Relevant bibliographies by topics / Driving test of vehicle

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Driving test of vehicle'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Driving test of vehicle"

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Zhao, Danchen, Yaochen Li, and Yuehu Liu. "Simulating Dynamic Driving Behavior in Simulation Test for Unmanned Vehicles via Multi-Sensor Data." Sensors 19, no. 7 (April 8, 2019): 1670. http://dx.doi.org/10.3390/s19071670.

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Driving behavior is the main basis for evaluating the performance of an unmanned vehicle. In simulation tests of unmanned vehicles, in order for simulation results to be approximated to the actual results as much as possible, model of driving behaviors must be able to exhibit actual motion of unmanned vehicles. We propose an automatic approach of simulating dynamic driving behaviors of vehicles in traffic scene represented by image sequences. The spatial topological attributes and appearance attributes of virtual vehicles are computed separately according to the constraint of geometric consistency of sparse 3D space organized by image sequence. To achieve this goal, we need to solve three main problems: Registration of vehicle in a 3D space of road environment, vehicle’s image observed from corresponding viewpoint in the road scene, and consistency of the vehicle and the road environment. After the proposed method was embedded in a scene browser, a typical traffic scene including the intersections was chosen for a virtual vehicle to execute the driving tasks of lane change, overtaking, slowing down and stop, right turn, and U-turn. The experimental results show that different driving behaviors of vehicles in typical traffic scene can be exhibited smoothly and realistically. Our method can also be used for generating simulation data of traffic scenes that are difficult to collect.
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Montazeri-Gh, M., A. Fotouhi, and A. Naderpour. "Driving patterns clustering based on driving features analysis." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 225, no. 6 (May 25, 2011): 1301–17. http://dx.doi.org/10.1177/2041298310392599.

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This article presents driving features analysis in order to determine superior driving features for driving conditions clustering. At first, data gathering is performed in real traffic conditions using advance vehicle location systems. Then driving data segmentation is performed and 21 driving features are defined for each driving segment. After driving feature extraction, the dependency between driving features is investigated. Influence of driving features on vehicle's fuel consumption and exhaust emissions is then studied using computer simulations. The simulation results are then verified by an experimental test. Two types of vehicles, a conventional vehicle and a hybrid electric vehicle (HEV), are simulated. Finally, the most effective driving features are determined. Two superior driving features, ‘energy’ and ‘idle time percentage’, are then used for driving segments clustering. Driving segments clustering may be utilized for driving cycle development, intelligent HEV control, etc.
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Li, Xiao, Zhifei Pang, and Hongxue Zhao. "Research on Construction Method of Urban Driving Cycle of Pure Electric Vehicle." E3S Web of Conferences 252 (2021): 02064. http://dx.doi.org/10.1051/e3sconf/202125202064.

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The driving cycle of the vehicle is taken as the basis of the vehicle test, which plays an important role in improving vehicle performance and reducing energy consumption. Traditional fuel vehicles have been studied more in the current stage. Test conditions specifically for pure electric vehicles have been less studied. The data acquisition method of pure electric vehicle is studied and used to collect driving data. The driving cycle was established through the extraction and analysis of characteristic parameters. The research results can lay a foundation for the research of driving system optimization and energy consumption reduction of pure electric vehicles.
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Lee, Jae-Gil, Kwan Lee, and Seoung-Ho Ryu. "Vehicle Politeness in Driving Situations." Future Internet 11, no. 2 (February 16, 2019): 48. http://dx.doi.org/10.3390/fi11020048.

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Future vehicles are becoming more like driving partners instead of mere machines. With the application of advanced information and communication technologies (ICTs), vehicles perform driving tasks while drivers monitor the functioning states of vehicles. This change in interaction requires a deliberate consideration of how vehicles should present driving-related information. As a way of encouraging drivers to more readily accept instructions from vehicles, we suggest the use of social rules, such as politeness, in human-vehicle interaction. In a 2 × 2 between-subjects experiment, we test the effects of vehicle politeness (plain vs. polite) on drivers’ interaction experiences in two operation situations (normal vs. failure). The results indicate that vehicle politeness improves interaction experience in normal working situations but impedes the experience in failure situations. Specifically, in normal situations, vehicles with polite instructions are highly evaluated for social presence, politeness, satisfaction and intention to use. Theoretical and practical implications on politeness research and speech interaction design are discussed.
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Lyu, Meng, Xiaofeng Bao, Yunjing Wang, and Ronald Matthews. "Analysis of emissions from various driving cycles based on real driving measurements obtained in a high-altitude city." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 6 (February 7, 2020): 1563–71. http://dx.doi.org/10.1177/0954407019898959.

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Vehicle emissions standards and regulations remain weak in high-altitude regions. In this study, vehicle emissions from both the New European Driving Cycle and the Worldwide harmonized Light-duty driving Test Cycle were analyzed by employing on-road test data collected from typical roads in a high-altitude city. On-road measurements were conducted on five light-duty vehicles using a portable emissions measurement system. The certification cycle parameters were synthesized from real-world driving data using the vehicle specific power methodology. The analysis revealed that under real-world driving conditions, all emissions were generally higher than the estimated values for both the New European Driving Cycle and Worldwide harmonized Light-duty driving Test Cycle. Concerning emissions standards, more CO, NOx, and hydrocarbons were emitted by China 3 vehicles than by China 4 vehicles, whereas the CO2 emissions exhibited interesting trends with vehicle displacement and emissions standards. These results have potential implications for policymakers in regard to vehicle emissions management and control strategies aimed at emissions reduction, fleet inspection, and maintenance programs.
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Babangida, Aminu, and Péter Tamás Szemes. "Electric Vehicle Modelling and Simulation of a Light Commercial Vehicle Using PMSM Propulsion." Hungarian Journal of Industry and Chemistry 49, no. 1 (September 21, 2021): 37–46. http://dx.doi.org/10.33927/hjic-2021-06.

