scholarly journals Car Following Behaviours on Multilane Highways in Kuwait: A Case Study on Road 40 during Winter Season

2021 ◽  
Author(s):  
Eisa Alenzi ◽  
◽  
Sitti Asmah Hassan ◽  
Othman Che Puan ◽  
◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Influencing Factor ◽  
Winter Season ◽  
Weather Conditions ◽  
Car Following ◽  
Speed Flow ◽  
Safety Awareness ◽  
Road Geometry ◽  
The Impact

The car following behaviour of a driver is the process of following the drivers to create an adjustment in the leading vehicle behaviour. In a condition, where the traffic volume is in a free-flowing situation, the selection of vehicles speed is typically limited by some factors such as weather conditions, lighting, and road geometry features. This study aims to investigate the effects of climates on driver’s car following behaviour and speed flow relationships for highways in Kuwait. The case study was conducted at Road 40 in Kuwait using RTMS Sx-300 device which is known as a radar device particularly used for monitoring traffic. The data was gathered between the periods from 29th December 2018 to 5th January 2019 within winter. MATLAB code was written to analyse and classify the gathered data. Then, the models were built using R-software. The study depicts that nearly 24.87% of the vehicles move between 60 km/h and 69 km/hour. Additionally, the vehicles were segmented according to their types i.e., Truck, Small, Medium and Large Sized Cars, in order to find the impact of following pattern on the vehicle average. It has been found that no significant association remains amidst the type of following pattern and the headway. Ultimately, a liner regression of data was developed to calculate a liner equation that shows the average headway as an element of speed for sixteen diverse following patterns. It has been recognized that an association could be supposed in medium-sized and small-sized vehicles. It has been observed that headway average could be placed in a linear equation for large, medium, and small as well as truck vehicles. It is worthy to denote that when data is bigger, the exactitude of a study enhances. Findings from each model of liner regression has more than 80% confidence level. The models of regression are deliberated as statistically significant where, the R (square) figures lies amidst 0.99 till 0.6. As per the findings, speed is the key influencing factor for headway value. The type of car does affect headway with drivers behind Heavy Good Vehicles and cars at the similar speed. According to the data, cars are identified to keep more headway when behind Heavy Good Vehicles in contrast with when behind other cars. These results will help the drivers to understand their behaviour that are associated with car crashes. Thus, increase road safety awareness and reduce traffic congestion in Kuwait.

An improved car-following model considering the impact of safety messages

2018 ◽  
Vol 32 (32) ◽  
pp. 1850398 ◽  
Author(s):  
Tenglong Li ◽  
Fei Hui ◽  
Xiangmo Zhao
Keyword(s):  
Traffic Congestion ◽  
Dominant Factor ◽  
Velocity Difference ◽  
Car Following ◽  
Safety Message ◽  
Warning Messages ◽  
Gray Correlation ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.

scholarly journals The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

2018 ◽  
Vol 11 (3) ◽  
pp. 57
Author(s):  
Xiao-Yan Cao ◽  
Bing-Qian Liu ◽  
Bao-Ru Pan ◽  
Yuan-Biao Zhang
Keyword(s):  
Traffic Congestion ◽  
Large Scale ◽  
Gated Communities ◽  
Urban Traffic ◽  
Average Delay ◽  
Traffic Demand ◽  
Car Following ◽  
Car Following Model ◽  
Urbanization In China ◽  
The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

scholarly journals Water Preservation and Conservation above Coal Mines Using an Innovative Approach: A Case Study

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2818
Author(s):  
Yujun Xu ◽  
Liqiang Ma ◽  
Yihe Yu
Keyword(s):  
Coal Mining ◽  
Water Conservation ◽  
Large Scale ◽  
Influencing Factor ◽  
Mining Area ◽  
Mining Operations ◽  
Narrow Strip ◽  
Geological Conditions ◽  
The Impact

