scholarly journals Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Weiwei Qi ◽  
Lianjie Ruan ◽  
Yue Zhi ◽  
Bin Shen
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Flow Characteristics ◽  
Practical Significance ◽  
Risk Level ◽  
Risk Area ◽  
Potential Conflict ◽  
Bus Stop ◽  
Risk Areas ◽  
The Impact

Effective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and video recognition software, and the traffic flow characteristics of the bus stop are analyzed by the mathematical and statistical methods. Secondly, using the gray clustering evaluation theory, on the basis of the rasterization of the functional area of the bus bay stop, a risk level model based on the index system of conflict rate, conflict severity, and potential conflict risk is proposed. Finally, take a bus stop in Guangzhou as an example to verify the solution. The results show that the constructed model can effectively identify the risk areas of bus bay stops. The risk areas of the bus bay stops are concentrated in the middle and lower reaches of the bus stop, which proves that the impact of bus exiting the stop on the surrounding traffic is greater than the process of bus entering the stop; the traffic risk areas of lanes near the bus stop are concentrated, and the severity of conflicts is low. The traffic risk zone of the lane far away from the bus stop is widely distributed, and the severity of conflict is higher. The research results can provide a basis for the micro safety performance evaluation and safety optimization of bus bay stops, which has strong theoretical and practical significance.

scholarly journals Assessment of Soil Erosion and Its Impact on Agricultural Productivity by Using the RMMF Model and Local Perception: A Case Study of Rangun Watershed of Mid-Hills, Nepal

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dinesh Bhandari ◽  
Rajeev Joshi ◽  
Raju Raj Regmi ◽  
Nripesh Awasthi
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Group Discussion ◽  
Agricultural Productivity ◽  
Weighted Mean ◽  
Risk Area ◽  
Barren Land ◽  
Erosion Risk ◽  
Risk Areas ◽  
The Impact

Soil erosion is a major concern for the environment and natural resources leading to a serious threat to agricultural productivity and one of the major causes of land degradation in the mid-hills region of Nepal. An accurate assessment of soil erosion is needed to reduce the problem of soil loss in highly fragile mountainous areas. The present study aimed to assess spatial soil loss rate and identified risk areas and their perceived impact on agricultural productivity by using the Revised Morgan–Morgan–Finney (RMMF) model and social survey in the Rangun watershed of Dadeldhura district, Nepal. Soil erosion was assessed by using data on soil, digital elevation model, rainfall, land use, and land cover visually interpreted from multitemporal satellite images, and ILWIS 3.3 academic software was used to perform the model. A household questionnaire survey (n = 120) and focus group discussion (n = 2) in identified risk areas were carried out to understand the people’s perception towards soil erosion and its impact on agricultural productivity. The predicted average soil erosions from the forest, agriculture, and barren land were 2.7 t ha−1 yr−1, 53.73 t ha−1 yr−1, and 462.59 t ha−1 yr−1, respectively. The erosion risk area under very low to low, moderate to moderately high, and high to very high covers 92.32%, 4.96%, and 2.73%, respectively. It indicates that the rate of soil erosion was lower in forest areas, whereas it was higher in the barren land. The cropped area of the watershed has been reduced by 2.96 ha−1 yr−1, and productivity has been decreased by 0.238 t ha−1 yr−1. The impacts such as removal of topsoil (weighted mean = 4.19) and gully formation (weighted mean = 3.56) were the highest perceived factors causing productivity decline due to erosion. People perceived the impact of erosion in agricultural productivity differently ( ∗ significant at P ≤ 0.05 ). The study concluded that, comparatively, barren and agricultural lands seem more susceptible to erosion, so the long-term conservation and management investment in susceptible areas for restoration, protection, and socioeconomic support contribute significantly to land rehabilitation in the Rangun watershed.