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Even though the Internal Combustion Engine (ICE) used in conventional vehicles is one of the major causes of global warming and air pollution, the emission of toxic gases is also harmful to living organisms. Electric propulsion has been developed in modern electric vehicles to replace the ICE.The aim of this research is to use both the Simulink and Simscape toolboxes in MATLAB to model the dynamics of a light commercial vehicle powered by electric propulsion. This research focuses on a Volkswagen Crafter with a diesel propulsion engine manufactured in 2020. A rear-wheel driven electric powertrain based on a Permanent Magnet Synchronous Motor was designed to replace its front-wheel driven diesel engine in an urban environment at low average speeds.In this research, a Nissan Leaf battery with a nominal voltage of 360 V and a capacity of 24 kWh was modelled to serve as the energy source of the electric drivetrain. The New European Driving Cycle was used in this research to evaluate the electric propulsion. Another test input such as a speed ramp was also used to test the vehicle under different road conditions. A Proportional Integral controller was applied to control the speed of both the vehicle and synchronous motor. Different driving cycles were used to test the vehicle. The vehicle demonstrated a good tracking capability in each type of test. In addition, this research determined that the fuel economy of electric vehicles is approximately 19% better than that of conventional vehicles.
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Chen, Gang, and Wei-gong Zhang. "Design of prototype simulation system for driving performance of electromagnetic unmanned robot applied to automotive test." Industrial Robot: An International Journal 42, no. 1 (January 19, 2015): 74–82. http://dx.doi.org/10.1108/ir-06-2014-0353.

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Purpose – The purpose of this paper is to present a prototype simulation system for driving performance of an electromagnetic unmanned robot applied to automotive test (URAT) to solve that it is difficult and dangerous to online debug control program and to quickly obtain test vehicle dynamic performance. Design/methodology/approach – The driving performance of the electromagnetic URAT can be evaluated by the prototype simulation system. The system can simulate various driving conditions of test vehicles. An improved vehicle longitudinal dynamics model matching to the electromagnetic URAT is established. The proposed model has good real-time, and it is easy to implement. The displacement of throttle mechanical leg, brake mechanical leg, clutch mechanical leg and shift mechanical arm is used for the system input. Test vehicle speed and engine speed are used for the system output, and they are obtained by the computation of the established vehicle longitudinal dynamics model. Findings – Driving conditions simulation test and vehicle emission test are performed using a Ford Focus car. Simulation and experiment results show that the proposed prototype simulation system in the paper can simulate the driving conditions of actual vehicles, and the performance that electromagnetic URAT drives an actual vehicle is evaluated by the simulation system. Research limitations/implications – Future research will focus on improving the real time of the proposed simulation system. Practical implications – The autonomous driving performance of electromagnetic URAT can be evaluated by the proposed prototype simulation system. Originality/value – A prototype simulation system for driving performance of an electromagnetic URAT based on an improved vehicle longitudinal dynamics model is proposed in this paper, so that it can solve the difficulty and danger of online debugging control program, quickly obtaining the test vehicle performance.
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Rahman, S. M. Ashrafur, I. M. Rizwanul Fattah, Hwai Chyuan Ong, Fajle Rabbi Ashik, Mohammad Mahmudul Hassan, Md Tausif Murshed, Md Ashraful Imran, et al. "State-of-the-Art of Establishing Test Procedures for Real Driving Gaseous Emissions from Light- and Heavy-Duty Vehicles." Energies 14, no. 14 (July 12, 2021): 4195. http://dx.doi.org/10.3390/en14144195.

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Air pollution caused by vehicle emissions has raised serious public health concerns. Vehicle emissions generally depend on many factors, such as the nature of the vehicle, driving style, traffic conditions, emission control technologies, and operational conditions. Concerns about the certification cycles used by various regulatory authorities are growing due to the difference in emission during certification procedure and Real Driving Emissions (RDE). Under laboratory conditions, certification tests are performed in a ‘chassis dynamometer’ for light-duty vehicles (LDVs) and an ‘engine dynamometer’ for heavy-duty vehicles (HDVs). As a result, the test drive cycles used to measure the automotive emissions do not correctly reflect the vehicle’s real-world driving pattern. Consequently, the RDE regulation is being phased in to reduce the disparity between type approval and vehicle’s real-world emissions. According to this review, different variables such as traffic signals, driving dynamics, congestions, altitude, ambient temperature, and so on have a major influence on actual driving pollution. Aside from that, cold-start and hot-start have been shown to have an effect on on-road pollution. Contrary to common opinion, new technology such as start-stop systems boost automotive emissions rather than decreasing them owing to unfavourable conditions from the point of view of exhaust emissions and exhaust after-treatment systems. In addition, the driving dynamics are not represented in the current laboratory-based test procedures. As a result, it is critical to establish an on-road testing protocol to obtain a true representation of vehicular emissions and reduce emissions to a standard level. The incorporation of RDE clauses into certification procedures would have a positive impact on global air quality.
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He, Ping, Zhu Rong Dong, Cheng Wei Han, and Song Hua Hu. "Design and Test Development of a Comprehensive Performance Test Bench for Electric Wheel." Applied Mechanics and Materials 644-650 (September 2014): 817–22. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.817.

