Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes

Desiraju, Divya; Chantem, Thidapat; Heaslip, Kevin

doi:10.1109/tits.2014.2356932

Cited by 35 publications

(17 citation statements)

References 33 publications

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“…Desiraju et al discussed a technique to maximize the number of safe lane changes that can be made on a highway in a given time duration [28]. However, there is a lack of research on determining when, how, and why vehicles should make lane changes, especially while ensuring a high exit success percentage.…”

Section: Related Workmentioning

confidence: 99%

“…To accomplish this step, we leverage our previous work [28], which aimed to maximize the total number of successful lane changes. The main difference between this work and the previous work is that the latter made no attempt to coordinate the behaviors of the vehicles to achieve a common goal; it merely facilitates as many lane changes as possible without accounting for the fact that some vehicles may miss their destination exits.…”

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

“…The main difference between this work and the previous work is that the latter made no attempt to coordinate the behaviors of the vehicles to achieve a common goal; it merely facilitates as many lane changes as possible without accounting for the fact that some vehicles may miss their destination exits. In the original algorithm [28], a stretch of a highway is divided in a series of 3 contiguous-lane highways. For each 3-lane highway, only vehicles from the left and right lanes wishing to lane change into the center lane are considered.…”

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

“…We will rely on existing work [28] to ensure the safety of a given lane change given derived acceleration and velocity values. Since only non-conflicting VVs are selected to proceed with the actual lane changes and since vehicles in a given VV are guaranteed to not interfere with one another during lane changing, our proposed approach is guaranteed to be collision free.…”

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

See 3 more Smart Citations

Optimizing Departures of Automated Vehicles From Highways While Maintaining Mainline Capacity

Meissner

Chantem

Heaslip

2016

IEEE Trans. Intell. Transport. Syst.

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Automated vehicles have the potential to revolutionize our nation's transportation systems as they promise to dramatically reduce congestion, accidents, and fuel usage. Namely, as it becomes possible to precisely exert control on and coordinate the movement and placement of vehicles along a stretch of highway, the separation distance between vehicles can be reduced, thus increasing flow and minimizing congestion. Precise and coordinated vehicle controls and placements also improve predictability, resulting in fewer instances of sudden braking, which reduce fuel usage and accidents. Most existing research has focused on the steady-state behaviors and operations of automated vehicles, such as platooning, and assumes complete knowledge of the system, e.g., the number of vehicles and their destinations and/or neglects dynamic or transition operations such as exiting a highway and lane changing. Uncoordinated lane-changing and exiting behaviors by automated vehicles can significantly reduce the flow of traffic as vehicles will require larger separations, are forced to slow down, or worse, collide. In this paper, we present a collision-free runtime approach to efficiently organize the departures of automated vehicles from a highway environment while maintaining highway capacity in extremely dynamic conditions. To maximize the number of safe departures, the key ideas are to: 1) determine when, and where to, an exiting vehicle should lane change in order to make a successful exit given current traffic conditions as provided by connected vehicle technology and 2) execute the actual lane-change operations using a reservation-based approach. Simulation results show that, by coordinating vehicles' behaviors, traffic flow can be improved by up to five times of today's typical flow while ensuring a 100% exit success rate in a collision-free manner.

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Section: Related Workmentioning

confidence: 99%

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

Section: Phase 3-selecting Vehicles To Lane Changementioning

confidence: 99%

See 2 more Smart Citations

Optimizing Departures of Automated Vehicles From Highways While Maintaining Mainline Capacity

Meissner

Chantem

Heaslip

2016

IEEE Trans. Intell. Transport. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…They proposed a Progressively Constrained Dynamic Optimization (PCDO) method for solving the optimal control problem. In [12], authors have presented an algorithm to minimize the disruption of traffic flow and thus maximizing the number of lane changes. They used time slack calculation and the concept of vehicle grouping and used a distributed algorithm to solve the problem.…”

Section: Introductionmentioning

confidence: 99%

A Cooperative Algorithm for Lane Sorting of Autonomous Vehicles

2020

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In this paper, we propose a generalized algorithm that converts traffic composed of vehicles located randomly in a set of lanes into sorted traffic in which vehicles are moved into the lane corresponding to their destination group. Focus is placed on the cooperative behavior of vehicles. The proposed algorithm architecture divides the entire scenario into various independent sections (called frames) that can be processed in parallel at the same time. Processing each frame involves solving an optimization procedure of a nonlinear programming problem reducible to a linear programming problem. The performance of the proposed algorithm is tested using the Simulation of Urban MObility (SUMO) simulator. Results are obtained and presented for average sorting distance required for sorting all vehicles in the scenario for different traffic settings. INDEX TERMS Intelligent transportation system, lane sorting, linear programming, lane assignment, vehicle platooning.

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A probabilistic model for discretionary lane change proposals in highway driving situations

Schmidt

Wissing

Nattermann

et al. 2021

Forsch Ingenieurwes

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This contribution presents a novel probabilistic approach for the generation of discretionary lane change proposals with a focus on highway driving situations. The developed model is based on the quantification of the utility of driving lanes. It generates a lane change proposal if the current driving lane is unsatisfactory in the sense that the desired velocity of the automated vehicle is undershot because of a slow preceding vehicle. A driving simulator study was conducted to create a dataset for the optimization of the model parameters. The optimization goal is to accurately match the timings of the lane change intentions of all participants. Finally, the applicability of the model is shown on real data from a test vehicle.

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Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes

Cited by 35 publications

References 33 publications

Optimizing Departures of Automated Vehicles From Highways While Maintaining Mainline Capacity

Optimizing Departures of Automated Vehicles From Highways While Maintaining Mainline Capacity

A Cooperative Algorithm for Lane Sorting of Autonomous Vehicles

A probabilistic model for discretionary lane change proposals in highway driving situations

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