Prospective and retrospective performance assessment of Advanced Driver Assistance Systems in imminent collision scenarios: the CMI-Vr approach

Structured abstract Introduction Prospective and retrospective performance assessment of Advanced Driver Assistance Systems (ADASs) is fundamental to pilot future enhancements for active safety devices. In critical road scenarios between two vehicles where ADAS activation enables collision mitigation only, currently available assessment methodologies rely on the reconstruction of the impact phase consequent to the specific intervention on braking and steering: the velocity change sustained by the vehicle in the collision ($$\Delta V$$ Δ V ) is retrieved, so that IR decrease for the vehicle occupants can be obtained by appropriate Injury Risk (IR) models. However, information regarding the ADAS performance is available only after the impact phase reconstruction and not just as when the criticality occurs in the pre-impact phase: the best braking and steering alternative cannot be immediately envisaged, since a direct correlation lacks between the braking/steering intervention and IR. Method This work highlights an ADAS performance assessment method based on the disaggregation of $$\Delta V$$ Δ V in the two pre-impact parameters closing velocity at collision ($$V_r$$ V r ) and impact eccentricity, represented by the Crash Momentum Index (CMI). Such a disaggregation leads to the determination of IR based solely on impact configuration between the vehicles, without directly considering the impact phase. The performance of diverse ADASs in terms of intervention logic are directly comparable based on the resulting impact configuration, associated with a single coordinate in the CMI-$$V_r$$ V r plane and a sole IR value as a consequence. Results The CMI-$$V_r$$ V r approach is employable for both purposes of prospective and retrospective performance assessment of ADAS devices. To illustrate the advantages of the methodology, a solution for prospective assessment based on the CMI-$$V_r$$ V r plane is initially proposed and applied to case studies: this provides direct suggestions regarding the most appropriate interventions on braking and steering for IR minimization, fundamental in the tuning or development phase of an ADAS. A method for retrospective assessment is ultimately contextualized in the EuroNCAP "Car-to-Car Rear moving" test for an Inter-Urban Autonomous Emergency Braking system, a device implemented on a significant portion of the circulating fleet. Conclusions Based on the evidenced highlights, it is demonstrated that the approach provides complementary information compared to well-established performance assessment methodologies in all stages of an ADAS life cycle, by suggesting a direct physical connection in the pre-impact phase between the possible ADAS interventions and the foreseeable injury outcomes

Methods and models for safety benefit assessment of advanced driver assistance systems in car-to-cyclist conflicts

To help drivers avoid or mitigate the severity of crashes, advanced driver assistance systems (ADAS) can be designed to provide warnings or interventions. Prospective safety assessment of ADAS is important to quantify and optimise their safety benefit. Such safety assessment methods include, for example, virtual simulations and test-track testing.Today, there are many components of virtual safety assessment simulations with models or methods that are missing or can be substantially improved. This is particularly true for simulations assessing ADASs that address crashes involving cyclists—a crash type that is not decreasing at the same rate as the overall number of road crashes in Europe. The specific methodological gaps that this work addresses are: a) computational driver models for car-to-cyclist overtaking, b) algorithms for model fitting and efficient calculation of ADAS intervention time, and c) a method for merging data from different data sources into the safety assessment.Specifically, for a), different driver models for everyday driver behaviour while overtaking cyclists in a naturalistic driving setting were derived and compared. For b), computationally efficient algorithms to fit driver models to data and compute ADAS intervention time were developed for different types of vehicle models. The algorithms can be included in ADAS both for offline use in virtual assessment simulations and online real-time use in in-vehicle ADAS. Lastly, for c), a method was developed that uses Bayesian statistics to combine results from different data sources, e.g., simulations and test-track data, for ADAS safety benefit assessment.In addition to presenting five peer-reviewed scientific publications, which address these issues, this compilation thesis discusses the use of different data sources; introduces the fundamentals of Bayesian inference, linear programming, and numerical root-finding algorithms; and provides the rationale for methodological choices made, where relevant. Finally, this thesis describes the relationships among the publications and places them into context with existing literature.This work developed driver models for the virtual simulations and methods for the reliable estimation of the prospective safety benefit, which together have the potential to improve the design and the evaluation of ADAS in general, and ADAS for the car-to-cyclist overtaking scenario in particular

