Combined Scheduling and Control Design for the Coordination of Automated Vehicles at Intersections

Kneissl, Maximilian; Molin, Adam; Kehr, Sebastian; Esen, Hasan; Hirche, Sandra

doi:10.1016/j.ifacol.2020.12.2316

Cited by 4 publications

(5 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The approach in this article also depends on a pre-defined vehicle sequence decision. Therefore, we apply a scheduling problem (resource-constraint-project-scheduling) to compute this sequence, which has been introduced in [24] and suggests a trade-off between optimality and scalability of the solution.…”

Section: A Related Workmentioning

confidence: 99%

“…In the article, this is envisioned to be provided by a central infrastructure node as illustrated in Fig. 3 and discussed in [24]. Alternatively, distributed sequence decisions could replace the central infrastructure node.…”

Section: Multi-vehicle Coordination Formulationmentioning

confidence: 99%

“…To decompose these, we repeat respective coupling constraints in each coupled local sub-system and move the integer decision (11h) to the central infrastructure node. A scheduling-based method where m is computed in an approximate way given vehicles' trajectories is presented in [24]. In the following we will assume a given integer decision m, i.e., the order in which vehicles cross CZ k .…”

Section: Distributed Coordination Modelmentioning

confidence: 99%

“…2) Scalability: The standard JOR algorithm requires a centralized update step (24). Moreover, through the condition ř Nv i"1 ω i " 1 the speed of convergence depends on the number of vehicles in the network G.…”

Section: Algorithmic Propertiesmentioning

confidence: 99%

“…For each of the 200 test cases five different control methods are simulated: (i) overpass, where no interaction between vehicles is required; (ii) centralized: the result (11) with a given decision m; (iii) Jacobi 4´iter, applying problems (18) with Algorithm 1 and l max " 4; (iv) Jacobi 1´iter, the same as (iii) with l max " 1; and (v) traffic rules, where vehicles have to yield the rightof-way which in these scenarios is the case for left turns (if two vehicles want to turn left at the same time lane E is prioritized). The crossing sequence in (ii), (iii), and (iv) is computed according the scheduling rule introduced in [24]. Fig.…”

Section: B Coordination Performance In An Intersection Crossing Scenariomentioning

confidence: 99%

See 4 more Smart Citations

Any-Time Feasible Coordination for Multivehicle Systems

Kneissl

Molin

Esen

et al. 2022

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

This article proposes a distributed control methodology for the coordination of multiple connected and automated vehicles (CAVs). Each vehicle computes its local trajectory based on a model predictive control (MPC) law and communicates the result with other relevant vehicles. In an iterative negotiation process, planned trajectories are optimized within a sampling time step. Inspired by the Jacobi over-relaxation (JOR) algorithm, we develop a distributed Jacobi over-relaxation algorithm (DJOR) for vehicle coordination. The modified algorithm exploits the structure of the distributed problem setting in which coupling occurs only in a bilateral way. Besides being able to guarantee any-time feasibility that implies collision-freeness, the algorithm scales well, unlike the standard JOR algorithm. The DJOR algorithm allows for significantly less conservatism in the choice of the update weightings. As a result, much faster convergence rates can be expected. Furthermore, the collision avoidance guarantee is extended for unforeseen scenarios such as emergency braking. Using an exact penalty function formulation ensures that the distributed optimization problem remains feasible even in previously unforeseen cases. Numerical simulations of an intersection crossing scenario illustrate the presented approach and show its benefits in comparison with standard traffic rules and a centralized computation.

show abstract

Section: A Related Workmentioning

confidence: 99%

Section: Multi-vehicle Coordination Formulationmentioning

confidence: 99%

Section: Distributed Coordination Modelmentioning

confidence: 99%

Section: Algorithmic Propertiesmentioning

confidence: 99%

Section: B Coordination Performance In An Intersection Crossing Scenariomentioning

confidence: 99%

See 3 more Smart Citations

Any-Time Feasible Coordination for Multivehicle Systems

Kneissl

Molin

Esen

et al. 2022

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

A distributed trajectory control strategy for the connected automated vehicle in an isolated roundabout

Jia

Yang

et al. 2021

IET Intelligent Trans Sys

View full text Add to dashboard Cite

This paper develops a distributed cooperative control strategy (DCCS) to plan and optimize the collision-free trajectory for the connected automated vehicle (CAV) at an isolated roundabout. The representation of the trajectories of CAVs is defined within a roundabout. The central angle and lane radius are used to indicate the location of vehicles, and the corresponding angular velocity is used to describe the vehicle's speed through the roundabout. This trajectory definition method simplifies the proposed problem into two parts: the trajectory optimization of each vehicle in a specific lane and the lane change coordination of CAVs in the roundabout. To solve the trajectory optimization problem, a mixed-integer linear programming (MILP) model is formulated at the vehicle level to minimize the travel time and make the trajectory as smooth as possible. A model predictive control (MPC) framework is designed to coordinate lane-change conflicts and push CAVs' trajectories toward global optimization. The proposed framework integrates the vehicles' trajectory optimization results so that all CAVs reach a consensus. Numerical experiments test the effect of the strategy in terms of traffic efficiency and mobility performance under different demand pattern scenarios. The results show that the proposed RA-DCCS (Roundabout-DCCS) can make all CAVs smooth and conflict-free trajectories and enable vehicles to execute reasonable lane change decisions.

show abstract