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In order to research the driving performance of electric vehicle driven by the electric wheels and provide the test basis to the design of electric vehicle, the author of the paper designed and developed a multifunctional comprehensive performance test bench for electric wheel. Such test bench has the basic functions of road simulation, resistance simulation, vehicle weight simulation and inertia simulation, and the other functions of steering simulation, coupling simulation of electric braking and mechanical coupling, wheel hub motor performance test lamp. The author of the paper made certain design for the relevant test items, which has far-reaching significance for the test and research of the battery electric vehicle (BEV) driven by the wheel hub motor.
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Zhao, Jian Zhu, Lu Zhang, Guo Ye Wang, Yan Chen, and Zhong Fu Zhang. "Safe Test System for the Turning Vehicles ESP Control Performances on the Lateral Restricted Vehicle System." Advanced Materials Research 694-697 (May 2013): 1334–39. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1334.

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Project the lateral restricted vehicle system to establish a safe and efficient vehicle driving stability control test system. Aimed at Chery A3 car, based on Matlab/Simulink, establish the lateral restricted vehicle dynamic simulation system. Used the braking and driving integrated ESP control strategy, separately analyze the ESP control performances of the independent vehicle system and the lateral restricted vehicle system on three test conditions including neutral steering, under steering, over steering. The research results indicate that the ESP control performances of the lateral restricted vehicle system and the independent vehicle system have great uniformity on the three test conditions, provide a basis for the vehicle driving stability control test research.
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Dissertations / Theses on the topic "Driving test of vehicle"

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Khan, Utsav, and Andrea Bianchi. "Steering system development using test rig and driving simulators." Thesis, KTH, Fordonsdynamik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-265626.

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Conventional model-based development approaches such as Model-in-Loop (MiL) and Software-in-Loop (SiL) have been used in electric power assisted steering (EPAS) development in recent years, but when it involves a physical motor and the vehicle communication network, the development mostly comes down to real vehicle testing and tuning. The objective and outcome of this master thesis is to develop a Hardware-in-Loop (HiL) environment that involves the real EPAS powerpack and human Driver-in-Loop (DiL) using a static driving simulator. The focus is on the study of the performance of the HiL rig in terms of its ability to reproduce steering related Objective Metrics (OMs).In this thesis work, the initial part deals with the study of EPAS systems, HiL test-rigs, objective metrics and real-time simulation environment. The second part deals with the modeling and verification methods of an EPAS system along with HiL testrigs using high and low fidelity vehicle models and steering systems in the MiL and SiL environment.As this thesis work deals with the HiL test rig, some practical problems were faced. These involve implementation and HiL architecture, data transmission between the test rig and the real time simulation environment with rest-bus simulation. Several HiL test-rig issues and limitations are addressed: 1. EPAS torque measurement noise; 2. System bandwidth limitation from control and hardware perspectives; 3. Simulation model; 4. System delays and cogging. Due to these drawbacks the testing scenarios are currently limited between low to mid-frequency vehicle manoeuvres. OM values from HiL simulations accurately compare with real-test data, but the subjective steering feel can still be quite different which is not rep-resented by OMs. Furthermore, the system can be improved by smoothing the reference and control signals by an implementation of low-pass filters or observers, and potentially by different servo control strategies and compensators. Once fully functional, the HiL simulation will be useful during early stage steering system development, being sensitive to changes in a similar way to a real vehicle during testing.
Konventionella modellbaserade utvecklingsmetoder såsom Model-in-Loop (MiL) och Software-in-Loop (SiL) har använts inom utvecklingen av elektriskt servoassisterad styrning (Elec-tric Power Assisted Steering, EPAS) under de senaste åren, men när det handlar om en fysisk motor och kommunikation huvudsakligen med fordonets nätverk, så sker utvecklingen oftast med verkliga fordonstest med nödvändig justering. Syftet och målet med detta examensarbete är att utveckla en HiL-rigg (Hardware-in-Loop) som involverar det verkliga EPAS systemet och Driver-in-Loop (DiL) med hjälp av en statisk körsimulator, där fokus ligger på att studera prestandan för HiL-rigg och dess förmåga att återskapa styrrelaterade Objektiva Mätetal (OM). I detta examensarbete består den inledande delen av studien av EPAS-system, HiL-test-riggar, Objektiva mätetal samt realtidssimuleringsmiljö. Den andra delen består av modellerings- och verifieringsmetoder för ett EPAS-system tillsammans med HiL-testriggar med fordonsmodeller med hög och låg trovärdighet och styrsystem i MiL- och SiL miljöer. Då detta examensarbete involverar en HiL-testrigg har vissa praktiska problem uppstått. Bland problemen var implementering och HiL-arkitektur, dataöverföring mellan testriggen och realtidssimulering med rest-bus simulering. Flertalet problem med en HiL-testrigg och dess begränsningar har behandlats: 1. EPAS-brus i vridmomentmätning; 2. Sys-tembandbreddsbegränsning från regler-och hårdvaruperspektiv; 3. Simuleringsmodell; 4. Systemfördröjningar och ojämnt vridmoment från elmotorn. På grund av dessa nackdelar är testscenarierna för närvarande begränsade till fordonsmanövrar med låga till mellanfrekvensområden. OM-värden från HiL-simuleringar stämmer överens med verkliga testdata, men den subjektiva styrkänslan kan fortfarande kännas ganska annorlunda vilket inte är representerat av OMs. Dessutom kan systemet förbättras genom att referens- och styrsignaler filtreras genom implementering av lågpassfilter eller observatörer, samt med olika servoreglertrategier och kompensatorer. När systemet är fullt funktionellt kan HiL simuleringen vara användbar vid utvecklingen av styrsystemet i ett tidigt skede, då det är känsligt för förändringar likt ett verkligt fordon under testning.
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Romera, Orengo Javier. "Analysis of vehicle ergonomics using a driving test routine in the DHM tool IPS IMMA." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19055.

