Sina Arefizadeh

SY
3papers
19citations
Novelty37%
AI Score19

3 Papers

SYOct 5, 2017
Collaborative Platooning of Automated Vehicles Using Variable Time-Gaps

Aria HasanzadeZonuzy, Sina Arefizadeh, Alireza Talebpour et al.

Connected automated vehicles (CAVs) could potentially be coordinated to safely attain the maximum traffic flow on roadways under dynamic traffic patterns, such as those engendered by the merger of two strings of vehicles due a lane drop. Strings of vehicles have to be shaped correctly in terms of the inter-vehicular time-gap and velocity to ensure that such operation is feasible. However, controllers that can achieve such traffic shaping over the multiple dimensions of target time-gap and velocity over a region of space are unknown. The objective of this work is to design such a controller, and to show that we can design candidate time-gap and velocity profiles such that it can stabilize the string of vehicles in attaining the target profiles. Our analysis is based on studying the system in the spacial rather than the time domain, which enables us to study stability as in terms of minimizing errors from the target profile and across vehicles as a function of location. Finally, we conduct numeral simulations in the context of shaping two platoons for merger, which we use to illustrate how to select time-gap and velocity profiles for maximizing flow and maintaining safety.

SYFeb 1, 2018
Assessing Strong String Stability of Constant Spacing Policy under Speed Limit Fluctuations

Sina Arefizadeh, Aria Hasanzadezonuzy, Alireza Talebpour et al.

The speed limit changes frequently throughout the transportation network, due to either safety (e.g., change in geometry) or congestion management (e.g., speed harmonization systems). Any abrupt reduction in the speed limit can create a shockwave that propagates upstream in traffic. Dealing with such an abrupt reduction in speed limit is particularly important while designing control laws for a platoon of automated vehicles from both stability and efficiency perspectives. This paper focuses on Adaptive Cruise Control (ACC) based platooning under a constant spacing policy, and investigates the possibility of designing a controller that ensures stability, while tracking a given target velocity profile that changes as a function of location. An ideal controller should maintain a constant spacing between successive vehicles, while tracking the desired velocity profile. The analytical investigations of this paper suggest that such a controller does not exist.

SYSep 28, 2017
Platooning in the Presence of a Speed Drop: A Generalized Control Model

Sina Arefizadeh, Alireza Talebpour, Igor Zelenko

The positive impacts of platooning on travel time reliability, congestion, emissions, and energy consumption have been shown for homogeneous roadway segments. However, speed limit changes frequently throughout the transportation network, due to either safety-related considerations (e.g., workzone operations) or congestion management schemes (e.g., speed harmonization systems). These abrupt changes in speed limit can result in shock- wave formation and cause travel time unreliability. Therefore, designing a platooning strategy for tracking a reference velocity profile is critical to enabling end-to-end platooning. Accordingly, this study introduces a generalized control model to track a desired velocity profile, while ensuring safety in the platoon of autonomous vehicles. We define appropriate natural error terms and the target curve in the state space of the control system, which is the set of points where all error terms vanish and corresponds to the case when all vehicles move with the desired velocities and in the minimum safe distance between them. In this way, we change the tracking velocity profile problem into a state- feedback stabilization problem with respect to the target curve. Under certain mild assumptions on the Lipschitz constant of the speed drop profile, we show that the stabilizing feedback can be obtained via introducing a natural dynamics for the maximum of the error terms for each vehicle. Moreover, we show that with this stabilizing feedback collisions will not occur if the initial state of the system of vehicles is sufficiently close to the target curve. We also show that the error terms remain bounded throughout the time and space. Two scenarios were simulated, with and without initial perturbations, and results confirmed the effectiveness of the proposed control model in tracking the speed drop while ensuring safety and string stability.