Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving)

[EN] Nowadays, there are many electronic products that incorporate elements and features coming from the research in the field of mobile robotics. For instance, the well-known vacuum cleaning robot Roomba by iRobot, which belongs to the field of service robotics, one of the most active within the sector. There are also numerous autonomous robotic systems in industrial warehouses and plants. It is the case of Autonomous Guided Vehicles (AGVs), which are able to drive completely autonomously in very structured environments. Apart from industry and consumer electronics, within the automotive field there are some devices that give intelligence to the vehicle, derived in most cases from advances in mobile robotics. In fact, more and more often vehicles incorporate Advanced Driver Assistance Systems (ADAS), such as navigation control with automatic speed regulation, lane change and overtaking assistant, automatic parking or collision warning, among other features. However, despite all the advances there are some problems that remain unresolved and can be improved. Collisions and rollovers stand out among the most common accidents of vehicles with manual or autonomous driving. In fact, it is almost impossible to guarantee driving without accidents in unstructured environments where vehicles share the space with other moving agents, such as other vehicles and pedestrians. That is why searching for techniques to improve safety in intelligent vehicles, either autonomous or manual-assisted driving, is still a trending topic within the robotics community. This thesis focuses on the design of tools and techniques for planning and control of intelligent vehicles in order to improve safety and comfort. The dissertation is divided into two parts, the first one on autonomous driving and the second one on manual-assisted driving. The main link between them is the use of clothoids as mathematical formulation for both trajectory generation and collision detection. Among the problems solved the following stand out: obstacle avoidance, rollover avoidance and advanced driver assistance to avoid collisions with pedestrians.[ES] En la actualidad se comercializan infinidad de productos de electrónica de consumo que incorporan elementos y características procedentes de avances en el sector de la robótica móvil. Por ejemplo, el conocido robot aspirador Roomba de la empresa iRobot, el cual pertenece al campo de la robótica de servicio, uno de los más activos en el sector. También hay numerosos sistemas robóticos autónomos en almacenes y plantas industriales. Es el caso de los vehículos autoguiados (AGVs), capaces de conducir de forma totalmente autónoma en entornos muy estructurados. Además de en la industria y en electrónica de consumo, dentro del campo de la automoción también existen dispositivos que dotan de cierta inteligencia al vehículo, derivados la mayoría de las veces de avances en robótica móvil. De hecho, cada vez con mayor frecuencia los vehículos incorporan sistemas avanzados de asistencia al conductor (ADAS por sus siglas en inglés), tales como control de navegación con regulación automática de velocidad, asistente de cambio de carril y adelantamiento, aparcamiento automático o aviso de colisión, entre otras prestaciones. No obstante, pese a todos los avances siguen existiendo problemas sin resolver y que pueden mejorarse. La colisión y el vuelco destacan entre los accidentes más comunes en vehículos con conducción tanto manual como autónoma. De hecho, la dificultad de conducir en entornos desestructurados compartiendo el espacio con otros agentes móviles, tales como coches o personas, hace casi imposible garantizar la conducción sin accidentes. Es por ello que la búsqueda de técnicas para mejorar la seguridad en vehículos inteligentes, ya sean de conducción autónoma o manual asistida, es un tema que siempre está en auge en la comunidad robótica. La presente tesis se centra en el diseño de herramientas y técnicas de planificación y control de vehículos inteligentes, para la mejora de la seguridad y el confort. La disertación se ha dividido en dos partes, la primera sobre conducción autónoma y la segunda sobre conducción manual asistida. El principal nexo de unión es el uso de clotoides como elemento de generación de trayectorias y detección de colisiones. Entre los problemas que se resuelven destacan la evitación de obstáculos, la evitación de vuelcos y la asistencia avanzada al conductor para evitar colisiones con peatones.[CA] En l'actualitat es comercialitzen infinitat de productes d'electrònica de consum que incorporen elements i característiques procedents d'avanços en el sector de la robòtica mòbil. Per exemple, el conegut robot aspirador Roomba de l'empresa iRobot, el qual pertany al camp de la robòtica de servici, un dels més actius en el sector. També hi ha nombrosos sistemes robòtics autònoms en magatzems i plantes industrials. És el cas dels vehicles autoguiats (AGVs), els quals són capaços de conduir de forma totalment autònoma en entorns molt estructurats. A més de en la indústria i en l'electrònica de consum, dins el camp de l'automoció també existeixen dispositius que doten al vehicle de certa intel·ligència, la majoria de les vegades derivats d'avanços en robòtica mòbil. De fet, cada vegada amb més freqüència els vehicles incorporen sistemes avançats d'assistència al conductor (ADAS per les sigles en anglés), com ara control de navegació amb regulació automàtica de velocitat, assistent de canvi de carril i avançament, aparcament automàtic o avís de col·lisió, entre altres prestacions. No obstant això, malgrat tots els avanços segueixen existint problemes sense resoldre i que poden millorar-se. La col·lisió i la bolcada destaquen entre els accidents més comuns en vehicles amb conducció tant manual com autònoma. De fet, la dificultat de conduir en entorns desestructurats compartint l'espai amb altres agents mòbils, tals com cotxes o persones, fa quasi impossible garantitzar la conducció sense accidents. És per això que la recerca de tècniques per millorar la seguretat en vehicles intel·ligents, ja siguen de conducció autònoma o manual assistida, és un tema que sempre està en auge a la comunitat robòtica. La present tesi es centra en el disseny d'eines i tècniques de planificació i control de vehicles intel·ligents, per a la millora de la seguretat i el confort. La dissertació s'ha dividit en dues parts, la primera sobre conducció autònoma i la segona sobre conducció manual assistida. El principal nexe d'unió és l'ús de clotoides com a element de generació de trajectòries i detecció de col·lisions. Entre els problemes que es resolen destaquen l'evitació d'obstacles, l'evitació de bolcades i l'assistència avançada al conductor per evitar col·lisions amb vianants.Girbés Juan, V. (2016). Clothoid-based Planning and Control in Intelligent Vehicles (Autonomous and Manual-Assisted Driving) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/65072TESI