Defining procedures and simulation tools to test high levels of automation for cars in realistic traffic, driving and boundary conditions

Il crescente livello di automazione nella guida dei veicoli su gomma rende sempre più complesse e articolate le procedure di testing e validazione dei dispositivi. La tendenza alla realizzazione di sistemi che sostituiscano il guidatore in tutto o in parte, determina un cambiamento paradigmatico nell'ambito della validazione, la quale non può più occuparsi esclusivamente del test del corretto funzionamento del dispositivo da validare, ma dovrà testare le logiche di guida e le "scelte" che opera al variare dei contesti. Come ampiamente evidenziato nella letteratura scientifica di settore1 i processi di validazione rappresenteranno il più grande ostacolo alla realizzazione e messa in produzione dei sistemi di quarto e quinto livello SAE2 di automazione. Numerose ricerche hanno dimostrato3 che il testing su strada non rappresenta una soluzione che possa dare risultati attendibili in tempi sufficientemente brevi, ma a tutt'oggi non esistono software sufficientemente complessi da realizzare simulazioni che tengano conto di tutte le variabili necessarie. La ricerca intende definire le corrette procedure di testing di veicoli ad elevato grado di automazione in condizioni di traffico realistiche, avvalendosi di software di simulazione specifici di ogni settore coinvolto nel processo, realizzando uno strumento di testing integrato sufficientemente efficace

A strategic assessment of alternative engineering concepts for a low volume sportscar manufacturer to meet european stage II pedestrian head impact legislative requirements

The Lotus Elite concept car was revealed at the Paris motor show in September 2010 and is a two- door 2+2 Sports Grand Tourer planned to compete in the High Luxury Sportscar vehicle segment and is part of a revolutionary model strategy based on a new platform to revitalise Lotus Cars into a profitable and sustainable business through increased margins and volumes. Future Lotus vehicles will therefore have to comply with any future legislative requirements. These are primarily focussed on vehicle and occupant safety crash performance and these requirements are an important attribute of the proposed Lotus Elite design and development programme. Road traffic fatalities are a worldwide issue according to a report by the World Health Organisation, an estimated 1.2 million people lost their lives and 50 million non-fatal injuries were due to Road Traffic Accidents. Over the past decade automotive safety initiatives have grown in scope to not only include the vehicle occupants but also to pedestrians. Legislation relating to Pedestrian Protection currently exists in the European Union with further requirements and stricter targets planned for introduction in 2012 and beyond. These new requirements pose a quandary for Lotus due to the fact that aesthetic style is an important attribute of delivering Lotus core brand values and legislation requirements relating to pedestrian protection may drive a need to compromise and potentially degrade the impact of this key attribute. These compromises are driven by the potential physical geometric changes that maybe required to the front end surfaces to meet targets. A review of current literature was extensively performed to benchmarking of competitors, identifies industry trends and market landscape to determine what has been, is, and is going to be possibly done in the future to meet pedestrian protection requirements. A set of requirements and targets were defined to enable a more structured review of what technology automotive vehicle manufacturers and suppliers are offering and whether these technologies or strategies could meet the needs of the Lotus Elite to meet requirements. The current status of the Lotus Elite showcar relating to the achievement of pedestrian protection head impact requirements was derived. Identifying the head impact landscape of the vehicle geometry and highlighted areas of the vehicle that require further analysis and engineering focus to meet pedestrian protection targets. Both legislative and consumer test regime validity to ‘real’ world accident injury data are reviewed and discussed with a view that existing test criteria and methods do not address the primary causes of injury to pedestrians in the windscreen and ‘A’ pillar areas. Conclusions draws on research and CAE testing carried out by the Lotus Cars Engineering team to recommend that Elite must meet pedestrian protection requirements in order to support its growth strategy. The adoption of a passive pedestrian protection design strategy is also proposed by the Elite programme team, potentially allowing a lower technical risk and a faster time to market with reduced cost compared to active systems.Engineering and Physical Sciences (EPSRC)Automotive Technology Managemen