To better protect the ecological environment during large scale underground coal mining operations in the northwest of China, the authors have proposed a water-conservation coal mining (WCCM) method. This case study demonstrated the successful application of WCCM in the Yu-Shen mining area. Firstly, by using the analytic hierarchy process (AHP), the influencing factors of WCCM were identified and the identification model with a multilevel structure was developed, to determine the weight of each influencing factor. Based on this, the five maps: overburden thickness contour, stratigraphic structure map, water-rich zoning map of aquifers, aquiclude thickness contour and coal seam thickness contour, were analyzed and determined. This formed the basis for studying WCCM in the mining area. Using the geological conditions of the Yu-Shen mining area, the features of caved zone, water conductive fractured zone (WCFZ) and protective zone were studied. The equations for calculating the height of the “three zones” were proposed. Considering the hydrogeological condition of Yu-Shen mining area, the criteria were put forward to evaluate the impact of coal mining on groundwater, which were then used to determine the distribution of different impact levels. Using strata control theory, the mechanism and applicability of WCCM methods, including height-restricted mining, (partial) backfill mining and narrow strip mining, together with the applicable zone of these methods, were analyzed and identified. Under the guidance of “two zoning” (zoning based on coal mining’s impact level on groundwater and zoning based on applicability of WCCM methods), the WCCM practice was carried out in Yu-Shen mining area. The research findings will provide theoretical and practical instruction for the WCCM in the northwest mining area of China, which is important to reduce the impact of mining on surface and groundwater.

scholarly journals Applying a Model for Trip Assignment and Dynamic Routing of Automated Taxis with Congestion: System Performance in the City of Delft, The Netherlands

2018 ◽  
Vol 2672 (8) ◽  
pp. 588-598 ◽  
Author(s):  
Xiao Liang ◽  
Gonçalo Homem de Almeida Correia ◽  
Bart van Arem
Keyword(s):  
The Netherlands ◽  
Real Time ◽  
Traffic Congestion ◽  
Programming Model ◽  
Profit Maximization ◽  
The Real ◽  
Real Size ◽  
The Impact ◽  
The City

This paper proposes a method of assigning trips to automated taxis (ATs) and designing the routes of those vehicles in an urban road network, and also considering the traffic congestion caused by this dynamic responsive service. The system is envisioned to provide a seamless door-to-door service within a city area for all passenger origins and destinations. An integer programming model is proposed to define the routing of the vehicles according to a profit maximization function, depending on the dynamic travel times, which varies with the ATs’ flow. This will be especially important when the number of automated vehicles (AVs) circulating on the roads is high enough that their routing will cause delays. This system should be able to serve not only the reserved travel requests, but also some real-time requests. A rolling horizon scheme is used to divide one day into several periods in which both the real-time and the booked demand will be considered together. The model was applied to the real size case study city of Delft, the Netherlands. The results allow assessing of the impact of the ATs movements on traffic congestion and the profitability of the system. From this case-study, it is possible to conclude that taking into account the effect of the vehicle flows on travel time leads to changes in the system profit, the satisfied percentage and the driving distance of the vehicles, which highlights the importance of this type of model in the assessment of the operational effects of ATs in the future.

scholarly journals How Would We Cycle Today If We Had the Weather of Tomorrow? An Analysis of the Impact of Climate Change on Bicycle Traffic

2021 ◽  
Vol 13 (18) ◽  
pp. 10254
Author(s):  
Anton Galich ◽  
Simon Nieland ◽  
Barbara Lenz ◽  
Jan Blechschmidt
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Winter Season ◽  
Model Performance ◽  
Weather Conditions ◽  
Planning And Design ◽  
Validation Procedure ◽  
The Impact ◽  
The City ◽  
Local Weather

