scholarly journals Traffic Model and On-Ramp Metering Strategy under Foggy Weather Conditions Using T-S Fuzzy Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Changle Sun ◽  
Hongyan Gao
Keyword(s):  
Traffic Safety ◽  
Weather Conditions ◽  
Ramp Metering ◽  
Traffic Model ◽  
Crash Risk ◽  
Traffic Density ◽  
Percentage Error ◽  
S Model ◽  
Takagi Sugeno ◽  
Curve Radius

Foggy weather seriously deteriorates the performance of freeway systems, particularly regarding traffic safety and efficiency. General macroscopic traffic models have difficulty reflecting the characteristics of a freeway under foggy weather conditions. In the present study, a macroscopic traffic model using a correction factor under foggy weather conditions is therefore proposed, which is regulated according to the different levels of visibility and curve radius of the freeway using the Takagi–Sugeno (T-S) model. Based on the proposed traffic model, a local ramp metering strategy with density correction under foggy weather conditions is proposed to improve traffic safety. The proposed local ramp metering strategy regulates the on-ramp flow using the T-S model according to the mainstream density, speed, and visibility. The correction factors are determined based on the parameters of the consequent part in the T-S model, which are optimized using the particle swarm optimization algorithm. The sum of the mean absolute percentage error of the mainstream traffic density and speed is used to evaluate the proposed traffic model. The real-time crash-risk prediction model, which reflects the degree of traffic safety, is used to evaluate the proposed local ramp metering strategy. Simulations using VISSIM and MATLAB show that the proposed traffic model is suitable under foggy weather conditions and that the proposed local ramp metering strategy achieves a better performance in reducing fog-related crashes.

scholarly journals Predicting Wet-Road Crashes Using the Finite-Mixture Zero-Truncated Negative Binomial Model

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ying Chen ◽  
Zhongxiang Huang
Keyword(s):  
Traffic Safety ◽  
Negative Binomial ◽  
Safety Data ◽  
Method Comparison ◽  
Weather Conditions ◽  
Finite Mixture ◽  
Crash Risk ◽  
Crash Data ◽  
Road Crashes ◽  
Inclement Weather

Inclement weather affects traffic safety in various ways. Crashes on rainy days not only cause fatalities and injuries but also significantly increase travel time. Accurately predicting crash risk under inclement weather conditions is helpful and informative to both roadway agencies and roadway users. Safety researchers have proposed various analytic methods to predict crashes. However, most of them require complete roadway inventory, traffic, and crash data. Data incompleteness is a challenge in many developing countries. It is common that safety researchers only have access to data on sites where a crash has occurred (i.e., zero-truncated data). The conventional crash models are not applicable to zero-truncated safety data. This paper proposes a finite-mixture zero-truncated negative binomial (FMZTNB) model structure. The model is applied to three-year wet-road crash data on 395 divided roadway segments (total 586 km), and the parameters are estimated using the Markov chain Monte Carlo (MCMC) method. Comparison indicates that the proposed FMZTNB model has better fitting performance and is more accurate in predicting the number of wet-road crashes. The model is capable of capturing the heterogeneity within the sample crash data. In addition, lane width showed mixed effects in different components on wet-road crashes, which are not observed in conventional modeling approaches. Practitioners are encouraged to consider the finite-mixture zero-truncated modeling approach when complete safety dataset is not available.

Analysis on the Anti-Glare Plate Setting Distance on Horizontal Curve Sections of Expressway

2014 ◽  
Vol 587-589 ◽  
pp. 2156-2159 ◽  
Author(s):  
Tian Xiao ◽  
Ji Shu Sun ◽  
Can Zhang Jin
Keyword(s):  
Traffic Safety ◽  
Calculation Formula ◽  
Horizontal Curve ◽  
Distance Calculation ◽  
Element Simulation ◽  
Curved Section ◽  
Curve Radius ◽  
The Relationship ◽  
Plate Distance ◽  
Glare Effect

Glare is one of the most important factors threating expressway traffic safety an night. The most commonly way to prevent glaring night is to set anti-glare plate. Different from the straight sections of expressway, the relationship between the front light of vehicles and the distance of anti-glare plate on the horizontal curved section has some-what changed. Through a lot of tests and finite element simulation, the relationship between the distance of anti-glare plate, horizontal curve radius and anti-glare effect were analyzed systematically. Distance calculation formula of anti-glare plate in horizontal curve sections was revised in this paper. The anti-glare plate distance requirement under different expressway alignment design indexes and its calculation formula was proposed. The achievement was beneficial to confirm the anti-glare effect and improve traffic safety. It can provide us with a reference and a supplement of the specification.