Dynamic Human Body Models in Vehicle Safety: An Overview

Significant trends in the vehicle industry are autonomous driving, micromobility, electrification and the increased use of shared mobility solutions. These new vehicle automation and mobility classes lead to a larger number of occupant positions, interiors and load directions. As safety systems interact with and protect occupants, it is essential to place the human, with its variability and vulnerability, at the center of the design and operation of these systems. Digital human body models (HBMs) can help meet these requirements and are therefore increasingly being integrated into the development of new vehicle models. This contribution provides an overview of current HBMs and their applications in vehicle safety in different driving modes. The authors briefly introduce the underlying mathematical methods and present a selection of HBMs to the reader. An overview table with guideline values for simulation times, common applications and available variants of the models is provided. To provide insight into the broad application of HBMs, the authors present three case studies in the field of vehicle safety: (i) in-crash finite element simulations and injuries of riders on a motorcycle; (ii) scenario-based assessment of the active pre-crash behavior of occupants with the Madymo multibody HBM; (iii) prediction of human behavior in a take-over scenario using the EMMA model

Towards Safe Autonomous Driving

Autonomous driving is expected to bring several benefits, in particular regarding safety. This thesis aim to contribute towards two questions concerning safety: "What is the potential safety benefit of autonomous driving?\u27\u27 and "How can we ensure safe operation of such vehicles?\u27\u27.In the first part of the thesis, methods for evaluating the safety benefit are investigated. In particular predictive effectiveness evaluation based on resimulation of accident data, using models to estimate new outcomes in case the safety system had been available. To illustrate the methodology, four examples of gradual increase in model complexity are presented. First, an Autonomous Emergency Braking (AEB) system using a sensor model, decision algorithm, vehicle dynamics model and regression based injury model. This is extended in a Forward Collision Warning (FCW) system which additionally requires a driver model to simulate driver reactions. The third example shows how an active, AEB, and passive, airbag, system can be combined.\ua0Finally the fourth example combines several systems to emulate a highly automated vehicle. Apart from predicting the real world performance, this analysis also identifies current safety gaps by studying the residual of the accident set.Safety benefit estimation using accident data gives an evaluation on the current accident distributions, however, the systems may introduce new accidents if not operated as intended. In the second part of the thesis, safety verification processes with the intent of preventing unsafe operation, are presented. This is particularly challenging for machine learning based components, such as neural networks. In this case, traditional analytical verification approaches are\ua0difficult to apply due to the non-linearity and high dimensional parameter spaces. Similarly, statistical safety arguments often require unfeasible amounts of annotated validation data. Instead, monitor functions are investigated as a complement to increase safety during operation. The method presented estimates the similarity of the driving environment, compared to the training data, where decisions inferred from novel data can be considered less reliable.\ua0Although not providing a complete safety assurance, the methodology show promising initial results for increasing safety. In addition, it could potentially be used to collect novel data and reduce redundancy in training data

Modeling, Simulation and Prediction of Vehicle Crashworthiness in Full Frontal Impact