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The objective of this project is to develop a driving test using a Digital Human Modeling tool (DHM), specifically IPS IMMA, which will allow the evaluation of the ergonomics of the interior of vehicles as currently demanded by the automotive companies. Thus, improving both the design and the design process. This will involve a study of the driving and the tasks carried out by a real person to end up programming them in the DHM software. Based on this study an interface is suggested that guides engineers or ergonomists to design their own driving tests and enable them to evaluate their own designs without a high specialization in DHM tools and software. Taking into account the already present autonomous cars and their future development, the conceptual design of a two positions steering wheel (autonomous/manual driving) will be introduced as an example to be added in the driving test. This example is intended to show how DHM tools can be used to evaluate different designs solutions in early stages of the product development process. This project will be a contribution to one of the sections of the ADOPTIVE project carried out at the University of Skövde and in collaboration with Swedish automotive companies.
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Patil, Mayur. "Test Scenario Development Process and Software-in-the-Loop Testing for Automated Driving Systems." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574794282029419.

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Miller, Erik. "Implementation of a Scale Semi-Autonomous Platoon to Test Control Theory Attacks." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2057.

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With all the advancements in autonomous and connected cars, there is a developing body of research around the security and robustness of driving automation systems. Attacks and mitigations for said attacks have been explored, but almost always solely in software simulations. For this thesis, I led a team to build the foundation for an open source platoon of scale semi-autonomous vehicles. This work will enable future research into implementing theoretical attacks and mitigations. Our 1/10 scale car leverages an Nvidia Jetson, embedded microcontroller, and sensors. The Jetson manages the computer vision, networking, control logic, and overall system control; the embedded microcontroller directly controls the car. A lidar module is responsible for recording distance to the preceding car, and an inertial measurement unit records the velocity of the car itself. I wrote the software for the networking, interprocess, and serial communications, as well as the control logic and system control.
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Cholasta, Lukáš. "Měření a porovnání jízdních parametrů vozidel v různých jízdních režimech." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-232481.

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n this work is processed a summary of selected driving parameters of vehicles, methods of measuring and use in the automotive industry or related branch especially. This work is focused on driving tests of vehicles and measurement driving parameters of vehicles. As part of this work was done measurements parameters of vehicles driving in various driving regimes and subsequent analyse of obtained data. The result of this work is determination methodology division driving regimes and evaluation the impact of driving regimes on to ride a car in a directional curve.
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Fumero, Aguiló María C. "Development of Guidelines for In-Vehicle Information Presentation: Text vs. Speech." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/10067.

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The demand for in-vehicle information systems (IVIS) has been increasing through the years. There are numerous systems that can be incorporated into vehicles and various ways in which the information can and should be presented to the driver. The way the information is presented to the drivers is extremely important in terms of increasing safety and decreasing driver distraction. The expected outcomes of this research included the development of human factors guidelines for the design and use of in-vehicle information systems. It was a desirable goal to identify the most suitable information presentation formats for certain tasks, since this may influence the drivers' attention and driving performance. This study focused on how the factors of interest may affect drivers' attention and driving performance while performing IVIS secondary tasks related to specific applications. This was accomplished through an on-road within-factors experiment. Sixteen participants performed secondary tasks related to three IVIS applications at two levels of difficulty. The tasks were presented using five types of displays. Data collected from video and in-vehicle sensors were statistically analyzed to determine significant effects between the factors. Driving performance, external reaction time, and perceived mental workload results were compiled into general guidelines for the design and use of IVIS. The findings of this study strongly suggest that visual displays should not be used for the presentation of IVIS. Auditory and multi-modal (i.e. both visual and auditory interface) displays are the most appropriate ways to present IVIS information. A normal speech rate is preferred over a fast speech rate. IVIS tasks should be kept as simple as possible in terms of the number of steps. From the three manipulated factors (type of display, IVIS application, and task level of difficulty), the type of display had the largest number of significant results across the dependent variables measurements. The visual display led to the worst driver performance, while auditory and multi-modal displays yielded significantly better driving performance.
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Naujoks, Frederik, Sebastian Hergeth, Katharina Wiedemann, Nadja Schömig, Yannick Forster, and Andreas Keinath. "Test procedure for evaluating the human-machine interface of vehicles with automated driving systems." Taylor & Francis, 2019. https://publish.fid-move.qucosa.de/id/qucosa%3A72242.

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Objective: The human–machine interface (HMI) is a crucial part of every automated driving system (ADS). In the near future, it is likely that—depending on the operational design domain (ODD)—different levels of automation will be available within the same vehicle. The capabilities of a given automation level as well as the operator’s responsibilities must be communicated in an appropriate way. To date, however, there are no agreed-upon evaluation methods that can be used by human factors practitioners as well as researchers to test this. Methods: We developed an iterative test procedure that can be applied during the product development cycle of ADS. The test procedure is specifically designed to evaluate whether minimum requirements as proposed in NHTSA’s automated vehicle policy are met. Results: The proposed evaluation protocol includes (a) a method to identify relevant use cases for testing on the basis of all theoretically possible steady states and mode transitions of a given ADS; (b) an expert-based heuristic assessment to evaluate whether the HMI complies with applicable norms, standards, and best practices; and (c) an empirical evaluation of ADS HMIs using a standardized design for user studies and performance metrics. Conclusions: Each can be used as a stand-alone method or in combination to generate objective, reliable, and valid evaluations of HMIs, focusing on whether they meet minimum requirements. However, we also emphasize that other evaluation aspects such as controllability, misuse, and acceptance are not within the scope of the evaluation protocol.
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Wahlberg, Linnea. "Eyes on the Road! : Off-Road Glance Durations when Performing Tasks on In-Vehicle Systems while Driving in a Simulator." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94622.