A New Highway Safety Model Based on Cellular Automata

2014 ◽  
Vol 989-994 ◽  
pp. 2340-2343
Author(s):  
Li Xing Li
Keyword(s):  
Cellular Automata ◽  
Energy Conservation ◽  
Traffic Safety ◽  
Conservation Law ◽  
Highway Safety ◽  
Traffic Density ◽  
New Model ◽  
The Road ◽  
The Right ◽  
Energy Conservation Law

With the growth of the total mileage of highway. There is great importance in studying highway safety. At the present time, there are little research on traffic safety with the consideration of the Keep-Right-Except-To-Pass Rule, which requires drivers to drive in the right-most lane unless they are passing another vehicle. Based on Cellular Automata, this paper constructs a new model of highway safety with the consideration of the particular Rule. To evaluate the safety of the road, the model proposes a new index based on energy conservation law. After the simulation, the result shows the best traffic density to balance the safety and traffic flux is 20.1133veh/km.

scholarly journals Role of Poverty in California Teenagers’ Fatal Traffic Crash Risk

2009 ◽  
Vol 7 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Mike Males
Keyword(s):  
Traffic Safety ◽  
Low Income ◽  
Motor Vehicle ◽  
Strong Association ◽  
Motor Vehicle Crash ◽  
Motor Vehicle Crashes ◽  
Crash Risk ◽  
Vehicle Crashes ◽  
Fatal Crash ◽  
Adolescent Risk

Teenagers’ high rates of motor vehicle crashes, accounting for 40% of external deaths among 16-19 yearolds, have been ascribed largely to inherent “adolescent risk-taking” and developmental hazards. However, the fact that compared to adults 25 and older, teenagers are twice as likely to live in poverty and low-income areas, risk factors for many types of violent death, has not been assessed. This paper uses Fatality Analysis Reporting System data on 65,173 fatal motor vehicle crashes by drivers in California’s 35 most populous counties for 1994-2007 to analyze fatal crash involvements per 100 million miles driven by driver age, county, poverty status, and 15 other traffic safety-related variables. Fatal crash rates were substantially higher for every driver age group in poorer counties than in richer ones. Multivariate regression found socioeconomic factors, led by the low levels of licensing and high unemployment rates prevalent in low-income areas, were associated with nearly 60% of the variance in motor vehicle crash risks, compared to 3% associated with driver age. The strong association between fatal crash risk and poverty, especially for young drivers who are concentrated in high-poverty brackets and low-income areas, suggests that factors related to poorer environments constitute a major traffic safety risk requiring serious attention.

An integrated control method based on the priority of ways in a freeway network

2016 ◽  
Vol 40 (3) ◽  
pp. 843-852 ◽  
Author(s):  
Minghui Ma ◽  
Shidong Liang
Keyword(s):  
Traffic Congestion ◽  
Control Method ◽  
Integrated Control ◽  
Adaptive Controller ◽  
Ramp Metering ◽  
Traffic Density ◽  
Variable Speed ◽  
Speed Limits ◽  
Variable Speed Limits ◽  
Freeway Networks

Traffic congestion is a common problem in merging regions of freeway networks. An adaptive integrated control method involving variable speed limits and ramp metering is presented with the aim of easing traffic congestion at merging regions. The problem of the imbalanced rights of ways of the upstream mainline and on-ramp at the merging region is solved by constructing the evaluation indices of congestion degree. Specifically, the traffic density and queue length of the upstream mainline and on-ramp are selected for use in the evaluation indices. Then, an adaptive controller is designed, integrating variable speed limits and ramp metering. The proposed method is tested in simulations considering a real freeway network in China calibrated by real traffic variables. The results show that the proposed adaptive integrated control method can prevent traffic flow breakdown and maintain a high outflow at the merging region during peak periods. The adaptive integrated control may lead to a 17% improvement in traffic delay.

