Deployment of Leader-Follower Automated Vehicle Systems for Smart Work Zone Applications with a Queuing-based Traffic Assignment Approach. (arXiv:2308.03764v1 [eess.SY])

The emerging technology of the Autonomous Truck Mounted Attenuator (ATMA), a
leader-follower style vehicle system, utilizes connected and automated vehicle
capabilities to enhance safety during transportation infrastructure maintenance
in work zones. However, the speed difference between ATMA vehicles and general
vehicles creates a moving bottleneck that reduces capacity and increases queue
length, resulting in additional delays. The different routes taken by ATMA
cause diverse patterns of time-varying capacity drops, which may affect the
user equilibrium traffic assignment and lead to different system costs. This
manuscript focuses on optimizing the routing for ATMA vehicles in a network to
minimize the system cost associated with the slow-moving operation.

To achieve this, a queuing-based traffic assignment approach is proposed to
identify the system cost caused by the ATMA system. A queuing-based
time-dependent (QBTD) travel time function, considering capacity drop, is
introduced and applied in the static user equilibrium traffic assignment
problem, with a result of adding dynamic characteristics. Subsequently, we
formulate the queuing-based traffic assignment problem and solve it using a
modified path-based algorithm. The methodology is validated using a small-size
and a large-size network and compared with two benchmark models to analyze the
benefit of capacity drop modeling and QBTD travel time function. Furthermore,
the approach is applied to quantify the impact of different routes on the
traffic system and identify an optimal route for ATMA vehicles performing
maintenance work. Finally, sensitivity analysis is conducted to explore how the
impact changes with variations in traffic demand and capacity reduction.



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