Bicycle usage is significantly affected by weather conditions. Climate change is, therefore, expected to have an impact on the volume of bicycle traffic, which is an important factor in the planning and design of bicycle infrastructures. To predict bicycle traffic in a changed climate in the city of Berlin, this paper compares a traditional statistical approach to three machine learning models. For this purpose, a cross-validation procedure is developed that evaluates model performance on the basis of prediction accuracy. XGBoost showed the best performance and is used for the prediction of bicycle counts. Our results indicate that we can expect an overall annual increase in bicycle traffic of 1–4% in the city of Berlin due to the changes in local weather conditions caused by global climate change. The biggest changes are expected to occur in the winter season with increases of 11–14% due to rising temperatures and only slight increases in precipitation.

scholarly journals An Empirical Research on Study Success in Times of COVID-19 Pandemic – a Case Study

2021 ◽  
pp. 17-35
Author(s):  
Christin Voigt ◽  
◽  
Jonas Kötter ◽  
Natallia Kukharenka ◽  
◽  
...  
Keyword(s):  
Online Learning ◽  
Online Survey ◽  
Influencing Factor ◽  
Study Success ◽  
Path Diagram ◽  
Almost All ◽  
The Impact ◽  
Quantitative And Qualitative Methods

The COVID-19 pandemic and measures to contain it pushed many universities to switch to online learning in the spring of 2020. The changes took place very quickly and it became clear that the long-term consequences of such a transformation are uncertain and require more detailed study. This research attempts to analyze the impact of online learning on study success. This research makes use of a triangulation with quantitative and qualitative methods. Quantitatively, it contains path diagram with various factors that have an impact on the study success at a German university, which is based on a quantitative online survey with 1.529 participants. Qualitatively, 49 interviews were analyzed in order to identify reasons for the risk of failing to achieve study success. The relevance of technology becomes evident in the quantitative analysis, as it manifests itself in almost all categories that affect study success. Moreover, a new influencing factor appeared, the “adaption to digital teaching”, which was often considered important qualitatively.

scholarly journals The Impact of Social Status on Language Shift: A Case Study on Family Domain Language in Lembar

2019 ◽  
Vol 6 (3) ◽  
pp. 959
Author(s):  
Nazarudin Sodah
Keyword(s):  
Social Status ◽  
Economic Status ◽  
Influencing Factor ◽  
High Standard ◽  
Upper Class ◽  
Network Mobility ◽  
The People ◽  
Job Opportunities ◽  
The Impact

Every society is stratified in different classes and they are mainly measured through economic conditions. Diversity among the people in terms of their position, status, abilities is a very common phenomenon in this world. Age, gender, nationality, ethnicity, power, economy are a few influencing factors which are promoting divisions among the group. This research is about social status which trigers lexicon shifts on nucluer family of lembar society. This aims at finding out factors which lead to lexicon shift as well where the shifts mainly occur. The participants were 20 from low socio-economic status with span of age 20 to 50; no particular gender takes into account. Data obtained from this research clearly shows that peoples’ inclination towards prestigious variety comes after their desire to be upper class like. People’s social network/mobility is one of the influencing factor determines people to shift the language. People who possess good education, job opportunities and wealth obviously influence low economic people to use high standard language.

scholarly journals Observing the Impact of WWF Earth Hour on Urban Light Pollution: A Case Study in Berlin 2018 Using Differential Photometry

2019 ◽  
Vol 11 (3) ◽  
pp. 750 ◽  
Author(s):  
Andreas Jechow
Keyword(s):  
Electricity Consumption ◽  
Weather Conditions ◽  
Pollution Reduction ◽  
Light Pollution ◽  
Digital Cameras ◽  
Differential Photometry ◽  
Potsdamer Platz ◽  
Future Work ◽  
The Impact

Earth Hour is one of the most successful coordinated mass efforts worldwide to raise awareness of environmental issues, with excessive energy consumption being one driver of climate change. The campaign, first organized by the World Wildlife Fund in Australia in 2007, has grown across borders and cultures and was celebrated in 188 countries in 2018. It calls for voluntarily reduction of electricity consumption for a single hour of one day each year. Switching off non-essential electric lights is a central theme and resulted in 17,900 landmarks going dark in 2018. This switch-off of lights during Earth Hour also leads to reduction of light pollution for this specific period. In principle, Earth Hour allows the study of light pollution and the linkage to electricity consumption of lighting. However, quantitative analysis of the impact of Earth Hour on light pollution (and electricity consumption) are sparse, with only a few studies published showing no clear impact or the reverse, suffering from residual twilight and unstable weather conditions. In this work, light pollution measurements during Earth Hour 2018 in an urban park (Tiergarten) in Berlin, Germany, are reported. A novel light measurement method using differential photometry with calibrated digital cameras enables tracking of the switching off and switching back on of the lights of Berlin’s iconic Brandenburg Gate and the buildings of Potsdamer Platz adjacent to the park. Light pollution reduction during the event was measurable, despite the presence of moonlight. Strategies for future work on light pollution using such events are discussed.

A new longitudinal car-following control scheme of AVs towards the non-connected situation

2020 ◽  
Vol 34 (13) ◽  
pp. 2050135
Author(s):  
Yang Li ◽  
Min Zhao ◽  
Dihua Sun ◽  
Jin Chen ◽  
Weining Liu
Keyword(s):  
Traffic Congestion ◽  
Nonlinear Partial Differential Equation ◽  
Ar Model ◽  
Driving Safety ◽  
Prediction Errors ◽  
Car Following ◽  
V2v Communication ◽  
Control Scheme ◽  
Preceding Vehicle ◽  
The Impact

Connected cooperative driving is known as the promising way to mitigate traffic congestion, enhance driving safety and improve fuel economy. However, before vehicle-to-vehicle (V2V) communication technology became widely applied, vehicles could not always communicate with the front cars due to the uncertainty of vehicle type and communication function. Towards the non-connected situation and making the most of the on-board sensors of the automated vehicles (AVs), an auto-regression (AR) model was adopted to predict the velocity of the preceding vehicle at the next moment, then a new longitudinal car-following control scheme is given from the perspective of cyber physical system to improve the longitudinal following performance. The sufficient condition ensuring a better performance is acquired by local stability analysis and the impact of velocity prediction errors of the AR model is analyzed through a nonlinear partial differential equation. The experiments based on the US-101 dataset and numerical simulations were carried out and the results are in great agreement with the theoretical analysis, which reveals that applying AR model to predicting the velocity of the preceding vehicle at the next moment can improve the car-following performance of AVs without the support of communication devices.

Stability analysis of car-following model on straight and curved roads considering the preceding vehicle’s velocity feedback control

2018 ◽  
Vol 32 (21) ◽  
pp. 1850238 ◽  
Author(s):  
Peng Tan ◽  
Di-Hua Sun ◽  
Dong Chen ◽  
Min Zhao ◽  
Tao Chen
Keyword(s):  
Feedback Control ◽  
Traffic Flow ◽  
Traffic Congestion ◽  
Velocity Feedback ◽  
Car Following ◽  
Car Following Model ◽  
Negative Feedback Control ◽  
The Stability ◽  
The Impact ◽  
Good Agreement

In order to reveal the impact of preceding vehicle’s velocity on traffic flow, an extended car-following model considering preceding vehicle’s velocity feedback control is proposed in this paper. The linear stability criterion of the new model is derived through control theory method and it shows that the feedback control signal impacts the stability of traffic flow. Numerical simulation results is in good agreement with the theoretical analysis, which prove that a smaller negative feedback control of the preceding vehicle’s velocity can enhance the stability of traffic flow, while a smaller positive feedback control of the preceding vehicle’s velocity can exacerbate traffic congestion. Moreover, the reaction coefficients of straight and curved road conditions also play an important role in the stability of traffic flow.

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