Abstract In the near future, autonomous vehicles (AVs) may cohabit with human drivers in mixed traffic. This cohabitation raises serious challenges, both terms of traffic flow and individual mobility, as well from road safety point view. Mixed fail to fulfill expected security requirements due heterogeneity unpredictability drivers, cars could then monopolize Using multi-agent reinforcement learning (MARL) algorithms, researchers have attempted design for scenarios, this paper investigates...

This paper focuses on a combination of reliability-based approach and an empirical modelling for rollover risk assessment heavy vehicles. A warning system is developed to alert the driver potential before entering into bend. The idea behind proposed methodology estimate by probability that vehicle load transfer ratio (LTR) exceeds critical threshold. Accordingly, so-called reliability index may be used as measure assess safe functioning. In method, computing maximum LTR requires predict...

In this paper, a machine-learning framework is used for riding pattern recognition. The problem formulated as classification task to identify the class of patterns using data collected from 3-D accelerometer/gyroscope sensors mounted on motorcycles. These measurements constitute an experimental database analyze powered two-wheeler rider behavior. Several well-known techniques are investigated, including Gaussian mixture models, k-nearest neighbor model, support vector machines, random...

Driving errors are considered to be the greatest contributory cause in all road accidents and an important of most fatal accidents. This is particularly case for users powered two-wheeled vehicles (PTWs), perhaps because PTW riders play a greater role control their vehicles' stability than four-wheeled vehicle drivers. Thus, observing analyzing evolution riders' behavior real-life context step identification environment characteristics that constitute risk factor riders. A relevant research...

This paper presents a simple and efficient methodology that uses both acceleration angular velocity signals to detect fall of Powered Two Wheelers (PTW). Detecting the rider's (before impact rider on ground) can indeed be used provide signal in order trigger inflation an airbag jacket worn by rider, reducing thus injury severity. The detection is therefore formulated as sequential anomaly problem. investigates popular method namely Multivariate CUmulative SUM (MCUSUM) control charts such...

Fog is a local meteorological phenomena which drastically reduces the visibility range. detection and range estimation are critical tasks for road operators who need to warn drivers advise them on speed reductions. To achieve this task, fixed sensors quite accurate but they have reduced spatial cover. Mobile less accurate, good Based combination of roadside in-vehicle devices (sensors or fog lamps), data fusion framework presented aiming at taking advantages both mobile extensive density....

The vehicles real trajectories analysis on dangerous zones is an important task to improve the road safety. objective of this study provide tools for driving behaviour identification with associated risk as regards handling loss. This aims take into account infrastructure, driver and vehicle interactions, which are useful evaluate accurately.We propose in paper a bend within suitable Support Vector Machine (SVM) algorithm framework. At first, we will be interested trajectory definition...

In this paper, we develop a simple and efficient methodology for riding patterns recognition based on machine learning framework. The pattern problem is formulated as classification aiming to identify the class of situation by using data collected from three-accelerometer three-gyroscope sensors mounted motorcycle. These measurements constitute experimental database which valuable analyze Powered Two Wheelers (PTW) rider behavior. Five well known techniques are used: Gaussian mixture models...

An efficient diagnosis method dedicated to embedded wiring network based on reflectometry technique is developed in this study. The proposed methodology the two complementary steps. In first step, time‐domain (TDR) simulated, by RLCG ( R : resistance, L inductance, C capacitance and G conductance) circuit model numerical finite‐difference method, at same time datasets are created. second support vector machine (SVM) algorithm combined with a principal component analysis identify faults from...

Motorcycle drivers are considered among the most vulnerable road users, as attested by number of crashes increasing every year. The significant part fatalities relates to “single vehicle” loss control in bends. During this investigation, a system based on an instrumented multi-sensor platform and algorithmic study was developed accurately reconstruct motorcycle trajectories achieved when negotiating This is used French Gendarmerie order objectively evaluate examine way riders take their...

Human errors are the primary cause of powered two-wheeler crashes worldwide due to demanding control required and often ineffective rider-training programs. Literature on rider behaviour is limited, partly lack standard investigation methodologies. This work investigated differences in riding style capability a diverse set riders. It explored impact familiarisation instruction through objective metrics. Correlation with experience was particular focus. Seven riders various levels performed...

In this data article, we will present the coming from 3D Inertial Measurement Unit (3-accelerometers and 3-gyroscopes sensors) mounted on motorcycle collected during a motorcycle's falls experiments. Developing fall events detection algorithms is very challenging task because falling multi-factorial strongly influenced by many unknown factors. To solve issue, one solution can be to use data-set controlled experiments, knowing that real cannot replicated, stuntman chosen as close reality...

The objective of this work, is performance handling and maneuverability, by means the observation vehicle dynamics in order to obtain safer an easier driving. First second sliding mode observers are developed estimate state. Lateral forces estimated a last step.

In this paper a new wiring network diagnosis approach dedicated to embedded system based on Time Domain Reflectometry (TDR) response is proposed. The method two complementary steps namely the forward and inverse models. model used generate TDR using RLCG circuit Finite-Difference Time-Domaine (FDTD) method, create datasets. allows detect, localize characterize faults from time of faulty by Random Forest (RF) technique. Two types RF models have been in procedure: classifiers regression...

The understanding of rider/vehicle interaction modalities remains an issue, specifically in the case bend-taking. This difficulty results both from lack adequate instrumentation to conduct this type study and variety practices population road users. Riders have numerous explanations strategies for controlling their motorcycles when taking bends. objective paper is develop a data-driven methodology order identify typical riding behaviors bends by using clustering methods. real dataset used...

This paper addresses the use of existing widespread Inductive Loops Detector (ILD) Network for realizing an estimation individual travel time a mixed population cars and trucks. The aim is to provide traffic information both users managers. identification vehicles realized by comparing destination inductive signature features with origin using method. In this paper, we propose three methods : Bayesian based learning approach, fuzzy logic method SVM These are evaluated on real site. order...

In a semiconductor factory, Parametric Tests (PT) are performed to check if particular product is within certain predefined specifications, and detect possible process drifts as early possible. addition, PT results used decide based on Statistical Process Control (SPC) charts whether accept or reject wafer <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . These methods lead stop many lots unnecessarily. this paper, we introduce an...

Analysis of human driving behavior aims to inspect drivers’ in the real-world and a virtual environment. The study behaviors can be conducted naturalistic situations or controlled experiments. Analyzing based on data collected experiments environment is beneficial fill many knowledge gaps about risk factors. amount during complex with laps drivers tested under different experimental conditions instructions huge. such thus considered challenging time-consuming if done manually because it...

Understanding driver-vehicle interactions remains a challenge, particularly in the case of cornering. This is for powered two-wheeler vehicle (PTWs) users, perhaps because PTW drivers play greater role controlling stability their vehicles than do four-wheeled drivers. difficulty stems from variety practices this population road users when entering, path, and exiting turns. Thus, observing evolution rider behavior during cornering maneuver an essential step identifying environment features...

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