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The 85th percentile off-road glances while performing three tasks on an in-vehicle system while driving in a simulator was investigated. The tasks were a radio task, a telephone task and a sound settings task which were performed at three occasions each. The distribution of 85th percentile off-road glance durations for each subject and task showed that durations differed between individuals rather than between tasks. It also turned out that durations longer than 2.00 seconds were not rare and 2 of 16 subjects had durations longer than 2.00 seconds in the radio task. Even though the distribution showed small differences between tasks on an individual level, differences on a group level were found between the tasks. A tendency of a learning effect was found, which implied a decrease in 85th percentile off-road glance durations as the tasks were performed at several occasions. A tendency of a floor effect in 85th percentile off-road glance durations, when the subjects are familiarized with tasks, was also found. Performance on a computerized trail-making test, measuring ability of visual search, motor speed and mental flexibility, was found not to be related with 85th percentile off-road glance durations.
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Matteusson, Theodor, and Niclas Persson. "Statistical Modelling of Plug-In Hybrid Fuel Consumption : A study using data science methods on test fleet driving data." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172812.

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The automotive industry is undertaking major technological steps in an effort to reduce emissions and fight climate change. To reduce the reliability on fossil fuels a lot of research is invested into electric motors (EM) and their applications. One such application is plug-in hybrid electric vehicles (PHEV), in which internal combustion engines (ICE) and EM are used in combination, and take turns to propel the vehicle based on driving conditions. The main optimization problem of PHEV is to decide when to use which motor. If this optimization is done with respect to emissions, the entire electric charge should be used up before the end of the trip. But if the charge is used up too early, latter driving segments for which the optimal choice would have been to use the EM will have to be done using the ICE. To address this optimization problem, we studied the fuel consumption during different driving conditions. These driving conditions are characterized by hundreds of sensors which collect data about the state of the vehicle continuously when driving. From these data, we constructed 150 seconds segments, including e.g. vehicle speed, before new descriptive features were engineered for each segment, e.g. max vehicle speed. By using the characteristics of typical driving conditions specified by the Worldwide Harmonized Light Vehicles Test Cycle (WLTC), segments were labelled as a highway or city road segments. To reduce the dimensions without losing information, principle component analysis was conducted, and a Gaussian mixture model was used to uncover hidden structures in the data. Three machine learning regression models were trained and tested: a linear mixed model, a kernel ridge regression model with linear kernel function, and lastly a kernel ridge regression model with an RBF kernel function. By splitting the data into a training set and a test set the models were evaluated on data which they have not been trained on. The model performance and explanation rate obtained for each model, such as R2, Mean Absolute Error and Mean Squared Error, were compared to find the best model. The study shows that the fuel consumption can be modelled by the sensor data of a PHEV test fleet where 6 features contributes to an explanation ratio of 0.5, thus having highest impact on the fuel consumption. One needs to keep in mind the data were collected during the Covid-19 outbreak where travel patterns were not considered to be normal. No regression model can explain the real world better than what the underlying data does.
Fordonsindustrin vidtar stora tekniska steg för att minska utsläppen och bekämpa klimatförändringar. För att minska tillförlitligheten på fossila bränslen investeras en hel del forskning i elmotorer (EM) och deras tillämpningar. En sådan applikation är laddhybrider (PHEV), där förbränningsmotorer (ICE) och EM används i kombination, och turas om för att driva fordonet baserat på rådande körförhållanden. PHEV: s huvudoptimeringsproblem är att bestämma när man ska använda vilken motor. Om denna optimering görs med avseende på utsläpp bör hela den elektriska laddningen användas innan resan är slut. Men om laddningen används för tidigt måste senare delar av resan, för vilka det optimala valet hade varit att använda EM, göras med ICE. För att ta itu med detta optimeringsproblem, studerade vi bränsleförbrukningen under olika körförhållanden. Dessa körförhållanden kännetecknas av hundratals sensorer som samlar in data om fordonets tillstånd kontinuerligt vid körning. Från dessa data konstruerade vi 150 sekunder segment, inkluderandes exempelvis fordonshastighet, innan nya beskrivande attribut konstruerades för varje segment, exempelvis högsta fordonshastighet. Genom att använda egenskaperna för typiska körförhållanden som specificerats av Worldwide Harmonized Light Vehicles Test Cycle (WLTC), märktes segment som motorvägs- eller stadsvägsegment. För att minska dimensioner på data utan att förlora information, användes principal component analysis och en Gaussian Mixture model för att avslöja dolda strukturer i data. Tre maskininlärnings regressionsmodeller skapades och testades: en linjär blandad modell, en kernel ridge regression modell med linjär kernel funktion och slutligen en en kernel ridge regression modell med RBF kernel funktion. Genom att dela upp informationen i ett tränings set och ett test set utvärderades de tre modellerna på data som de inte har tränats på. För utvärdering och förklaringsgrad av varje modell användes, R2, Mean Absolute Error och Mean Squared Error. Studien visar att bränsleförbrukningen kan modelleras av sensordata för en PHEV-testflotta där 6 stycken attribut har en förklaringsgrad av 0.5 och därmed har störst inflytande på bränsleförbrukningen . Man måste komma ihåg att all data samlades in under Covid-19-utbrottet där resmönster inte ansågs vara normala och att ingen regressionsmodell kan förklara den verkliga världen bättre än vad underliggande data gör.
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Dougherty, Bradley Edward. "Visual and Demographic Factors in Bioptic Driving Training and Road Safety." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366284836.

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Books on the topic "Driving test of vehicle"

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Kwok, Tom. Theory test. London (51a Blackstock Road, London, N4 2JW): Diamond School of Motoring, 1996.

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A guide to the heavy goods vehicle driving test and licences. 5th ed. London: Kogan Page, 1986.

