Study on the Controlled Field Test Scenarios of Automated Vehicles

Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA) problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

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Study on the Test Scenarios of Level 2 Automated Vehicles

2018 IEEE Intelligent Vehicles Symposium (IV) ◽

10.1109/ivs.2018.8500600 ◽

2018 ◽

Cited By ~ 1

Author(s):

Li Huang ◽

Qin Xia ◽

Fei Xie ◽

Hai-Lin Xiu ◽

Hong Shu

Keyword(s):

Automated Vehicles ◽

Test Scenarios ◽

Level 2

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A Conflict Duration Graph-Based Coordination Method for Connected and Automated Vehicles at Signal-Free Intersections

Applied Sciences ◽

10.3390/app10186223 ◽

2020 ◽

Vol 10 (18) ◽

pp. 6223

Author(s):

Zhiyun Deng ◽

Yanjun Shi ◽

Qiaomei Han ◽

Lingling Lv ◽

Weiming Shen

Keyword(s):

Automated Vehicles ◽

Coordination Model ◽

Vehicle Collision ◽

Conflict Duration ◽

Traffic Volumes ◽

Medium Level ◽

Coordination Framework ◽

Complex Constraints ◽

Design Speed ◽

Test Scenarios

Previous studies on Connected and Automated Vehicles (CAVs) demonstrated the potential to coordinate the behaviors of multiple connected vehicles for traffic improvements. In this paper, we first propose a Conflict Duration Graph-based (CDG-based) coordination framework to resolve collisions and improve the traffic capacity of signal-free intersections. Secondly, a Speed Control-based Intersection Coordination Model (SICM) is developed to identify complex constraints in multi-vehicle collision scenarios. Thirdly, a geometric Translation-based Intersection Coordination Algorithm (TICA) is proposed to calculate the ideal location of time blocks in CDGs and then obtain the near-optimal design speed in the form of combinatorial optimization. Twelve groups of test scenarios with different traffic volumes were designed and tested on a MATLAB-based simulation platform. Simulation results showed that the proposed method can resolve all the collisions and instruct the vehicles to pass signal-free intersections collaboratively without stopping in low to medium level of congestion.

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Generating Traffic Safety Test Scenarios for Automated Vehicles using a Big Data Technique

KSCE Journal of Civil Engineering ◽

10.1007/s12205-019-1287-4 ◽

2019 ◽

Vol 23 (6) ◽

pp. 2702-2712 ◽

Cited By ~ 2

Author(s):

Jaehyun Jason So ◽

Inseon Park ◽

Jeongran Wee ◽

Sangmin Park ◽

Ilsoo Yun

Keyword(s):

Big Data ◽

Traffic Safety ◽

Automated Vehicles ◽

Safety Test ◽

Test Scenarios

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Test scenarios construction based on combinatorial testing strategy for automated vehicles

IEEE Access ◽

10.1109/access.2021.3103912 ◽

2021 ◽

pp. 1-1

Author(s):

Hong Shu ◽

Haoran Lv ◽

Kang Liu ◽

Kang Yuan ◽

Xiaolin Tang

Keyword(s):

Combinatorial Testing ◽

Testing Strategy ◽

Automated Vehicles ◽

Test Scenarios

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