Monte Carlo Analysis of Safe Following Distances Under Different Road Conditions

2003 ◽  
Author(s):  
Scott Kimbrough
Keyword(s):  
Probability Theory ◽  
Real Life ◽  
Monte Carlo Analysis ◽  
Reaction Rates ◽  
The Road ◽  
Lead Driver ◽  
Road Friction ◽  
On The Road ◽  
To Come ◽  
Lead Vehicle

In order to avoid accidents drivers must maintain an adequate amount of separating distance between themselves and vehicles in front of them. If the driver of the lead vehicle suddenly applies his brakes, the driver of the following vehicle needs sufficient time and space to react and apply his brakes to come to a stop. If all vehicles and drivers had the same brake performance, then the required separating distance would simply be the distance traveled while reacting; basically the product of the speed being traveled times the reaction time of the driver. This simple rule would guarantee that a following driver would be able to apply his brakes before arriving at the place on the road where the lead driver applied his brakes. In real life though, all vehicle and drivers do not have the same stopping performance. There are variations due to the different tires on the vehicles, the brake balance of the vehicles, the reaction rates of the drivers, the skills of the drivers, and the traction afforded by the particular wheel paths followed by the vehicles. One way to deal with these variations is to use probability theory [2–6]. In this paper probability theory is used to determine how following distance should vary as a function of speed, average road friction, and variation of the road friction, so that the probability of a collision remains below a desired threshold.

Anti-Lock Wheel Slip Control With an Adaptive Searching Algorithm for the Optimal Slip

2015 ◽  
Author(s):  
Ning Pan ◽  
Liangyao Yu ◽  
Lei Zhang ◽  
Zhizhong Wang ◽  
Jian Song
Keyword(s):  
Lyapunov Theory ◽  
Modulation Amplitude ◽  
Wheel Slip ◽  
Slip Control ◽  
The Road ◽  
Road Friction ◽  
Speed Fluctuation ◽  
On The Road ◽  
Pressure Modulation ◽  
Abs Algorithm

An adaptive searching algorithm for the optimal slip during ABS wheel slip control is proposed. By taking advantage of the fluctuation of wheel slip control, the direction towards the optimal slip can be found, and the target slip calculated by the algorithm asymptotically converged to the optimal slip, which is proved using the Lyapunov theory. A gain-scheduling wheel slip controller is developed to control the wheel slip to the target slip. Simulations on the uniform road and on the road with changed friction are carried out to verify the effectiveness of the proposed algorithm. Simulation results show that the ABS algorithm using the proposed searching algorithm can make full use of the road friction and adapts to road friction changes. Comparing with the conventional rule-based ABS, the pressure modulation amplitude and wheel speed fluctuation is significantly reduced, improving control performance of ABS.

scholarly journals A NEW CAR-FOLLOWING MODEL CONSIDERING ACCELERATION OF LEAD VEHICLE

Transport ◽  
2014 ◽  
Vol 31 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Bingrong Sun ◽  
Na Wu ◽  
Ying-En Ge ◽  
Taewan Kim ◽  
Hongjun Michael Zhang
Keyword(s):  
General Motors ◽  
Weighted Sum ◽  
Relative Speed ◽  
New Model ◽  
Car Following ◽  
Stimulus Response ◽  
The Road ◽  
Car Following Model ◽  
On The Road ◽  
Lead Vehicle

For decades, the general motors (gm) car following model has received a great deal of attention and provided a basic framework to describe the interactions between vehicles on the road. It is based on the stimulus-response assumption that the following vehicle responds to the relative speed between the lead vehicle and itself. However, some of the empirical findings show that the assumption of gm model is not always true and need some modification. For example, the acceleration of the following vehicle is very sensitive to the sign of the relative speed and because of no term in the model that directly represents the leader’s acceleration, the follower’s response to the leader’s acceleration can be retarded. This paper offers a new car-following model that can be considered as a variant of the gm model that can better capture car following behavior. The new model treats the follower’s acceleration as a proportion of a weighted sum of the leader’s acceleration and the relative speed between the lead and following vehicles. This paper compares the new model with the original gm model numerically and the characteristics of the new parameters in the model are investigated. It is also shown that the new model overcomes the shortcomings of the original gm model identified in this paper and gives us more instruments to capture the real-world car-following behavior.

