A Combinatorial Dynamic Network Trajectory Reservation Algorithm for Connected Autonomous Vehicles

We present a combinatorial assignment algorithm for reserving space-time trajectories from origins to destinations given an ordered list of vehicles. Space-time trajectories include guaranteed arrival times at every node in the path, including at the destination. Traffic flows are modeled using the...

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Bibliographic Details
Published inNetworks and spatial economics Vol. 19; no. 1; pp. 27 - 55
Main Author Levin, Michael W.
Format Journal Article
LanguageEnglish
Published New York Springer US 01.03.2019
Springer Nature B.V
Subjects
Algorithms
Autonomous vehicles
Civil Engineering
Combinatorial analysis
Constraint modelling
Economic activity
Economics
Economics and Finance
Operations Research/Decision Theory
Regional/Spatial Science
Spacetime
Traffic models
Trajectories
Travel time
Vehicles
Trajectory reservation
Dynamic traffic assignment
Cell transmission model
Autonomous vehicles
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Summary:We present a combinatorial assignment algorithm for reserving space-time trajectories from origins to destinations given an ordered list of vehicles. Space-time trajectories include guaranteed arrival times at every node in the path, including at the destination. Traffic flows are modeled using the cell transmission model, a Godunov approximation to the kinematic wave model. Space-time trajectories are constructed to follow the cell transmission model constraints and first-in-first-out behavior. Reservation-based intersection control for connected autonomous vehicles, which determines intersection access and delays for individual vehicles, is used to ensure that reserved trajectories are followed. The algorithm is suitable for city networks. Results show that vehicles with higher priority tend to have much lower travel times. In addition, the trajectory reservation system reduced overall congestion in the network compared with dynamic user equilibrium assignments.
ISSN:1566-113X
1572-9427
DOI:10.1007/s11067-018-9422-1