Design and Performance of Managed Lanes in a Mixed Driver-Operated and Autonomous Vehicle Environment

It is anticipated that as autonomous vehicles (AVs) are gradually adopted, there will be a mixed vehicle fleet containing AVs and driver-operated vehicles. Researchers have suggested using a dedicated lane facility to limit vehicle-to-vehicle interaction since it may affect freeway performance. Managed lanes (MLs), a form of dedicated lanes, can be used since their strategies can be adjusted based on traffic demand. Therefore, ML strategies and envelope designs may need reassessment. This study optimizes ML design strategies and evaluates the impact of these strategies on freeway performance at various AV adoption rates (i.e., 25%, 50%, and 75%) and traffic volume ratios. The vehicle types were AVs, DVs, and HGVs. The ML design strategies were based on vehicle eligibility, access control considerations, and orientation. The access control measures were left-side (S1) and right-side (S2) continuous access, and left-side (S3), and right-side (S4) restricted access. Each of these ML strategies varied based on AV adoption rates, traffic volume ratios and the number of MLs. A heterogeneous traffic environment was considered the base scenario (S0). The traffic performance and safety were evaluated by determining the relative average vehicle travel time and the number of traffic conflicts. The results of this study indicate that the geometric design for S1 and S3 should have a width that ranges from about 2.8 m to 3.6 m, while S2 and S4 should be kept at 3.6 m. The results also indicate that 800 m and 400 m are required as the minimum total lane change distance and ingress opening, respectively, for S3 regardless of the AV adoption rates, traffic volume ratios and number of MLs. At an AV adoption rate of 25% and 50%, a 600 m buffer opening should be added to the acceleration lane length regardless of the number of MLs. However, at 75% AV adoption rate, this buffer distance could be reduced by 50 m. The results also indicate that a ML may not be warranted at an AV adoption rate of 25% and 75%. However, at an AV adoption rate of 50%, one left-side continuous ML could be implemented for AVs.

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Engineering, Civil

Grantor dc:publisher

Carleton University

Year dc:date.issued

2023

Author dc:creator

• Sarran, Jana

Statement dc:rights

• Copyright © 2023 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, distribution to students, research and scholarship. Theses may only be shared by linking to the Carleton University Institutional Repository and no part may be copied without proper attribution to the author; no part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2023-15967

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/41290