Vehicle crashworthiness assessment is critical to help reduce road accident fatalities and ensure safer vehicles for road users. Techniques to assess crashworthiness include physical tests and mathematical modeling and simulation of crash events, the latter is preferred as mathematical modeling is generally cheaper to perform in comparison with physical testing. The most common mathematical modeling technique used for crashworthiness assessment is nonlinear Finite Element (FE) modeling. However, a problem with the use of Finite Element Model (FEM) for crashworthiness assessment is inaccessibility to individual researchers, public bodies, small universities and engineering companies due to need for detailed CAD data, software licence costs along with high computational demands. This thesis investigates modeling strategies which are affordable, computationally and labour inexpensive, and could be used by the above-mentioned groups. Use of Lumped Parameter Models (LPM) capable of capturing vehicle parameters contributing to vehicle crashworthiness has been proposed as an alternative to adopting FEM, while the later have been used to validate LPMs developed in this thesis. The main crash scenario analysed is a full frontal impact against a rigid barrier. Front-end deformation which can be used to measure crash energy absorption and pitching which could lead to occupant injuries in a frontal crash event are parameters focused on. The thesis investigates two types of vehicles; vehicle with initial structure intact is defined as baseline vehicle, while a vehicle that underwent unprofessional repairs on its structural members made of Ultra High Strength Steel (UHSS) is defined as a modified vehicle. The proposed novel LPM for a baseline vehicle impact is inspired by pendulum motion and expresses the system using Lagrangian formulation to predict the two phases of impact: front-end deformation and vehicle pitching. Changes in crashworthiness performance of a modified vehicle were investigated with a FEM; tensile tests on UHSS coupons were conducted to generate material inputs for this FEM. Further, a full scale crash test was conducted to validate the FE simulations. An LPM to conduct crashworthiness assessment of a modified vehicle has been proposed, it is based on a double pendulum with a torsional spring representing the vehicle undergoing a full frontal impact.publishedVersio

DEVELOPMENT OF A CONTROL ALGORITHM FOR A PARALLEL HYBRID POWERTRAIN

The current legislation calls for fast electrification of vehicle powertrains, since it is necessary to fulfil the CO2 requirements for the vehicle fleets. The hybrid electric vehicles (HEV) with parallel powertrain topologies – together with pure battery electric vehicles (BEV) – are the most common ways of electrification. However, the HEV powertrain – opposed to the BEV or conventional powertrain – poses an interesting challenge associated with the control system design to achieve the ideal power split between an internal combustion engine (ICE) and electrical machines (EM) during the whole vehicle operation.The presented paper sums up the specific functions and requirements on a control system, together with the description of general control strategy options for a HEV powertrain. The proposed control strategy then combines heuristic rules with a suboptimal numerical control method, calculating the optimal power split ratio based on the efficiencies of ICE and EMs. This control strategy is built into a modular algorithm in Matlab/Simulink for two different parallel HEV powertrain topologies: P2 and P0P4. It is subsequently coupled with a vehicle models created in GT-Suite environment and tested on a WLTC homologation driving cycles. The following simulation tests show the fuel consumption reduction potential for chosen HEV topologies working in hybrid modes, in comparison to a base operation with conventional mode only. Yet, the heuristic rules can be further optimized to obtain even better overall results.Současná legislativa tlačí výrobce vozidel k okamžité elektrifikaci pohonu, protože je to v tuto chvíli jediná možnost, jak dostát požadavkům na flotilové emise CO2. Nejběžnější formou elektrifikace pohonu jsou v dnešní době vozidla s paralelním hybridním pohonem anebo bateriové elektromobily. Nicméně hybridní pohon, na rozdíl právě od konvenčního nebo čistě elektrického pohonu, představuje zajímavé výzvy spojené s návrhem řídicího algoritmu, který musí v každém okamžiku zajišťovat optimální rozdělení výkonu mezi spalovací motor a elektromotor.Tento článek v úvodu krátce shrnuje specifické funkce a požadavky na takový řídicí algoritmus, společně s obecným přehledem možných řídicích strategií hybridních vozidel. Následně je navržena řídicí strategie kombinující heuristická pravidla se suboptimální numerickou metodou, která vypočítává parametr optimálního dělení výkonu na základě účinností spalovacího motoru a elektromotoru. Na základě navrhnuté strategie je v programu Matlab/Simulink vytvořen modulární řídicí algoritmus pro dvě paralelní hybridní topologie: P2 a P0P4, který je následně propojen s modely vozidel vytvořenými v simulačním prostředí GT-Suite a testován v homologačním cyklu WLTC. Nakonec je prezentováno několik testů řídicího algoritmu, které demonstrují úsporu paliva vybraných topologií hybridního vozidla pracujících v hybridních režimech, ve srovnání s provozem pouze v konvenčním režimu pohonu. Avšak heuristická pravidla mohou být dále optimalizována, s cílem dosáhnout ještě příznivějších celkových výsledků

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety