Two-dimensional vehicular movement modelling at intersections based on optimal control

Zhao, Jing; Knoop, Victor L.; Wang, Meng

doi:10.1016/j.trb.2020.04.001

Cited by 113 publications

(72 citation statements)

References 54 publications

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“…Previous studies optimized the trajectory of vehicles at the approach lanes whereas neglecting the trajectory inside the intersection [14], [27], [28]. Nonetheless, the trajectory inside the intersection is not only directly related to whether the vehicle will collide inside the intersection, but also affects the intersection efficiency [29]. Thus, the trajectory of CAVs in the approach lane and inside the intersection is optimized in this section.…”

Section: B Trajectory Optimizationmentioning

confidence: 99%

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Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Long

Jiang

et al. 2020

IEEE Access

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Section: B Trajectory Optimizationmentioning

confidence: 99%

“…(28) guarantees safe movements for vehicle and its predecessor vehicle ′. (29) and (30) are the limits of vehicle arrival states.…”

Section: B Trajectory Optimizationmentioning

confidence: 99%

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Long

Jiang

et al. 2020

IEEE Access

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“…[25] used Fosgerau's valuation method to calculate travel time reliability in costbenefit analysis. Zhao J et al [26] used optimal control theory to optimize intersection travel time. Reliability estimation model of travel time based on stochastic user equilibrium allocation model.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Routing for Dynamic Road Network Based on Travel Time Reliability

2020

Self Cite

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Vehicle path selection follows the shortest path principle, while taking the shortest travel time as the optimization goal. In the real road network, affected by signal control, the travel time of the vehicle path has significant uncertainty. The shortest path algorithm with static road indicators as the weights has obvious defects in path selection. In order to solve this problem, according to the theory of distributed wave, the operating state of the vehicle under the influence of the downstream signal control is classified. The travel time of the vehicle on the road segment is classified and predicted, and the travel time prediction value set is further transformed into the travel time reliability. For the vehicle route selection of a dynamic road network, the path travel time reliability determined by the product of the road segment travel time reliability is logarithmically converted, and the Dijkstra algorithm is used to find the most reliable path as the target solution. Then, a simulation model is constructed to verify the validity of the algorithm. The experimental results prove that using the reliability of travel time as the weight of path selection and solving by Dijkstra algorithm can reflect the actual vehicle path selection more accurately. This method is a beneficial improvement to the problem of static path selection. INDEX TERMS dynamic road network, path selection, signal control, traffic engineering, travel time reliability.

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“…They explained that the proposed method improves the traffic safety by providing a safe speed, enhances the fuel efficiency and reduces the emissions. A recent study deployed optimal control method, assuming that drivers maximize their utility, to model vehicle movements at intersections [22]. This approach also requires empirical data for calibration.…”

Section: Introductionmentioning

confidence: 99%

Modeling Trajectories and Trajectory Variation of Turning Vehicles at Signalized Intersections

et al. 2020

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Information on the trajectories of turning vehicles at signalized intersections can be used in numerous applications, such as movement planning of autonomous vehicles, realistic representation of surrounding vehicle movements in driving simulator and virtual reality applications, and in microscopic simulation tools. However, no proper framework is currently available to realistically model and estimate trajectories of turning vehicles reflecting the intersection geometries, which is critical for the reliability of simulation models. This study explores the applicability of the minimum-jerk principle, which has been initially applied in neuroscience and robotics domains, to model and simulate free-flow trajectories of turning vehicles. The modeling method is validated by comparing model outputs with empirical trajectories collected at several signalized intersections in Nagoya, Japan. The capability of the model in realistically capturing the variations in turning trajectories based on intersection geometry (e.g., intersection angle and turning radius) is also explained. Further, the applicability of the modeling framework at intersections with different geometric features under different speeds and accelerations are also discussed.

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Two-dimensional vehicular movement modelling at intersections based on optimal control

Cited by 113 publications

References 54 publications

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Integrated Optimization of Traffic Signals and Vehicle Trajectories at Intersection With the Consideration of Safety During Signal Change

Vehicle Routing for Dynamic Road Network Based on Travel Time Reliability

Modeling Trajectories and Trajectory Variation of Turning Vehicles at Signalized Intersections

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