Adaptive Cruise Control (ACC) vehicles have a longer reaction time, and the on-board sensors have a limited detection range that adversely affects the freeway bottleneck capacity. These limitations can cause small speed fluctuations into larger stop-and-go waves at typical freeway bottlenecks. Microsimulation results revealed that flow instability increases with the increase in ACC market penetration for a single lane freeway. The ACC car following model was developed for higher speed ranges only; thus, it could not capture rapid deceleration to lower speeds, let alone complete stops. The algorithm applies collision avoidance and brake relatively late in those instances, which leads to vehicles clustered closer together when at complete stops (or lower speeds). Therefore, the jam density increases with ACC market penetration. Simulation results also represented that no change in capacity was observed with the introduction of ACC vehicles on a freeway without diverging off-ramp and merging on-ramp demand compared to manually driven vehicles. The result is owed to the fact that lane changes and disturbances are not prominent without merging and diverging sections. However, the situation aggravates more for ACC vehicles when there is diverging off-ramp demand and merging on-ramp demand. The effect becomes severe with the increase of ACC market penetration. The field experiments for the fundamental characteristics of traffic flow showed that maximum capacity can be achieved when all the vehicles are operating in ACC mode. However, that maximum flow is unstable, and a minor speed variation can cause severe capacity drop. The jam density is also more in all ACC scenario that might result in rapid queue propagation as the wave speed is larger compared to the mixed driving scenario. / Includes bibliography. / Thesis (MS)--Florida Atlantic University, 2021. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_78742 |
| Contributors | Murshed, Md Tausif (author), Kan, David (Thesis advisor), Florida Atlantic University (Degree grantor), Department of Civil, Environmental and Geomatics Engineering, College of Engineering and Computer Science |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation, Text |
| Format | 93 p., application/pdf |
| Rights | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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