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A guide to the heavy goods vehicle driving test and licences. 6th ed. London: Kogan Page, 1987.

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The official theory test for drivers of large vehicles. 9th ed. London: TSO, 2007.

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The official theory test for drivers of large vehicles: Valid for theory tests taken from 16 July 2001. 2nd ed. London: Stationery Office, 2000.

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CDL exam -- CDL practice test secrets: Your key to exam success. [Beaumont, Tex.]: Mometrix Media, 2013.

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Boyd, Robert A. RV Rite: Step-by-step illustrated driver training and education manual : professional training for all owners/operators of motor homes, fifth wheel trailers, travel trailers, campers, and tent trailers. [Puyallup, Wash: RV Rite, 2003.

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New Jersey. Legislature. Senate. Task Force on Alcohol Related Motor Vehicle Accidents and Fatalities in New Jersey. Public hearing before Senate Task Force on Alcohol Related Motor Vehicle Accidents and Fatalities in New Jersey: Should blood alcohol concentration at which a person is prohibited from operating a motor vehicle be changed. Trenton, N.J: The Unit, 1997.

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Maze, T. H. AMASCOT: Automated mileage and stateline crossing operational test. [Ames, Iowa]: Center for Transportation Research and Education, Iowa State University, 1996.

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Cote, Remy. Driving a passenger vehicle. Quebec: The Societe, 1991.

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Book chapters on the topic "Driving test of vehicle"

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Kistler, Felix, Michael Nadj, Hans-Peter Reifenrath, Stefan Staudacher, and Michael Keckeisen. "Vehicle endurance testing through automated test driving." In Proceedings, 389–401. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29943-9_30.

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Majumdar, Rupak, Aman Mathur, Marcus Pirron, Laura Stegner, and Damien Zufferey. "Paracosm: A Test Framework for Autonomous Driving Simulations." In Fundamental Approaches to Software Engineering, 172–95. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71500-7_9.

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AbstractSystematic testing of autonomous vehicles operating in complex real-world scenarios is a difficult and expensive problem. We present Paracosm, a framework for writing systematic test scenarios for autonomous driving simulations. Paracosm allows users to programmatically describe complex driving situations with specific features, e.g., road layouts and environmental conditions, as well as reactive temporal behaviors of other cars and pedestrians. A systematic exploration of the state space, both for visual features and for reactive interactions with the environment is made possible. We define a notion of test coverage for parameter configurations based on combinatorial testing and low dispersion sequences. Using fuzzing on parameter configurations, our automatic test generator can maximize coverage of various behaviors and find problematic cases. Through empirical evaluations, we demonstrate the capabilities of Paracosm in programmatically modeling parameterized test environments, and in finding problematic scenarios.
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Zhang, Ping, Xiaomin Ding, Yi Zhang, Quan Yuan, and Maoming Sun. "Research on Design and Application of Vehicle Simulation Driving Test Platform for University Lab." In Lecture Notes in Electrical Engineering, 647–54. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6232-2_75.

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Donn, Christian, Michael Folie, Valerie Bensch, Johannes Friebe, Jonathan Spike, Paul Goossens, and Christine Schwarz. "Concept analysis & system design of a hybrid electric vehicle with virtual test driving." In Proceedings, 73–91. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-08844-6_6.

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Fitch, Gregory M., and Richard J. Hanowski. "Using Naturalistic Driving Research to Design, Test and Evaluate Driver Assistance Systems." In Handbook of Intelligent Vehicles, 559–80. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-085-4_21.

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Dennig, Hans-Jörg, Adrian Burri, and Philipp Ganz. "BICAR—Urban Light Electric Vehicle." In Small Electric Vehicles, 157–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_12.

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AbstractThis paper describes the technical features of the light electric vehicle (L2e-category) named BICAR. This specially designed vehicle is an all-in-one emissions-free micro-mobility solution providing a cost-effective and sustainable mobility system while supporting the transition towards a low carbon society (smart and sustainable city concept). The BICAR represents part of a multimodal system, complementing public transport with comfort and safety, relieving inner-city congestion and solving the “first and last mile” issue. The BICAR is the lightest and smallest three-wheel vehicle with weather protection. Due to the space-saving design, six to nine BICARS will fit into a single standard parking space. Safety is increased by an elevated driving position and a tilting mechanism when cornering. The BICAR achieves a range of 40–60 km depending on the battery package configuration in urban transport at a speed of 45 km/h. It features a luggage storage place and exchangeable, rechargeable batteries. The BICAR can be driven without a helmet thanks to the safety belt system, which is engineered for street approved tests. The BICAR has an integrated telematic box connected to the vehicle electronics and communicating with the dedicated mobile application, through which the BICAR can be geo-localised, reserved, locked/unlocked and remotely maintained.
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Han, Chenlei, Alexander Seiffer, Stefan Orf, Frank Hantschel, and Shiqing Li. "Validating Reliability of Automated Driving Functions on a Steerable VEhicle-in-the-Loop (VEL) Test Bench." In Proceedings, 546–59. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-33521-2_37.

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Geneder, S., F. Pfister, C. Wilhelm, A. Arnold, P. Scherrmann, and H. P. Dohmen. "Energy Flux Simulation on a Vehicle Test Bed for Validating the Efficiency of Different Driving and Assistance Systems." In Sustainable Automotive Technologies 2013, 3–13. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01884-3_1.

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Kaths, Jakob, Max-Arno Meyer, Christian Granrath, Jakob Andert, and Sébastien Christiaens. "Virtual test drives with multiple vehicles under test for the evaluation of collaborative assisted and automated driving functions." In Proceedings, 11–20. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-34752-9_2.

