On-road Testing Research Articles

The value of using the Addenbrookes Cognitive Exam-III and the Rookwood Driving Battery to aid fitness-to-drive decisions with people who have dementia or mild cognitive impairment

Introduction: Further evidence is required to support the use of a combination of a generalist cognitive screen Addenbrookes Cognitive Exam-III and a specialist neuropsychological driving screen Rookwood Driving Battery to aid occupational therapists in making fitness-to-drive decisions for people with dementia. Method: An exploratory retrospective study was completed for drivers with dementia or mild cognitive impairment living within Scotland. Data were extracted from patient notes of drivers referred to occupational therapy, who had an ACE-III and RDB completed within a 6-month timeframe. Results: The study sample included 98 participants. A significant negative correlation was identified between both assessments. Lower cut-off scores were identified on the ACE-III below which no participant scored Rookwood Driving Battery <6 (Addenbrookes Cognitive Exam-III cut-off = 65), or the upper Rookwood Driving Battery pass of ⩽10 (Addenbrookes Cognitive Exam-III cut-off = 54). A small subset of participants ( n = 14) sat the on-road test. No participant passed on-road with a score >7 on the Rookwood Driving Battery. Conclusion: The ACE-III is a useful guide for referral to occupational therapy for assessment using the Rookwood Driving Battery and subsequent fitness-to-drive decisions for people with dementia.

Discriminant Validity of the Standardized On-Road Assessment for Drivers (SOAD) Among Stroke Patients in Japan.

On-road tests are considered the gold standard for evaluating real-world driving skills. However, their reliability and validity remain inadequately established, particularly under varying legal and road conditions across countries. This study investigates the discriminant validity of the closed-course version of the Standardized On-Road Assessment for Drivers (SOAD) in Japan. This study was conducted in five Japanese rehabilitation hospitals and affiliated driving schools. The participants consisted of 108 brain-injured individuals (mean age: 50.0 years) undergoing driving assessments. The inclusion criteria focused on physician-referred patients diagnosed with brain injuries. The SOAD closed-course test, consisting of 40 items, was compared with off-road cognitive assessments, including the Mini-Mental State Examination Japanese Version (MMSE-J), Trail Making TestJapanese Version (TMT-J), Rey-Osterrieth Complex Figure Test, Stroke Drivers Screening Assessment Japanese version (J-SDSA), and Kohs Block Design Test. Spearman's correlation was used to evaluate discriminant validity, distinguishing driving-specific skills from cognitive functions. Weak to moderate correlations were found between SOAD and off-road tests, supporting the discriminant validity of SOAD. Among off-road tests, the J-SDSA dot time correlated most frequently with SOAD items, followed by MMSE-J and TMT-J. The highest correlation coefficient (-0.38) was observed between the J-SDSA dot error and a specific SOAD item. These results show that SOAD demonstrates strong discriminant validity as a closed-course on-road assessment tool for brain-injured individuals and measures unique aspects of driving skills not captured by cognitive tests.

Shared intention and shared awareness for conditional automated driving: An online, randomized video experiment

Objectives In conditional automation for automated vehicles (AVs), drivers are tasked with remaining vigilant and ready to assume control should the system encounter a malfunction. However, little to no information is provided to the driver either about the AV’s intended maneuvers or the AV’s awareness of potential threats in the surrounding environment. To address this research gap, the present study proposes 2 human–machine interaction (HMI) concepts: Firstly, the shared intended pathway (SIP), which presents a forecast of the AV’s intended maneuvers and, secondly, object recognition bounding boxes (ORBBs), which place transparent blue squares around other road users likely to contribute to a crash. Methods An online experiment with both within- and between-group factors tested 2 HMI designs: One with both SIP and ORBB and one with SIP only. Six videos were presented sequentially, each depicting 10 to 15 s of automated driving, to 394 participants (M age = 28.24 years, 64% male) in Australia. Participants monitored the AV in each of the videos, which were presented in 1 of 3 randomized conditions: no HMI display, SIP only, or SIP + ORBB. Questions after each video measured trust, situational awareness, stress, and user acceptance, as measured by the technology acceptance model (TAM) about user acceptance. Results Results suggest that SIP is beneficial in conditional automation monitoring, in terms of reduced stress, increased perceived usefulness, and future intentions to use AVs. Further, ORBB presence increased participant ratings of perceived usefulness and intentions to use AVs compared to no ORBB. The findings also provided support for the TAM, because perceived ease of use and perceived usefulness were found to be significant positive predictors of future intentions to use AVs. Conclusions The current study provides some evidence to suggest that SIP may be beneficial in automated driving. However, further on-road testing of HMI displays for AVs that include SIP and ORBBs are needed to enhance the user experience and acceptability of AVs and to provide more ecological validity.

Development and Experimental Validation of a Physics-Based Identification and Mitigation Strategy for Torsional Vibratory Behavior in Medium-Duty Commercial Vehicle Drivelines

<div>Torsional vibration generated during operation of commercial vehicles can negatively affect the life of driveline components, including the transmission, driveshafts, and rear axle. Undesirable vibrations typically stem from off-specification parts, or excitation at one or more system resonant frequencies. The solution for the former involves getting the system components within specification. As for the latter, the solution involves avoiding excitation at resonance, or modifying the parameters to move the system’s resonant frequencies outside the range of operation through component changes that modify one, or more, component inertia, stiffness, or damping characteristics. One goal of the effort described in this article is to propose, and experimentally demonstrate, a physics-based gear-shifting algorithm that prevents excitation of the system’s resonant frequency if it lies in the vehicle’s range of operation. To guide that effort, analysis was conducted with a numerical simulation model incorporating nonlinear driveline dynamics resulting from engine operation (including misfire and cylinder deactivation), excitation from multiple universal joints, the transmission, and a vehicle speed feedback controller, a contribution the authors have not seen in the pre-existing literature. The experimentally validated simulation results demonstrate that the torsional oscillating mode corresponding to the torque converter or turbine exhibits sensitivity to clutch activation, and variations in system parameters. Consequently, variation in system parameters alters the natural frequency of the system, potentially aligning it with the vehicle’s operational frequency range in specific gear ranges. Experimental on-road tests, described here, demonstrate that for the truck-under-test one of the natural frequencies of the system is within the range of operation for gears 4, 5, and 6 for certain vehicle speeds. Resonance in these gears was successfully prevented, and experimentally demonstrated, by using the proposed algorithm without sacrificing the performance of the vehicle.</div>

Exploring ultrafine particle emission characteristics from in-use light-duty diesel trucks in China using a portable measurement system

Diesel vehicle exhaust is one of the major contributors to ultrafine particles (UFPs) in urban areas in China. However, there is still a lack of knowledge about UFPs emission characteristics from current in-use diesel vehicles. This study has carried out an on-road test of 10 in-use Light-duty Diesel Trucks (LDDTs) with different emission control standards in China using a self-established portable measurement system based on the Electronic Low-pressure Impactor (ELPI) and characterized the ultrafine particle number (PN) concentration, particle size distribution and metal element contents. The results revealed a significant reduction of 93.37% in the average PN0.1 emission factor of LDDTs from China III to China VI. Notably, LDDTs compliant with the China VI vehicle emission control standard exhibited the lowest PN0.1 and PM0.1 emission factors, measuring 4.991 × 1014 #/km and 0.627 g/km, respectively. By taking into account emissions under real driving conditions, we found that the PN emission rates grow with the increase of the Vehicle Specific Power (VSP). The cold-start phase had higher PN emissions than the hot-start phase, with 8590, 1890, 477, and 22 times higher than those of the ambient air (1.18 × 105 #/cm3), respectively. The installation of Diesel Particulate Filter (DPF) can decrease UFPs by more than 99.8%, while the PN emission factor during the DPF regeneration stage (1.85 × 1016 #/km) increased by 5 orders of magnitude that of the DPF normal works (7.51 × 1011 #/km). Metal element contents analysis shows that Fe, Ca, Al and Mg are the dominant elements in UFPs of LDDT exhaust gas, but the element of Ni is slightly increasing in a China VI, possibly due to the new automotive engine exhaust manifolds being made of Ni instead of cast iron for the purpose of having more high-temperature resistance. Our study demonstrates the importance of monitoring and routine maintenance of exhaust after-treatment systems.

Fuel consumption and exhaust emissions from Euro 6d vehicles fueled by innovative LPG/DME blend