A New Framework to Evaluate Crash Risk for Road Traffic Safety Management System

2021 ◽  
pp. 573-587
Author(s):  
Fabio Porcu ◽  
Francesca Maltinti ◽  
Nicoletta Rassu ◽  
Francesco Pili ◽  
Michela Bonera ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Management System ◽  
Safety Management ◽  
Road Traffic ◽  
Crash Risk ◽  
Safety Management System ◽  
Road Traffic Safety ◽  
New Framework

Behavioral Analysis of Drivers Following Winter Maintenance Trucks Enabled with Collision Avoidance System

2019 ◽  
Vol 2673 (10) ◽  
pp. 394-404
Author(s):  
Rajat Verma ◽  
Ramin Saedi ◽  
Ali Zockaie ◽  
Timothy J. Gates
Keyword(s):  
Collision Avoidance ◽  
Traffic Safety ◽  
Response Times ◽  
Regression Tree ◽  
Field Testing ◽  
Operating Conditions ◽  
Classification And Regression Tree ◽  
Crash Risk ◽  
Winter Maintenance ◽  
Warning Light

Winter maintenance trucks (WMTs) often operate at lower speeds during inclement weather and roadway conditions, creating potential safety issues for motorists following close behind. In this study, a new prototype radar-based rear-end collision avoidance and mitigation system (CAMS) was tested to assess its impact on the behavior of drivers following WMTs. The system is designed to flash an auxiliary rear-facing warning light upon detection of a vehicle encroaching within an unsafe relative headway with the rear of the WMT. A series of field evaluations was performed during actual winter maintenance operations to assess the effectiveness of the system compared with normal operating conditions (i.e., without the CAMS warning light) toward improving driver behavior related to rear-end crash risk. Specifically, two measures were assessed: (a) rate of vehicles encroaching beyond a safe time headway threshold to the rear of the WMT, and (b) the reaction–response time of drivers. Classification and regression tree models were created for identifying the relevant factors influential in determining the change in driver response. The results indicate that this warning light was effective in reducing the likelihood of the subject drivers crossing beyond a relative headway of 4.5 s. It was also effective in reducing the reaction and response times of the drivers by 0.83 and 0.55 s (36% and 20% reduction), respectively. Although the results were encouraging, additional field testing is recommended before conclusions are drawn regarding the traffic safety impacts of the system.

scholarly journals Vehicle Collision Prediction under Reduced Visibility Conditions

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3026 ◽  
Author(s):  
Keng-Pin Chen ◽  
Pao-Ann Hsiung
Keyword(s):  
Communication Systems ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Collision Probability ◽  
Percentage Error ◽  
Collision Warning ◽  
Congested Traffic ◽  
Prediction Horizon ◽  
Low Visibility ◽  
Velocity Prediction

Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehicle; however, in poor weather conditions such as fog, rain, or snow, the accuracy is significantly affected. In recent years, the advent of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems has introduced new methods for solving the rear-end collision problem. Nevertheless, there is still much left for improvement. For instance, weather conditions have an impact on human-related factors such as response time. To address the issue of collision detection under low visibility conditions, we propose a Visibility-based Collision Warning System (ViCoWS) design that includes four models for prediction horizon estimation, velocity prediction, headway distance prediction, and rear-end collision warning. Based on the history of velocity data, future velocity volumes are predicted. Then, the prediction horizon (number of future time slots to consider) is estimated corresponding to different weather conditions. ViCoWs can respond in real-time to weather conditions with correct collision avoidance warnings. Experiment results show that the mean absolute percentage error of our velocity prediction model is less than 11%. For non-congested traffic under heavy fog (very low visibility of 120 m), ViCoWS warns a driver by as much as 4.5 s prior to a possible future collision. If the fog is medium with a low visibility of 160 m, ViCoWs can give warnings by about 2.1 s prior to a possible future collision. In contrast, the Forward Collision Probability Index (FCPI) method gives warnings by only about 0.6 s before a future collision. For congested traffic under low visibility conditions, ViCoWS can warn a driver by about 1.9 s prior to a possible future collision. In this case, the FCPI method gives 1.2 s for the driver to react before collision.

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