Automated Radius Calculation of a Turn for Navigation and Safety Enhancement in Automobiles

Gnanasaekaran, K.; Kanya, S.; Suresh, B.; Vasudevan, Shriram K.

doi:10.1007/978-3-319-23036-8_28

Cited by 1 publication

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For turning vehicles, however, the tasks are complicated since the geographical trajectory planning and calculation should generate both speed/acceleration and turning angle profiles, which needs to determine the turning pattern and the turning radius first. In this stage, the variety in vehicle sizes [21], planning algorithms [22], intersection geometric property [23][24][25], and desired turning speeds [21,26,27] directly leads to different turning patterns and radiuses, referring to variation in both vehicle position and speed trajectories. In the trajectory tracking and maneuvering, the speed and turning angle are required to be adjusted simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Simulation-Based Evaluation of Variation in Left-Turn Paths in the Coordinated Intersection Management

Yang

Bai

2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

Coordinated intersection management (CIM) has gained more attention with the advance of connected and autonomous vehicle technology. The optimization of passing schedules and conflict separation between conflicting vehicles are usually conducted based on the predefined travelling paths through the intersection area in the CIM. In real-world implementation, however, the diversity of turn paths exists due to multiple factors such as various vehicle sizes and automation control algorithms. The aim of this paper is to investigate how the variation in left-turn paths affects the feasibility and viability of optimal passing schedules, as well as the safety and efficiency of intersection operation. To do this, we start with identifying six typical left-turn paths to represent the variation. A scenario-based simulation is first conducted by using each of the paths as the nominal path. The optimal schedules and the corresponding alternative schedules are generated to calculate indicators for nominal performance, average performance, and robustness. The best path is selected in terms of schedule optimality and robustness. With schedules obtained by solving CIM models using the selected path, the left-turning CAVs are assumed to travel along one of the six paths randomly to simulate the path divergence. A surrogate safety measure, PET, is utilized to assess the safety of the intersection under CIM. The theoretical PET with the nominal path and the actual PET with the random path are calculated for each conflict event. Comparisons of two PET sets show the increase in conflict risk and vehicle delay. The conclusion can be drawn that the variation in left-turn paths causes the decline in safety level and travelling efficiency and should be considered in the CIM model to ensure safe and efficient implementation in the intersection.

show abstract