scholarly journals Design Method of ADAS for Urban Electric Vehicle Based on Virtual Prototyping

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Katarzyna Jezierska-Krupa ◽  
Wojciech Skarka
Keyword(s):  
Design Method ◽  
Virtual Prototyping ◽  
Real Life ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Smart Power ◽  
The Road ◽  
Unique Method ◽  
On The Road ◽  
Positive Effect

Since 2012, the Smart Power Team has been actively participating in the Shell Eco-marathon, which is a worldwide competition. From the very beginning, the team has been working to increase driver’s safety on the road by developing Advanced Driver Assistance Systems. This paper presents unique method for designing ADAS systems in order to minimize the costs of the design phase and system implementation and, at the same time, to maximize the positive effect the system has on driver and vehicle safety. The described method is based on using virtual prototyping tool to simulate the system performance in real-life situations. This approach enabled an iterative design process, which resulted in reduction of errors with almost no prototyping and testing costs.

scholarly journals DETERMINATION OF MOST SIGNIFICANT FACTORS FOR ANALYSIS OF HIGHWAY OPERATING CONDITIONS

2017 ◽  
Vol 16 (6) ◽  
pp. 493-497
Author(s):  
M. G. Solodkaya
Keyword(s):  
Real Life ◽  
Operating Conditions ◽  
Dynamic Loads ◽  
Vehicle Speed ◽  
Vehicle Dynamic ◽  
The Road ◽  
Road Pavement ◽  
On The Road ◽  
Significant Factors ◽  
Road System

Traffic circulation on highways is a random process. Therefore automotive damage rate and, respectively, roads on which they are moving is subjected to regularities of random processes. Dynamic processes of vehicle-road interaction are determined to various extents by a host of factors that include road pavement evenness and characteristics of moving vehicles. For this reason the following task has been set: to reveal the most significant factors and mathematically correlate values of vehicle dynamic loads with a quality of road pavement and vehicle speed. Such task statement has not been solved adequately and this situation determines importance and novelty of the investigations in the given direction. While solving the mentioned task the investigations which have been carried out under real-life conditions and with the help of real-life objects are considered as the most reliable ones. However, preparation and execution of such experiments as needed significantly complicates their implementation. In this regard it looks rather expediential to combine a factorial experiment with the tests of a checked model while using ECM with stage-by-stage parameter fixation of working processes passing in “vehicle-road” system, comprehensive assessment pertaining to influence of the selected factors and selection of their optimum combination. Mathematical dependence has been obtained to evaluate influence of several external factors on optimization of vehicle dynamic load on the road. This component makes it possible to attain a simplified and adequate description of element interaction in “vehicle – road” system. While investigating influence of pavement irregularities on maximum dynamic loads on the road influence rate of the selected factors is determined in the following sequence: vehicle weight, pavement evenness and speed of transport facility.

scholarly journals Comparison of Results Obtained by Two Methods of Surface Mapping

2020 ◽  
Vol 16 (1) ◽  
pp. 1-10
Author(s):  
Jozef Melcer ◽  
Eva Merčiaková ◽  
Peter Pisca
Keyword(s):  
Probability Theory ◽  
Primary Source ◽  
Data Sets ◽  
Surface Mapping ◽  
Kinematic Excitation ◽  
The Road ◽  
Comparison Of Results ◽  
Statistics And Probability ◽  
Important Input ◽  
On The Road

AbstractConsidering that the unevenness of the road surface is the primary source of the kinematic excitation of the vehicle, it is necessary to map the unevenness, and then to describe it mathematically. The data sets thus obtained represent an important input for numerical simulations of the motion of vehicles on the road. This paper deals with the analysis and comparison of results from two methods of mapping the surface of the road - exact levelling and spatial scanning. The obtained results are evaluated qualitatively and quantitatively by methods of mathematical statistics and probability theory.

scholarly journals Analysis of the advancements in real-life performance of highly automated vehicles' with regard to the road traffic safety

