Real-Time Path Planning in Urban Area via VANET-Assisted Traffic Information Sharing

Guo, Chang; Li, Demin; Zhang, Guanglin; Zhai, Menglin

doi:10.1109/tvt.2018.2806979

Cited by 81 publications

(25 citation statements)

References 26 publications

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“…2, with the design of (8), γ(s) will have higher value when i = 2 or 4, indicating that the vehicle is placed laterally with respect to SD and making people feel unsafe and uncomfortable. Therefore the stability angle α 2 and α 4 will have greater impact than α 1 and α 3 in (8). The γ(s) is independent among different states.…”

Section: Vehicle Stability Analysismentioning

confidence: 98%

“…2) Vehicle Stability Function Evaluation: To evaluate the effectiveness of the proposed stability function in (8), experiments were conducted in a simplified environment that is similar to the simulation environment with slope way, as shown in Fig. 9(a).…”

Section: ) Traversable Map Generationmentioning

confidence: 99%

“…With a suitable environment map, path planning strategy is one key technique for achieving stable robot navigation and has been well investigated over the past decades [8]- [10]. Generally, the goal for path planning is to generate a feasible path from the start location to the desired location regarding the vehicle motion or energy constraints.…”

Section: Introductionmentioning

confidence: 99%

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Stable Autonomous Robotic Wheelchair Navigation in the Environment With Slope Way

Wang

Xia

Meng

2020

IEEE Trans. Veh. Technol.

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In this article, we present a path planning approach that is capable of generating a feasible trajectory for stable robotic wheelchair navigation in the environment with slope way. Firstly, the environment is modeled by a lightweight navigation map, with which the proposed sampling-based path planning scheme with a modified extension function can generate a feasible path. Then, the path is further optimized by the proposed utility function involving the human comfort and the path cost. To improve the searching efficiency of an optimal trajectory, we present an adaptive weighting Gaussian Mixture Model (GMM) based sampling strategy. Particularly, the weights of the components in GMM are adjusted adaptively in the planning process. It is also worth noting that the proposed sampling-based planning paradigm can indicate the unsafe regions in the navigation map, which forms a traversable map and further guarantees the safety of the wheelchair robot navigation. Furthermore, the effectiveness and the efficiency of the proposed path planning method are verified in both simulation and real-world experiments.

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Section: Vehicle Stability Analysismentioning

confidence: 98%

Section: ) Traversable Map Generationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stable Autonomous Robotic Wheelchair Navigation in the Environment With Slope Way

Wang

Xia

Meng

2020

IEEE Trans. Veh. Technol.

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“…At a certain moment, the special situation on the road surface causes large fluctuations in the traffic flow. The road surface works, such as watering, spraying, and cleaning, should be immediately stopped after receiving the notice from the traffic command center and the staff members should quickly deviate, which can avoid the superposition of fluctuation effects [23]. The works can be resumed after the fluctuation has been slowed down, which will not affect the daily work tasks.…”

Section: Countermeasures Of Urban Traffic Improvement Based On Thmentioning

confidence: 99%

Countermeasure Study of Urban Traffic Improvement Based on the Internet of Things

Wang

Sheng

et al. 2020

IEEE Access

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In order to reduce the fluctuations of traffic flow and the impacts of traffic flow fluctuations, thereby increasing the level of service of roads and constructing the Internet of Things-based traffic system, based on the various causes of traffic flow fluctuations, the countermeasures were taken, such as the optimization of lanes, the management of intersections, the improvement and perfection of slow-vehicle lanes and bus stops, the timely renewal of traffic signs and marks, the rational arrangements of road operations, and the removal of visual obstacles, etc. The research results showed that these countermeasures could effectively reduce the hidden peril of accidents and improve the road capacity, thereby improving the level of service of roads, which provided a theoretical foundation and basis for road engineering design and traffic management. It can be seen that improving urban traffic through rational management and control measures can effectively improve the level of service of urban traffic. INDEX TERMS Urban road, traffic flow fluctuation, level of service, countermeasure.

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“…Unlike the conventional transportation system, the key support for building ITS is the data generated by humans, vehicles and the dynamic traffic environment [8]. Based on the collection and analysis of traffic data, the scheduling strategies can be determined to facilitate different vehicular applications such as path planing [9]- [11] and autonomous driving [12]- [15]. As a typical data collection method, vehicle classification and speed estimation can provide the data to rationalize the construction of traffic roads and reduce the driving risks.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Classification and Speed Estimation Based on a Single Magnetic Sensor

Liu

Hui

et al. 2020

IEEE Access

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The integration of Internet of things (IoT) and intelligent transportation system (ITS) is expected to improve the traffic efficiency and enhance the driving experience. However, due to the dynamic traffic environment and various types of vehicles, it is a challenge to perform vehicle classification and speed estimation with a single magnetic sensor. In this paper, based on a single low-cost magnetic sensor, a scheme is proposed to achieve vehicle classification and speed interval estimation by designing a twodimensional convolutional neural network (CNN). Specifically, we extract the magnetic field data of each vehicle and then convert the collected data into a two-dimensional grayscale image. In this way, the images of vehicle signals with different types and driving speeds can be used as the input data to train the designed CNN model. With the designed CNN model, we classify the vehicles into 7 types and estimate the speed interval of each vehicle, where the speeds in the range of 10km/h-70km/h are divided into 6 intervals of size 10km/h. The performance of the proposed vehicle classification and speed estimation scheme is evaluated by experiments, where the experimental results show that the accuracy of vehicle classification and the accuracy of speed interval estimation are 97.83% and 96.85%, respectively.

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Real-Time Path Planning in Urban Area via VANET-Assisted Traffic Information Sharing

Cited by 81 publications

References 26 publications

Stable Autonomous Robotic Wheelchair Navigation in the Environment With Slope Way

Stable Autonomous Robotic Wheelchair Navigation in the Environment With Slope Way

Countermeasure Study of Urban Traffic Improvement Based on the Internet of Things

Vehicle Classification and Speed Estimation Based on a Single Magnetic Sensor

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