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Förster, Martin, Rolf Hettel, Christian Schyr, and Peter E. Pfeffer. "Lateral dynamics on the vehicle test bed – a steering force module as a validation tool for autonomous driving functions." In Proceedings, 163–75. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-22050-1_14.

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Conference papers on the topic "Driving test of vehicle"

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He, Yaohua, Can Yang, and Bo Shang. "Vehicle Driving Wandering Test System Based on LabVIEW." In SAE 2010 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2010. http://dx.doi.org/10.4271/2010-01-0998.

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Peng, Meichun, Xuqi Liu, and Quanzhen Lin. "Construction of Engine Emission Test Driving Cycle of City Transit Buses." In SAE 2015 Commercial Vehicle Engineering Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2015. http://dx.doi.org/10.4271/2015-01-2800.

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Zhou, Xinglin, Yang Wu, and Wensha Lv. "Application of RTK Technology in Vehicle Driving Deviation Test." In 2016 International Forum on Management, Education and Information Technology Application. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/ifmeita-16.2016.118.

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Corti, Enrico. "Vehicle Simulation on the Test Bench." In ASME 2004 Internal Combustion Engine Division Fall Technical Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/icef2004-0834.

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International emission tests (EPA, SFTP, MVEG-B, J-10.15, etc.) are carried out with vehicles running on the rolls dynamometer. Results, in terms of total emissions, are influenced by vehicles parameters such as mass, gear ratios, front surface, drag coefficient, etc. It would be useful, in the automobiles design phase, to have information about the impact of these parameters on total emissions. The obvious solution would be to build up a complete vehicle model to simulate performance and emission levels. Engine pollutants production modeling is the weak point, since it is difficult to obtain reliable results. Anyway it is possible to avoid pollutants production simulation, testing the actual engine under the same operating condition it would face inside the car’s hood. This paper describes a methodology whose aim is to test the engine on a standard test bench, simulating on-board operating conditions. An equivalence condition has to be satisfied in order to guarantee the methodology effectiveness: engine speed and Manifold Absolute Pressure (MAP) must always match for the two types of test performed on the same driving cycle. Engine speed and torque can be controlled through the bench actuators, their values depending on the simulated vehicle motion: once the car dynamics are simulated by means of a model, engine speed and torque corresponding to the given driving cycle can in fact be evaluated. The model is solved in real time, its output being the brake load torque value satisfying the equivalence condition. The brake controller, used as a slave, regulates the engine operating conditions consequently. The global model incorporates tires, aerodynamic forces, clutch, gearbox and driveline behaviors simulation: its response has been first validated comparing its outputs with data measured on board, and then it has been used to control an eddy current brake, for vehicle test simulation on the test bench. Two different control philosophies can be used: either a human driver or an automatic controller can ride the simulated car. The influence of vehicle parameters and gearshift mode on fuel consumption and pollutant emissions can be investigated.
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Hemmati, Maryam, Morteza Biglari-Abhari, and Smail Niar. "Adaptive Vehicle Detection for Real-time Autonomous Driving System." In 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2019. http://dx.doi.org/10.23919/date.2019.8714818.

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Junfu, Huang, Zhang Qiang, Li Chaobin, Xin Chunhong, Yi Kan, and Yang Liangyi. "Study of Test and Evaluation Scenario for L2 level Intelligent Cruising Assist System Based on Natural Driving Data." In SAE 2020 Vehicle Electrification and Autonomous Vehicle Technology Forum. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2020. http://dx.doi.org/10.4271/2020-01-5124.

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Song, Ke, Bin Wei, Tian Zhu, Minyan Gong, Zhen Song, and Huan Chen. "Virtual Co-Simulation Platform for Test and Validation of ADAS and Autonomous Driving." In New Energy & Intelligent Connected Vehicle Technology Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-01-5040.

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Kreft, Sven, Wadim Lorenz, Jan Berssenbru¨gge, Ju¨rgen Gausemeier, and Ansgar Tra¨chtler. "A VR-Based Prototyping and Demonstration Platform Integrating a Fully Active X-by-Wire Test Vehicle." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28732.

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Interconnected basic vehicle functions, such as braking, steering and driving, have great potential to improve vehicle safety and comfort. In order to design and test the necessary control functions, a fully active X-by-wire test vehicle (“Chamaeleon”) has been developed. However, while demonstrating the vehicle’s capabilities with real test drives is of high risk, a driving simulator that integrates the entire vehicle provides safe conditions for interactive demonstration test drives — even for untrained drivers. In this paper, we introduce a driving simulator that is composed of Virtual Reality-based simulation software and the Chamaeleon test vehicle. This provides a prototyping and demonstration platform for integrated vehicle-dynamics control functions. Therefore, we enhanced an existing driving simulator. Moreover, we realized control functions in order to utilize the Chamaeleon’s active suspension to provide a motion platform with three degrees-of-freedom. The driving simulator has proven well as a demonstration platform during two international industry fairs. Here, the main goal was, to interactively illustrate the unconventional steering strategies as well as dedicated functionalities of the Chamaeleon. Although the achieved motion feedback is not very realistic, the presence of motion was very welcomed by fair attendees, who performed a simulated test drive. Additionally, first tests have shown that the driving simulator can be used as a prototyping platform. Here, complex control functions can be tested on actual vehicle hardware, while driving in a secured synthetic environment. This enables engineers to instantly perceive the impacts of the control algorithms on the behavior of the vehicle. This facilitates the development process.
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Young, Richard, Bijaya Aryal, Marius Muresan, Xuru Ding, Steve Oja, and S. Noel Simpson. "Road-to-Lab: Validation of the Static Load Test for Predicting On-Road Driving Performance While Using Advanced In-Vehicle Information and Communication Devices." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2005. http://dx.doi.org/10.17077/drivingassessment.1167.

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Corti, Enrico. "Eddy Current Brake Control for Test Cycles Simulation." In ASME 2003 Internal Combustion Engine Division Spring Technical Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/ices2003-0670.

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On-vehicle (rolls dynamometer or road) tests are usually more expensive and time-consuming than test bench ones. Furthermore, sometimes results would be useful during vehicles design phase. The paper aim is to present a methodology that allows simulating the vehicle on an engine test cell, by properly controlling the bench actuators. Engine operating conditions mainly depend on speed and load, which are determined by the vehicle driving conditions: the speed-time trend assigned for the vehicle must be converted into equivalent speed-time and load-time trends for the engine, and used for feedback control of brake and accelerator actuators. To evaluate the engine load torque it is necessary to know vehicle characteristics (mass, gear ratios, wheels radius, drag coefficient, frontal area, etc.) and driving conditions: the real vehicle can thus be substituted with a virtual vehicle. The methodology has been applied to simulate an ECE-EUDC driving cycle, which is usually carried out on the rolls dynamometer, as imposed by regulations. During such test the vehicle has to follow an assigned speed-time trajectory, while road load and vehicle inertia are simulated and calibrated using a standard procedure. The test is subject to human error, since the driver does not follow exactly the theoretical speed trend, while using robot-drivers increases the setup cost. The same test has been reproduced on a standard engine bench. This setup would be useful to tune the engine correctly and to study the effects of vehicle characteristics variation, thus allowing to determine the correct strategy for emissions reduction, or to estimate the vehicle emission performance, before it is available for chassis dynamometer tests. The same system could be used for real time implementation of control strategies involving both the vehicle and the engine, such as traction control algorithms. Furthermore driving conditions simulations, executed by electronically controlling engine speed and load trajectories, would be more repeatable than human driving on the chassis dynamometer, and their cost would be substantially smaller. The paper shows how the vehicle speed trend can be converted into engine speed and load trends with a physical system model, and then used to control the bench using a real time control system, thus performing a vehicle driving cycle simulation.
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Reports on the topic "Driving test of vehicle"

1

Bodie, Mark, Michael Parker, Alexander Stott, and Bruce Elder. Snow-covered obstacles’ effect on vehicle mobility. Engineer Research and Development Center (U.S.), November 2020. http://dx.doi.org/10.21079/11681/38839.

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The Mobility in Complex Environments project used unmanned aerial systems (UAS) to identify obstacles and to provide path planning in forward operational locations. The UAS were equipped with remote-sensing devices, such as photogrammetry and lidar, to identify obstacles. The path-planning algorithms incorporated the detected obstacles to then identify the fastest and safest vehicle routes. Future algorithms should incorporate vehicle characteristics as each type of vehicle will perform differently over a given obstacle, resulting in distinctive optimal paths. This study explored the effect of snow-covered obstacles on dynamic vehicle response. Vehicle tests used an instrumented HMMWV (high mobility multipurpose wheeled vehicle) driven over obstacles with and without snow cover. Tests showed a 45% reduction in normal force variation and a 43% reduction in body acceleration associated with a 14.5 cm snow cover. To predict vehicle body acceleration and normal force response, we developed two quarter-car models: rigid terrain and deformable snow terrain quarter-car models. The simple quarter models provided reasonable agreement with the vehicle test data. We also used the models to analyze the effects of vehicle parameters, such as ground pressure, to understand the effect of snow cover on vehicle response.
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Kurtz, Jennifer M., Samuel Sprik, Genevieve Saur, and Shaun Onorato. Fuel Cell Electric Vehicle Driving and Fueling Behavior. Office of Scientific and Technical Information (OSTI), March 2019. http://dx.doi.org/10.2172/1501674.

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Fuller, Raymond G. Prolonged Heavy Vehicle Driving Performance: Analysis of Different Types of Following Manoeuvre. Fort Belvoir, VA: Defense Technical Information Center, July 1988. http://dx.doi.org/10.21236/ada198730.

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West, Jeremy, Mark Hoekstra, Jonathan Meer, and Steven Puller. Vehicle Miles (Not) Traveled: Why Fuel Economy Requirements Don't Increase Household Driving. Cambridge, MA: National Bureau of Economic Research, May 2015. http://dx.doi.org/10.3386/w21194.

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Ellis, R. D., Thomas Meitzler, Gary Witus, Euijung Sohn, Darryl Byrk, Richard Goetz, and Grant Gerhart. Computational Modeling of Age-Differences In a Visually Demanding Driving Task: Vehicle Detection. Fort Belvoir, VA: Defense Technical Information Center, October 1997. http://dx.doi.org/10.21236/ada600550.

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Rodier, Caroline. The Potential for Autonomous Vehicle Technologies to Address Barriers to Driving for Individuals with Autism. Mineta Transportation Institute, February 2020. http://dx.doi.org/10.31979/mti.2020.1706.

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Kondo, Yoshinori, and Shinji Kobayashi. A Study on the Relation Between Driving Condition and Nano-Particle Emission From Diesel Vehicle. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0143.

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Davis, Williams. Yeager Airport Hydrogen Vehicle Test Project. Office of Scientific and Technical Information (OSTI), October 2015. http://dx.doi.org/10.2172/1244411.

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Kodama, Kenji, Satoshi Hiranuma, Reiko Doumeki, Yoshinaka Takeda, and Tatsuya Ikeda. Development of DPF System for Commercial Vehicle (Third Report)~Active Regenerating Function in Various Driving Conditions. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0146.

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Norcross, Richard J., Roger V. Bostelman, and Joseph A. Falco. Automated Guided Vehicle Bumper Test Method Development. National Institute of Standards and Technology, May 2015. http://dx.doi.org/10.6028/nist.ir.8029.

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