2018 ◽  
Vol 231 ◽  
pp. 05003 ◽  
Author(s):  
Arkadiusz Matysiak ◽  
Paula Razin
Keyword(s):  
Traffic Safety ◽  
Large Scale ◽  
Road Traffic ◽  
Real Life ◽  
Automated Vehicles ◽  
Automated Driving ◽  
The Road ◽  
Road Traffic Safety ◽  
On The Road ◽  
The Impact

The article presents the analysis of the performance of the vehicles equipped with automated driving systems (ADS) which were tested in real-life road conditions from 2015 to 2017 in the state of California. It aims at the effort to assess the impact on the road safety the continuous technological advancements in driving automation might have, based on of the first large-scale, real-life test deployments. Vehicle manufacturers and other stakeholders testing the highly automated vehicles in California are obliged to issue yearly reports which provide an insight on the test scale as well as the technology maturity. The so-called 'disengagement reports' highlight the range and number of control takeovers between the ADS and driver, which are made either based on driver's decision or information provided by the vehicle itself. The analysis of these reports allowed to investigate the development made in automated driving technology throughout the years of tests, as well as the direct or indirect influence of the external factors (e.g. various weather conditions) on the ADS performance. The results show that there is still a significant gap in reliability and safety between human drivers and highly automated vehicles which has been yet steadily decreasing due to technology advancements made while driving in the specific infrastructure and traffic conditions of California.

scholarly journals Driver Behavior Classification System Analysis Using Machine Learning Methods

2021 ◽  
Vol 11 (22) ◽  
pp. 10562
Author(s):  
Raymond Ghandour ◽  
Albert Jose Potams ◽  
Ilyes Boulkaibet ◽  
Bilel Neji ◽  
Zaher Al Barakeh
Keyword(s):  
Machine Learning ◽  
System Analysis ◽  
Real Life ◽  
Real Data ◽  
Gradient Boosting ◽  
Machine Learning Classification ◽  
The Road ◽  
Machine Learning Methods ◽  
Boosting Method ◽  
On The Road

Distraction while driving occurs when a driver is engaged in non-driving activities. These activities reduce the driver’s attention and focus on the road, therefore increasing the risk of accidents. As a consequence, the number of accidents increases and infrastructure is damaged. Cars are now equipped with different safety precautions that ensure driver awareness and attention at all times. The first step for such systems is to define whether the driver is distracted or not. Different methods are proposed to detect such distractions, but they lack efficiency when tested in real-life situations. In this paper, four machine learning classification methods are implemented and compared to identify drivers’ behavior and distraction situations based on real data corresponding to different behaviors such as aggressive, drowsy and normal. The data were randomized for a better application of the methods. We demonstrate that the gradient boosting method outperforms the other used classifiers.

scholarly journals Towards a Decision-Making Algorithm for Automatic Lane Change Manoeuvre Considering Traffic Dynamics

2016 ◽  
Vol 28 (2) ◽  
pp. 91-103 ◽  
Author(s):  
Sajjad Samiee ◽  
Shahram Azadi ◽  
Reza Kazemi ◽  
Arno Eichberger
Keyword(s):  
Decision Making ◽  
Environmental Conditions ◽  
Lateral Position ◽  
Lane Change ◽  
Lateral Movement ◽  
Traffic Dynamics ◽  
The Road ◽  
Road Friction ◽  
On The Road ◽  
Novel Algorithm

This paper proposes a novel algorithm for decision-making on autonomous lane change manoeuvre in vehicles. The proposed approach defines a number of constraints, based on the vehicle’s dynamics and environmental conditions, which must be satisfied for a safe and comfortable lane change manoeuvre. Inclusion of the lateral position of other vehicles on the road and the tyre-road friction are the main advantages of the proposed algorithm. To develop the lane change manoeuvre decision-making algorithm, first, the equations for the lateral movement of the vehicle in terms of manoeuvre time are produced. Then, the critical manoeuvring time is calculated on the basis of the constraints. Finally, the decision is made on the feasibility of carrying out the manoeuvre by comparing the critical times. Numerous simulations, taking into account the tyre-road friction and vehicles’ inertia and velocity, are conducted to compute thecritical times and a model named TUG-LCA is presented based on the corresponding results.

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