Expressway Merge Assistance Method and Evaluation Based on Connected Vehicle Technology

Wang, Dongzhu; Chen, Yanyan; Ma, Jun; Walton, C. Michael

doi:10.1061/jhtrcq.0000600

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Second, the interpolation method is used to fill in the missing positioning data. Through the onboard terminal device, the vehicle positioning information that we obtain includes the longitude and latitude, direction angle, speed and driving time [32][33][34][35] . The principle of removing abnormal data from the positioning information is shown in Figure 1.…”

Section: Data Preprocessingmentioning

confidence: 99%

Research and Application of Adaptive Projection Map Matching Algorithm under the Background of Complex Roads

fu,

cheng,

chen

2024

Preprint

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To address the problems of easy volatility, empty matching, incorrect matching, and low matching accuracy, an adaptive projection map matching algorithm is proposed based on existing map matching algorithms for intersecting urban roads. First, the method of setting the distance threshold was used to eliminate abnormal location points. Then, by comparison with the AutoNavi map, the missing data in the OpenStreetMap were filled. To reduce the matching time, the grid index was generated, and the impossible methods were filtered by the error circle. Second, the probabilities of the projection distance and direction were assigned, and the corresponding weight coefficients were adjusted adaptively. Finally, the probabilities of the candidate methods were calculated by considering both the projection distance and direction, which helped to determine the actual road and improve the matching accuracy. At the same time, real-time driving data from Changzhou taxi vehicles were used for experimental verification. The results show that the adaptive projection map matching algorithm can increase the matching accuracy by approximately 4% compared with other existing matching algorithms and shorten the single-point matching time by approximately 1.5 ms, which realizes accurate map matching under complex intersecting methods.

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Section: Data Preprocessingmentioning

confidence: 99%

Research and Application of Adaptive Projection Map Matching Algorithm under the Background of Complex Roads

fu,

cheng,

chen

2024

Preprint

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“…This is based on the unveiled relationship between speed variation and other traffic parameters, such as traffic volume and traffic composition. Wang et al 29 developed the expressway merge assistance method to improve safety by implementing the connected vehicle technology in a way so as to provide warnings to the driver in advance with VISSIM. As a result, the average speed increased by 38.3% and the average travel time decreased by 16.1%.…”

Section: Sajjadi and Kondylimentioning

confidence: 99%

Impact of an automated road debris removal system on traffic flow using VISSIM

Yang

Kim

et al. 2020

SIMULATION

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This study introduces a state-of-the-art road debris removal system (i.e., automated road debris removal system (ROBOS)) and analyzes its impact on traffic flow using the microscopic simulation model, VISSIM. Robust simulation scenarios were established, and the major parameters of individual scenarios were also included based on extensive interviews with road workers. The performances of road workers and the ROBOS in regard to road debris removal were investigated in terms of four measures of effectiveness. These included queue, density, percentage delay, and number of vehicle stops. To mimic the major arterial roadways in South Korea, two-lane, three-lane, and four-lane roads were considered for implementing the road debris removal process. The simulation results as well as the statistical analysis revealed that the ROBOS outperforms the direct removal by road workers in all aspects. Thus, the ROBOS can remove the debris more safely and efficiently. The findings of this research can improve institutional operational guidelines for the ROBOS by providing an appropriate range for its parameters. This can result in enhancing traffic safety and efficiency. Notwithstanding the simulation results, the more unexpected cases, such as the driver carelessness during removal work, should be reflected in future research to thoroughly prevent the potential risk of accidents as well as maintaining smooth traffic flow.

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“…Based on the microscopic METANET model and ALINEA algorithm, a variable speed control strategy is designed to achieve dynamic control of vehicle speed. Wang et al [16] employed a combination of various trafc sensors to collect real-time trafc status data in the merge area. Trough the decision-making unit, the trafc status data is processed, analyzed, and updated periodically.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Effects of Interchange Warning Systems on Driving Risk: A Driving Simulator Study

Li,

Guo,

et al. 2024

Journal of Advanced Transportation

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To investigate the effects of proactive safety control systems suitable for highway interchanges and improve road traffic safety. Simulated driving experiments were conducted to test the effects of the interchange warning system (IWS) on the ramp, merging section, diverging section, and accident section. Random forest (RF) and SHapley Additive exPlanations (SHAP) are used to analyze the effects between driving behavior and driving risk change in both situations without and with IWS. The results show that (1) as driving risk increases, drivers tend to increase the frequency of braking and engage in more comprehensive saccade behaviors. Concurrently, there is an increase in acceleration and speed variation, leading to a gradual decrease in speed. (2) Compared with the SVR and XGBoost, RF can better fit the nonlinear relationship between driving risk and driver behavior characteristics with the application of IWS. (3) The IWS mainly reduces driving risk by affecting operation behavior. When the mean speed, speed standard deviation (SD), acceleration SD, and maximum braking depth are at 40 to 70 km/h, 3 to 10 km/h, 0 to 0.6 m/s2, and 14 to 16, respectively, there is a significant reduction in driving risk. The application of the IWS expands the effective range of mean speed and speed SD for reducing driving risk to 40 to 100 km/h and 3 to 15 km/h, respectively.

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Expressway Merge Assistance Method and Evaluation Based on Connected Vehicle Technology

Cited by 3 publications

References 5 publications

Research and Application of Adaptive Projection Map Matching Algorithm under the Background of Complex Roads

Research and Application of Adaptive Projection Map Matching Algorithm under the Background of Complex Roads

Impact of an automated road debris removal system on traffic flow using VISSIM

Assessing the Effects of Interchange Warning Systems on Driving Risk: A Driving Simulator Study

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