maximum flow rate through the weaving section was attained at a 65% AuV share. At the same time, steadiness in the average speed of traffic was experienced with increasing AuV share. The results also revealed that a 95% AuV share could reduce potential conflicts by 94.28%. Finally, the results of simulated scenarios were consolidated and scaled to report expected mobility and safety outcomes from the prevailing traffic state and the optimal AuV share for the current inflow rate in weaving sections.
Highlights
Numerous studies have established the eminence of mixed traffic over traditional traffic systems from mobility, safety, and environmental perspectives, the exploration of coexistence is primarily limited to partial motion dynamics, most often car-following strategy, of studied vehicle groups [9,10,11,12]. is limitation is significant since both traffic operational and regulatory authorities must base their strategic investment and policy and legislative decision-making on sound, objective facts regarding integrating AVs with conventional traffic systems
Motivated by this gap in knowledge, this research, as part of a broader study, addresses the following question: how can the mobility and safety of varying traffic states in a multilane weaving section be influenced by the shared presence of automated vehicles (AuVs) and human-driven vehicles (HuVs)? e two-fold Journal of Advanced Transportation objective of this descriptive research includes the following: (i) contriving a comprehensive and realistic modeling framework of mixed traffic with bidirectional motion dynamic and (ii) quantifying and clarifying the causal connection between the presence of AuVs in traffic with a potential shift in mobility and safety benchmarks for a weaving section
The study outcomes can benefit research communities and industries actively committed to intelligent transportation systems and presume that AuVs will play a significant role in overcoming flow efficiency limitations and crash likelihood. e demand for understanding the implications of AuV substantiates the need for more comprehensive research from the mobility and safety perspective. ese perspectives play critical roles in measuring transportation system performance and the effects of mixed traffic on planning decisions
Summary
Despite real-world pilots of AuVs and the significant advancement in knowledge on this technology, large-scale deployment of AuVs in contemporary traffic streams is not readily achievable, making much of the existing literature that studies the effects of mixed traffic reliant on traffic simulation. Model predictive control (MPC)-based microscopic traffic dynamic has been adopted in few studies to simulate AuV motion. Ese studies provided valuable insights about roadway capacity changes of mainstream traffic resulting from mixed traffic flow at varying market shares, few explicitly explores the influence of integrating AuVs into freeway weaving sections. Ye and Yamamoto [35, 36] conducted studies on heterogenous traffic flow and concluded that the resulting capacity improvements depend largely on AuV market penetration and car-following parameters. While the desired headway of an individual vehicle would be fixed (with some exceptions for forced mandatory lane-changing) throughout the simulation period, the parameter would follow a log-normal distribution for the overall HuV proportion of traffic.
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