Generación de Trayectorias de Curvatura Continua para el Seguimiento de Líneas basado en Visión Artificial

Desarrollo matemático y análisis de nuevas técnicas para la generación de trayectorias de curvatura continua aplicado al problema del seguimiento de línea con curvatura y brusquedad acotadas.Girbés Juan, V. (2010). Generación de Trayectorias de Curvatura Continua para el Seguimiento de Líneas basado en Visión Artificial. http://hdl.handle.net/10251/12881Archivo delegad

On the Assessment of Fitness to Drive: Steering and Brake Operative Forces

The Directive (EU) 2015/653 aimed at facilitating that the maximum force that any disabled driver could make on the vehicle's primary controls could be adjusted to their needs. The technical adjustment in the vehicle's design requires a measurement of the operational forces applied by the driver on the steering and brake controls, in order to determine its functional capacity during the execution of driving manoeuvres. The objective of this paper is to define the steering and braking operative forces used for driving current-market M1 motor vehicles for the fitness to drive assessment of drivers with physical disabilities. A total of 200 trials were performed with 17 different vehicles and 26 drivers. The results obtained help to define a new threshold's criteria for operative forces onto the steering and braking systems for adapting motor vehicles to disabled drivers. The main contribution of this paper consist on a new technical recommendations about the use of code 20.07 -braking- and 40.01 -steering- to be used in the fitness to drive assessment of driver with disabilities according to Directive (EU) 2015/653 requirements

On the Assessment of Fitness to Drive: Steering and Brake Operative Forces

[EN] The Directive (EU) 2015/653 aimed at facilitating that the maximum force that any disabled driver could make on the vehicle's primary controls could be adjusted to their needs. The technical adjustment in the vehicle's design requires a measurement of the operational forces applied by the driver on the steering and brake controls, in order to determine its functional capacity during the execution of driving maneuvers. The objective of this paper is to define the steering and braking operative forces used for driving current market M1 motor vehicles for the ¿fitness to drive assessment of drivers with physical disabilities. A total of 200 trials were performed with 17 different vehicles and 26 drivers. The results obtained help to define a new threshold's criteria for operative forces onto the steering and braking systems for adapting motor vehicles to disabled drivers. The main contribution of this paper consist on a new technical recommendations about the use of code 20.07 -braking- and 40.01 -steering- to be used in the ¿fitness to drive assessment of driver with disabilities according to Directive (EU) 2015/653 requirements.This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the UPV Ethical Committee at a session celebrated on June 18, 2019, under Reference No. P5_18_06_19.Dols Ruiz, JF.; Girbés-Juan, V.; Jiménez, I. (2021). On the Assessment of Fitness to Drive: Steering and Brake Operative Forces. IEEE Access. 9:134682-134694. https://doi.org/10.1109/ACCESS.2021.3116080134682134694

Data Acquisition System for the Characterization of Biomechanical and Ergonomic Thresholds in Driving Vehicles

