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Qiang Luo
School of Civil Engineering, Guangzhou University, Guangzhou 510006, China

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Journal article
Published: 04 May 2021 in Sustainability
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Lane-changing behavior is one of the most common driving behaviors while driving. Due to the complexity of its operation, vehicle collision accidents are prone to occur when changing lanes. Under the environment of vehicle networking, drivers can obtain more accurate traffic information in time, which can be of great help in terms of improving lane-changing safety. This paper analyzes the core factors that affect the safety of vehicles changing lanes, establishes the weight model of influencing factors of lane-changing behavior using the analytic hierarchy process (AHP), and obtains the calculation method of lane-changing behavior factors (LCBFs). Based on the fuzzy reasoning theory, the headway between the lane-changing vehicle and adjacent vehicles in the target lane was examined, and fuzzy logic lane-changing models were established for both situations (i.e., change to the left and change to the right lane). The fuzzy logic lane-changing models were tested via simulation experiments, and the test results showed that the models have a better warning effect on lane changing (LCBF = 1.5), with an accuracy of more than 90%. Thus, the established model in this paper can provide theoretical support for safety warnings when changing lanes and theoretical support for the sustainable development of transportation safety.

ACS Style

Qiang Luo; Xiaodong Zang; Xu Cai; Huawei Gong; Jie Yuan; Junheng Yang. Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking. Sustainability 2021, 13, 5146 .

AMA Style

Qiang Luo, Xiaodong Zang, Xu Cai, Huawei Gong, Jie Yuan, Junheng Yang. Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking. Sustainability. 2021; 13 (9):5146.

Chicago/Turabian Style

Qiang Luo; Xiaodong Zang; Xu Cai; Huawei Gong; Jie Yuan; Junheng Yang. 2021. "Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking." Sustainability 13, no. 9: 5146.

Journal article
Published: 26 April 2021 in Sustainability
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Roadside parking systems plays an important role in the planning and design of parking spaces, parking management and operation, and ensuring the safety of passengers. Firstly, we proposed a traffic wave theory and an avoidance logic algorithm to analyze the interaction mechanism of the roadside parking system in a rail-integrated transport hub. Moreover, we researched the evaluation indexes of the stability of roadside parking systems via two new concepts, namely static roadside parking time and dynamic roadside parking time. We found these improved the algorithm of the time utilization rate of the berth. Secondly, the coupling relationship between parking rate, delay and time utilization of berth was also discussed, and mathematical models of stability of the curb parking system were established. Furthermore, the feasibility of models was verified by multi-agent simulation through the VISSIM simulation platform. Finally, a new rail-integrated transport hub was taken as a practical case and studied alongside the simulation of the stability of curb parking system. Our study concluded that the curb parking system was ultimate stable when the time utilization rate was 37.5% and the parking rate was 91.2%. The results of these studies will provide theoretical support for designing curb parking berths in rail-integrated transport hubs.

ACS Style

Junheng Yang; Xiaodong Zang; Qiang Luo; Liming Shao. Analysis on Stability of Roadside Parking System in a Rail-Integrated Transport Hub. Sustainability 2021, 13, 4855 .

AMA Style

Junheng Yang, Xiaodong Zang, Qiang Luo, Liming Shao. Analysis on Stability of Roadside Parking System in a Rail-Integrated Transport Hub. Sustainability. 2021; 13 (9):4855.

Chicago/Turabian Style

Junheng Yang; Xiaodong Zang; Qiang Luo; Liming Shao. 2021. "Analysis on Stability of Roadside Parking System in a Rail-Integrated Transport Hub." Sustainability 13, no. 9: 4855.