The Impact on Traffic Safety in Bus Stop

2015 ◽  
Author(s):  
Kailun Zhang ◽  
Xiaoping Guang ◽  
Yongsheng Qian
Keyword(s):  
Traffic Safety ◽  
Bus Stop ◽  
The Impact

scholarly journals Estimating and Comparing Response Times in Traditional and Connected Environments

2019 ◽  
Vol 2673 (4) ◽  
pp. 674-684 ◽  
Author(s):  
Anshuman Sharma ◽  
Zuduo Zheng ◽  
Jiwon Kim ◽  
Ashish Bhaskar ◽  
Md. Mazharul Haque
Keyword(s):  
Decision Making ◽  
Traffic Safety ◽  
Driving Simulator ◽  
Response Times ◽  
Flow Characteristics ◽  
Trajectory Data ◽  
Stimulus Response ◽  
Wide Range ◽  
The Mean ◽  
The Impact

Response time (RT) is a critical human factor that influences traffic flow characteristics and traffic safety, and is governed by drivers’ decision-making behavior. Unlike the traditional environment (TE), the connected environment (CE) provides information assistance to drivers. This in-vehicle informed environment can influence drivers’ decision-making and thereby their RTs. Therefore, to ascertain the impact of CE on RT, this study develops RT estimation methodologies for TE (RTEM-TE) and CE (RTEM-CE), using vehicle trajectory data. Because of the intra-lingual inconsistency among traffic engineers, modelers, and psychologists in the usage of the term RT, this study also provides a ubiquitous definition of RT that can be used in a wide range of applications. Both RTEM-TE and RTEM-CE are built on the fundamental stimulus–response relationship, and they utilize the wavelet-based energy distribution of time series of speeds to detect the stimulus–response points. These methodologies are rigorously examined for their efficiency and accuracy using noise-free and noisy synthetic data, and driving simulator data. Analysis results demonstrate the excellent performance of both the methodologies. Moreover, the analysis shows that the mean RT in CE is longer than the mean RT in TE.

scholarly journals Left-Side On-Ramp Metering for Improving Safety and Efficiency in Underground Expressway Systems

2019 ◽  
Vol 11 (12) ◽  
pp. 3247 ◽  
Author(s):  
Minhua Shao ◽  
Congcong Xie ◽  
Lijun Sun ◽  
Xiaomin Wan ◽  
Zhang Chen
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Traffic Control ◽  
Flow Characteristics ◽  
Ramp Metering ◽  
Accident Risk ◽  
Data Traffic ◽  
Traffic Efficiency ◽  
Traffic Characteristics ◽  
Two Parameter

As one of the effective measures of intelligent traffic control, on-ramp metering is often used to improve the traffic efficiency of expressways. Existing on-ramp metering research mainly discusses expressways with right-side on-ramps. However, for underground expressway systems (UESs), left-side on-ramps are frequently adopted to reduce the ground space occupied by ramp construction. Since traffic entering from the left and right sides of the mainline may have different traffic characteristics, on-ramp metering for UESs with left-side on-ramps should be explored specifically. This study examines the impacts of left-side on-ramps on the traffic safety and efficiency of UESs and proposes an effective on-ramp metering strategy. Firstly, using field data, traffic flow fundamental diagrams and speed dispersion are discussed to explore the traffic flow characteristics of the “left-in” UES. The results show that the capacity and critical occupancy are both reduced in left-side on-ramp compared to right-side on-ramp expressways. Meanwhile, the speed dispersion is higher in left-side on-ramp UESs, which means a higher accident risk. Based on this, considering traffic safety and efficiency, a novel two-parameter left-side on-ramp metering strategy for UESs is proposed, in which occupancy and speed are used as the control indicators simultaneously. Additionally, the mechanism of the metering strategy is explained. Finally, the proposed on-ramp metering strategy is simulated on a real UES. The results demonstrate the advantages of the proposed two-parameter on-ramp metering strategy for improving the traffic safety and efficiency of UESs.

EFFECT OF RAINFALL ON TRAFFIC FLOW CHARACTERISTICS DURING NIGHT TIME

2016 ◽  
Vol 78 (7-2) ◽  
Author(s):  
Nurul ‘Azizah Mukhlas ◽  
Nordiana Mashros ◽  
Othman Che Puan ◽  
Sitti Asmah Hassan ◽  
Norhidayah Abdul Hassan ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Mean Flow ◽  
Night Time ◽  
Lighting Condition ◽  
Adverse Weather ◽  
Traffic Flow Characteristics ◽  
Rural Highway ◽  
The Impact ◽  
The Relationship