[EN] Directive (EU) 2015/653 on driving licenses has involved the modification of different codes that must appear on driver's licenses. The definition of specific codes (20.07 and 40.01) compels measurement of the braking and steering forces. Performing practical tests to assess the driving fitness of special drivers will help to determine the maximum force that a driver can apply on primary controls when driving. From that point, definition of car control adaptations required to supply their functional deficiencies can be stated. This article describes a data acquisition system designed and developed for obtaining data from experimental tests based on the execution of habitual driving manoeuvres (braking, lane change and roundabouts). The data gathered will allow for definition of the thresholds of biomechanical values (forces on the steering wheel and brake pedal) and ergonomic values (driver's upper extremity mobility ranges) necessary for driving motor vehicles. The results have shown that application in real driving tests of the data acquisition system designed provides valid and suitable results for the case studied. Therefore, it will contribute to substantially improving the assessment procedure for drivers in general and for disabled people in particular when obtaining or renewing their driving licenses.This research was funded by Generalitat Valenciana (Spain) under grant APOSTD/2017/055 and by the Universitat Politecnica de Valencia (UPV) (Spain) under the project Characterization of biomechanical and ergonomic thresholds in driving motor vehicles applicable to driver evaluation (Ref. 20190480). This research has been approved by the UPV Ethical Committee at a session celebrated on 18 June 2019 (ref. P5_18_06_19).Dols Ruiz, JF.; Girbés, V.; Luna, Á.; Catalán, J. (2020). Data Acquisition System for the Characterization of Biomechanical and Ergonomic Thresholds in Driving Vehicles. Sustainability. 12(17):1-16. https://doi.org/10.3390/su12177013S1161217Disability Statisticshttps://ec.europa.eu/eurostat/statistics-explained/index.php?title=Disability_statistics_introducedFlash Eurobarometer 345; Accessibility; Report; Directorate-General Justice and Coordinated by Directorate-General for Communication; Brusselshttps://ec.europa.eu/commfrontoffice/publicopinion/flash/fl_345_en.pdfGirbés, V., Hernández, D., Armesto, L., Dols, J., & Sala, A. (2019). Drive Force and Longitudinal Dynamics Estimation in Heavy-Duty Vehicles. Sensors, 19(16), 3515. doi:10.3390/s19163515Dols, J., & Mirabet, E. (2008). Análisis experimental de los rangos de movilidad articular y fuerza muscular requerida para la conducción de vehículos automóviles. Securitas Vialis, 1(1), 17-26. doi:10.1007/s12615-008-9003-zHorberry, T., & Inwood, C. (2010). Defining criteria for the functional assessment of driving. Applied Ergonomics, 41(6), 796-805. doi:10.1016/j.apergo.2010.01.006Dols, J. F., Molina, J., Camacho, F. J., Marín-Morales, J., Pérez-Zuriaga, A. M., & Garcia, A. (2016). Design and Development of Driving Simulator Scenarios for Road Validation Studies. Transportation Research Procedia, 18, 289-296. doi:10.1016/j.trpro.2016.12.03

Haptic Feedback to Assist Bus Drivers for Pedestrian Safety at Low Speed

Buses and coaches are massive Passenger Transportation Systems (PTS), because they represent more than half of land PTS in the European Union. Despite of that, bus accident figures are lower than other means of transport, but its size and weight increase the severity of accidents in which buses are involved, even at low speed. In urban scenarios, turnings and manoeuvres around bus stops are the main causes of accidents, mostly due to low visibility, blind spots or driver s distractions. Therefore, there is an increasing interest in developing driving assistance systems to avoid these situations, among others. However, even though there are some solutions on the market, they are not meant to work in urban areas at low speed and with the sole purpose of preventing collisions with pedestrians. In this sense, the paper proposes an active safety system for buses in manoeuvres at low speed. The safety system consists of haptic feedback devices together with collision avoidance and risk evaluation systems based on detected people nearby the bus. The performance of the active safety system has been validated in a simulated urban scenario. Our results show that driver s reaction time is reduced and time to collision increased due to the proposed low-speed active safety system. In particular, it is shown that there is a reduction in the number of high risk cases and collisions, which implies a considerable improvement in safety terms. In addition to this, a brief discussion about current regulations for innovative safety systems on a real vehicles is carried out.This paper has been funded by Ministerio de Ciencia e Innovacion (Spain) through the projects "Sistemas Avanzados de Seguridad Integral en Autobuses (SAFEBUS)" (IPT-2011-1165-370000) and "Sistemas de Conduccion Segura de Vehiculos de Transporte de Pasajeros y Materiales con Asistencia Haptica/Audiovisual e Interfaces Biomedicas (SAFETRANS)" (DPI2013-42302-R). This work was also supported by Programa VALi+d (Generalitat Valenciana). The authors wish to thank Jose Luis Sanchez Carrascosa for his dedication and commitment to the project and thank to Ana Isabel Sanchez Galdon for her valuable help regarding ANOVA analysis.Girbés, V.; Armesto Ángel, L.; Dols Ruiz, JF.; Tornero Montserrat, J. (2016). Haptic Feedback to Assist Bus Drivers for Pedestrian Safety at Low Speed. IEEE Transactions on Haptics. 9(3):345-357. https://doi.org/10.1109/TOH.2016.2531686S3453579

Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles

In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing data. Our results show that this asynchronous multi-sensor (GPS+IMU+CAN-based odometry) fusion is advantageous in low-speed manoeuvres, improving accuracy and robustness to missing data, thanks to non-causal filtering. The proposed algorithm is based on Extended Kalman Filter and Smoother, with exponential discretization of continuous-time stochastic differential equations, in order to process measurements at arbitrary time instants; it can provide data to subsequent processing steps at arbitrary time instants, not necessarily coincident with the original measurement ones. Given the extra information available in the smoothing case, its estimation performance is less sensitive to the noise-variance parameter setting, compared to causal filtering. Working Matlab code is provided at the end of this work

Drive Force and Longitudinal Dynamics Estimation in Heavy-Duty Vehicles

Modelling the dynamic behaviour of heavy vehicles, such as buses or trucks, can be very useful for driving simulation and training, autonomous driving, crash analysis, etc. However, dynamic modelling of a vehicle is a difficult task because there are many subsystems and signals that affect its behaviour. In addition, it might be hard to combine data because available signals come at different rates, or even some samples might be missed due to disturbances or communication issues. In this paper, we propose a non-invasive data acquisition hardware/software setup to carry out several experiments with an urban bus, in order to collect data from one of the internal communication networks and other embedded systems. Subsequently, non-conventional sampling data fusion using a Kalman filter has been implemented to fuse data gathered from different sources, connected through a wireless network (the vehicle's internal CAN bus messages, IMU, GPS, and other sensors placed in pedals). Our results show that the proposed combination of experimental data gathering and multi-rate filtering algorithm allows useful signal estimation for vehicle identification and modelling, even when data samples are missing

An Active Safety System for Low-Speed Bus Braking Assistance

Accidents in which buses or coaches are involved cause thousands of injuries and fatalities every year. To reduce their number and severity, the paper describes an Advanced Driver Assistance Systems (ADAS) based on a haptic throttle pedal and emergency braking. It also proposes a computationally efficient algorithm with a methodology based on three main concepts: a simplified but accurate vehicle model; an efficient collision detection system considering driver's intention and pedestrians wandering around the vehicle; and a risk evaluation system to generate warnings and emergency braking signals. Finally, the performance of the proposed ADAS is validated using a driving simulation cabin with a very realistic urban scenario and original elements from real buses. The results show a statistically significant improvement in safety, as the number of collisions and high risk situations are clearly minimized, reaction time to press the brake pedal is improved and time to collision increased in emergency situations. Implementation of the proposed ADAS into city buses would potentially improve safety, reducing the frequency and severity of accidents with pedestrians.This work was supported in part by Ministry of Science and Innovation of Spain through the SAFEBUS Project "Sistemas Avanzados de Seguridad Integral en Autobuses" under Grant IPT-2011-1165-370000 and the SAFETRANS Project "Sistemas de Conduccion Segura de Vehiculos de Transporte de Pasajeros y Materiales con Asistencia Haptica/Audiovisual e Interfaces Biomedicas" under Grant DPI2013-42302-R and in part by the Generalitat Valenciana, Programa VALi+d (ACIF/2010/206). The Associate Editor for this paper was E. Kosmatopoulos.Girbés, V.; Armesto Ángel, L.; Dols Ruiz, JF.; Tornero Montserrat, J. (2017). An Active Safety System for Low-Speed Bus Braking Assistance. IEEE Transactions on Intelligent Transportation Systems. 18(2):377-387. https://doi.org/10.1109/TITS.2016.2573921S37738718

Combining haptics and inertial motion capture to enhance remote control of a dual-arm robot

High dexterity is required in tasks in which there is contact between objects, such as surface conditioning (wiping, polishing, scuffing, sanding, etc.), specially when the location of the objects involved is unknown or highly inaccurate because they are moving, like a car body in automotive industry lines. These applications require the human adaptability and the robot accuracy. However, sharing the same workspace is not possible in most cases due to safety issues. Hence, a multi-modal teleoperation system combining haptics and an inertial motion capture system is introduced in this work. The human operator gets the sense of touch thanks to haptic feedback, whereas using the motion capture device allows more naturalistic movements. Visual feedback assistance is also introduced to enhance immersion. A Baxter dual-arm robot is used to offer more flexibility and manoeuvrability, allowing to perform two independent operations simultaneously. Several tests have been carried out to assess the proposed system. As it is shown by the experimental results, the task duration is reduced and the overall performance improves thanks to the proposed teleoperation method