traffic conditions
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Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 171
Jiguang Hou ◽  
Xianteng Cao ◽  
Changshu Zhan

Suspension is an important part of intelligent and safe transportation; it is the balance point between the comfort and handling stability of a vehicle under intelligent traffic conditions. In this study, a control method of left-right symmetry of air suspension based on H∞ theory was proposed, which was verified under intelligent traffic conditions. First, the control stability caused by the active suspension control system running on uneven roads needs to be ensured. To address this issue, a 1/4 vehicle active suspension model was established, and the vertical acceleration of the vehicle body was applied as the main index of ride comfort. H∞ performance constraint output indicators of the controller contained the tire dynamic load, suspension dynamic stroke, and actuator control force limit. Based on the Lyapunov stability theory, an output feedback control law with H∞-guaranteed performance was proposed to constrain multiple targets. This way, the control problem was transformed into a solution to the Riccati equation. The simulation results showed that when dealing with general road disturbances, the proposed control strategy can reduce the vehicle body acceleration by about 20% and meet the requirements of an ultimate suspension dynamic deflection of 0.08 m and a dynamic tire load of 1500 N. Using this symmetrical control method can significantly improve the ride comfort and driving stability of a vehicle under intelligent traffic conditions.

2022 ◽  
Will S. Drysdale ◽  
Adam R. Vaughan ◽  
Freya A. Squires ◽  
Sam J. Cliff ◽  
Stefan Metzger ◽  

Abstract. During March–June 2017 emissions of nitrogen oxides were measured via eddy covariance at the British Telecom Tower in central London, UK. Through the use of a footprint model the expected emissions were simulated from the spatially resolved National Atmospheric Emissions Inventory for 2017, and compared with the measured emissions. These simulated emissions were shown to underestimate measured emissions during the day time by a factor of 1.48, but they agreed well overnight. Furthermore, underestimations were spatially mapped and the areas around the measurement site responsible for differences in measured and simulated emissions inferred. It was observed that areas of higher traffic, such as major roads near national rail stations, showed the greatest underestimation by the simulated emissions. These discrepancies are partially attributed to a combination of the inventory not fully capturing traffic conditions in central London, and both spatial and temporal resolution of the inventory not fully describing the high heterogeneity of the urban centre. Understanding of this underestimation may further improved with longer measurement time series ,to better understand temporal variation, and improved temporal scaling factors, to better simulate sub-annual emissions.

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Yanting Sheng ◽  
Rui Feng ◽  
Salvatore Antonio Biancardo

Traffic safety plays a crucial role in the development of autonomous vehicles which attracts significant attention in the community. It is a challenge task to ensure autonomous vehicle safety under varied traffic environment interference, especially for airport-like closed-loop conditions. To that aim, we analyze autonomous vehicle safety at typical roadway conditions and traffic state constraints (e.g., car-following state at different speed distributions) by simulating the airport-like traffic conditions. The experimental results suggest that traffic collision risk is in a positive relationship with the speed difference and distance among adjacent vehicles. More specifically, the autonomous vehicle may collide with neighbors when the time to collision (TTC) indicator is lower than 4 s, and vice versa. The research findings can help both research community and practioners obtain additional information for improving traffic safety for autonomous vehicles.

2022 ◽  
Bruce W. Kay ◽  
Adam Frewin ◽  
Stephanie Priess ◽  
Roland Sgorcea ◽  
Lesley A. Weitz

2022 ◽  
Vol 955 (1) ◽  
pp. 012014
M A Salim ◽  
A B Siswanto ◽  
T Mindiastiwi

Abstract The flood disaster that occurred in Pekalongan district in February 2021 was caused by the high intensity of rain for one week with rainfall >50 mm/day and the ebb and flow of sea water due to tides reaching 0.9-1.1 meters. Other problems due to flooding in Pekalongan district are change in land use, land subsidence, waste, erosion-sedimentation, as well as operation and maintenance factors. Losses due to floods cause material and building losses and traffic conditions are paralyzed. The method used in this research is primary and secondary data collection, descriptive qualitative data processing by describing understanding, research approach with field observations. Flood handling that has been carried out is by adding an emergency sliding door to the drainage, procuring a mobile water pump with a capacity of 250 liters/second, a CCSP (Corrugated Concrete Sheet Pile) embankment, rehabilitation of the Bremi River floodgate, construction of a Mrican pump house with a capacity of 8×2 m3/second, and construction of a 2,200 meter long Silempeng earthen embankment. The emergency handling that was carried out during the floods of February 2021 was the opening of the Long Storage Silempeng-Sengkarang and the preparation of sandbags and large sacks for emergency handling.

2022 ◽  
Vol 14 (2) ◽  
pp. 103-110
Olha Sakno ◽  
Ievgen Medvediev ◽  
Peter Eliseyev ◽  
Serhii Tsymbal ◽  

Uncertainty of data during environmental monitoring prevents with confidently and objectively assessing the current condition of the environment, the influence of factors affecting the fuel consumption of vehicles during operation. In addition, it creates a serious problem in assessing the dynamics of this condition, especially when it comes to relatively small levels of pollution that are on the verge of the sensitivity of systems and devices in the car. It is precisely these tasks that include the determination of atmospheric pollution by emissions from road transport in conditions of variable weather and climatic conditions, carrying out routine maintenance, changing a configuration of an engine or transmission. The article discusses: a) factors related to the characteristics and vehicle systems, with the maintenance of vehicles. This category focuses on fuel consumption and CO2 emissions, which depend on the technical and operational characteristics of the vehicle, its weight and aerodynamics, tires and auxiliary systems, the quality and timeliness of maintenance and repairs; b) factors related to the environment and traffic conditions (weather conditions, road morphology and traffic conditions); c) factors related to a driver of a vehicle (driver qualifications, driving style). Optimization of factors related to vehicle systems and their characteristics has been performed; by using fuel of optimum quality and driving efficiently, you can achieve savings in fuel (financial) consumption and CO2 emissions. The article proposes the solution to a complex problem of managing the transport process while minimizing fuel consumption and CO2 emissions from passenger cars, depending on the road and climatic conditions and the driver's qualifications, based on the theory of fuzzy sets. This approach made it possible to largely compensate for the lack of objective information about the process due to its uncertainty by subjective expert data.

2022 ◽  
Vol 13 (1) ◽  
pp. 15
Tim Jonas ◽  
Christopher D. Hunter ◽  
Gretchen A. Macht

While the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study. A total of 30 BEV inexperienced drivers test drove a 2017 Volkswagen eGolf on a route with various road types in two different traffic intensity scenarios: During morning commute hours with higher traffic congestion and lower congestion hours throughout the middle of the day. Results support the hypothesis that traffic conditions significantly impact the vehicle’s efficiency, with additional consumption of approximately 4–5% in the high traffic scenario. By creating and comparing driving in traffic to an underlying base case scenario, the additional range potential by avoiding traffic for this particular vehicle can be quantified as up to seven miles. New patterns of BEV efficiencies emerged, which can help stakeholders understand how eco-driving can be strategically improved by selecting trip times and routes that avoid high traffic intensity.

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