Understanding traffic behavior for obtaining a smooth, safe and economical traffic operation requires a thorough knowledge of traffic flow parameters and their mutual relationships.Eventhough adverse weather can reduce traffic efficiencies, there are still questions to answer regarding the relationship between weather conditions and traffic flow at night. This paper presents an investigation of the rainfall effects to the traffic flow characteristics on atwo-lane rural highway during night time. The traffic data and corresponding rainfall data for uninterrupted road segment of Federal route 3 at Dungun, Terengganu were collected under road lighting condition during the north-east monsoon season. The effect of good weather condition, light rain, moderate rain and heavy rain conditions on speed, flow and density were quantified and compared. Results from the analysis indicate that mean speed, mean flow and mean density are reduced under various rainfall conditions. In general, the impact of good weather and various rainfall conditions on Greenshield’s fundamental traffic flow relationship have weak correlations except for the relationship between flow and density. The important points in the fundamental diagram derived from flow-density relationships indicated that critical density, maximum flow, critical speed, jam density and free flow speed of roadway all decrease as rainfall intensity increases. It can be concluded that traffic flow characteristics of two-lane rural highway in Terengganu are affected by rainfall conditions.

scholarly journals A New Method Based on Field Strength for Road Infrastructure Risk Assessment

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Yi Li ◽  
Yuren Chen
Keyword(s):  
Risk Assessment ◽  
Field Strength ◽  
Driving Safety ◽  
Risk Level ◽  
Strength Model ◽  
Risk Area ◽  
Driver Behaviour ◽  
Road Infrastructure ◽  
Strength Models ◽  
The Impact

Because road infrastructures have significant impact on driving safety, their risk levels need to be evaluated dynamically according to drivers’ perception. To achieve this, this paper proposes two field strength models to quantify the impact of road infrastructures on drivers. First, road infrastructures are classified into two types (continuous and discrete). Then, two field strength models for these types are proposed. Continuous field strength model describes the impact of long-belt-shape infrastructure by differential and integral methods. Discrete field strength model describes the static and dynamic characteristics of infrastructures. This model includes four parameters: mass of vehicles, mass of infrastructures, warning level, and kinetic energy of road infrastructures. The field strength is a relative concept, which changes with vehicle state. At the end of this paper, risk assessment principles are listed to clarify the nature of road infrastructure risk evaluation. A workflow of risk assessment and a case study are presented to illustrate the application of this novel method. The result of this study shows that ① the field strength is positively related to its risk level; ② the distribution of road infrastructure risks explains driver behaviour correctly; ③ drivers tend to keep driving in low-risk area. These findings help to explain the impact mechanism of road infrastructures on drivers, which can be applied in AI-based driving assistance system in the future.

scholarly journals The Impact of Truck Proportion on Traffic Safety Using Surrogate Safety Measures in China

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Shengdi Chen ◽  
Shiwen Zhang ◽  
Yingying Xing ◽  
Jian Lu ◽  
Yichuan Peng ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Traffic Flow ◽  
Traffic Safety ◽  
Variation Coefficient ◽  
Support Vector ◽  
Safety Measures ◽  
Speed Variation ◽  
Surrogate Safety Measures ◽  
The Impact ◽  
The Relationship

The purpose of this study is to investigate the impact of the truck proportion on surrogate safety measures to explore the relationship between truck proportion and traffic safety. The relationship between truck proportion and traffic flow parameters was analyzed by correlation and partial correlation analysis, and the value of the 85th percentile speed minus the 15th percentile speed (85%V–15%V) and the speed variation coefficient were selected as surrogate safety measures to explore the impact of truck proportion on traffic status. The k-means algorithm and the support vector machine were employed to evaluate traffic status on a freeway under different truck proportions in different periods. The major results are that the relationship between truck proportion and the value of 85%V–15%V and the speed variation coefficient is consistent in different aggregation periods. With increasing truck proportion, the value of 85%V–15%V, as well as the speed variation coefficient, increases initially and then decreases. In addition, the traffic flow status tends to be dangerous when the truck proportion ranges from 0.4 to 0.6 and when the value of 85%V–15%V and the speed variation coefficient are above 42 km/h and 0.223, respectively. While the truck proportion is from 0.1 to 0.3 and from 0.7 to 0.9, the traffic flow is relatively safe on the condition that the value of 85%V–15%V and the speed variation coefficient were under 42 km/h and 0.223, respectively. Therefore, the relationship between truck proportion and traffic safety could be well revealed by two surrogate safety measures, that is, the value of 85%V–15%V and the speed variation coefficient. In addition, the k-means algorithm and the support vector machine can well reveal the impact of truck proportion on traffic safety in different periods. The findings of this study indicate a need for decreasing the disturbance of mixed traffic and the impact of the truck proportion on traffic safety status.

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