The aim of this research was to investigate the exhaust emissions from vehicles when fueled by a new and fully renewable fuel if made of bio-LPG and renewable dimethyl ether (DME), in comparison with standard gasoline. For this purpose, DME was mixed with liquefied petroleum gas (LPG) and used to fuel three bi-fuel LPG/gasoline spark-ignition engines light-duty vehicles. The suitable fuel blend was selected based on several octane tests using CFR engines. Exhaust emissions were tested over the WLTC and over the hot-start CADC cycles, as well as on the road. All Euro 6 standards were well fully met over the WLTC with both fuels. Switching from gasoline to LPG/DME fueling, the CO and NOx emission factors increased for two vehicles, whereas THC and NMHC decreased. Regarding particulates, for two vehicles the emission factors decreased, too. Generally, when the vehicles were driven on the CADC, lower gaseous emissions were observed compared to WLTC: excluding one vehicle, when switching from gasoline to LPG/DME fueling, the overall emission profiles reflected those of the same vehicles run on the WLTC. The unregulated particulate emissions measured over both testing cycles reflect what was detected for the regulated ones. Except for PN10, which was not measured, all regulated emissions were found to meet the (most severe) Euro 7 standards proposed at first by the European Commission. RDE tests showed that all vehicle emissions obtained from on-road tests were also found to meet the RDE standards, regardless of the fueling. Concerning CO2 emissions, LPG/DME fueling guaranteed a systematic decrease for all vehicles and cycles, both on road and in the laboratory. The present investigation aims at demonstrating that the innovative LPG/DME 80 %/20 % (m/m) blend not only can be deemed as potentially suitable for GHG emissions reduction, as long as both DME and propane are obtained from renewable sources, but even compliant with EN 589 and both Euro 6 and part of preliminary Euro 7 exhaust emission proposal.

Emissions of gaseous nitrous acid (HONO) from diesel trucks: Insights from real-driving emission experiments

Nitrous acid (HONO) serves as a substantial contributor in the atmospheric chemistry of hydroxyl radicals (·OH). Despite its significance, the primary sources of atmospheric HONO, particularly diesel truck emissions, have not been thoroughly examined. This study investigated the factors influencing HONO emissions via on-road exhaust emission tests using a self-developed portable measurement system. The findings show that the HONO emissions measured during on-road testing are higher than those measured during chassis dynamometer testing, highlighting the need for on-road tests to capture HONO emissions. Emission standards and truck types greatly influence HONO emission factors (EFs), with stricter regulations leading to lower emissions. The average fuel consumption-based EFs for light-duty diesel trucks ranged from 0.93 g/kg for China III to 0.08 g/kg for China VI. For medium-duty diesel trucks, the EFs decrease from 1.43 g/kg for China III to 0.19 g/kg for China V. Moreover, the vehicle-specific power demonstrated a stronger correlation with HONO emissions. This research showed that HONO emissions were significantly higher without or before the optimal operation of the SCR device, and the device notably reduced HONO emissions. Future research should focus on the impact of various exhaust after-treatment systems and explore HONO conversion mechanisms.

Evaluation of the effectiveness of three different interventions on older driver safety over a 12-month period: study protocol for a randomised controlled trial

IntroductionThe growing population of older drivers presents challenges for road safety attributed to age-related declines and increased crash fatality rates. However, enabling older people to maintain their health and independence...

Assessing the American public’s preferences for reforms to teen driving licensure systems: a discrete choice experiment

ObjectivesTo analyse factors influencing the American public’s preferences for changes to teenage driver licensing requirements.MethodsWe employed a discrete choice experiment (DCE) with 808 participants from National Opinion Research Center’s AmeriSpeak...

Evaluation of steering wheel vibration in electric vehicles and application to Dynamic Motor Drive

Eliminating steering wheel vibration is a key in refining vehicle Noise, Vibration, and Harshness (NVH). The absence of masking engine noise and vibration makes this challenge harder in a pure electric vehicle. This paper provides three key insights with regards to the evaluation of steering wheel vibration in EVs using on-road test data. First, we explore the effects of steering wheel grip variation in the measured accelerometer response. Second, we identify the limitations of evaluating powertrain induced vibration in a noisy environment and propose a post-processing technique to reject irregular road-induced perturbations from the measured data. Third, we evaluate a tuned mass absorber as a localized mitigation tool for steering wheel vibration. Finally, we describe how the above techniques were brought together to deliver a refined NVH experience while integrating Dynamic Motor Drive (DMD) technology as a software-only solution which has been shown to improve EV range by 0.4% on IPM and 3% on EESM based vehicles.

Diesel Fuel Injector Nozzle Reclamation

Diesel engines are integral to various industries due to their efficiency and durability. A key component of these engines is the fuel injector nozzle, which can degrade over time due to contaminants, carbon deposits, and mechanical wear. This paper examines the reclamation process for diesel fuel injector nozzles, highlighting its benefits, challenges, and the validation of reclaimed nozzles. Reclamation offers cost savings, environmental benefits, and extended component life, but requires stringent quality control and adaptation to technological advances. The paper underscores the importance of meticulous reclamation procedures and robust validation methods, such as dyno and on-road testing, to ensure the performance of reclaimed nozzles meets or exceeds original specifications. As diesel technology evolves, the reclamation industry must continuously adapt to maintain its relevance and efficacy.

Modelling CO2 Emissions from Vehicles Fuelled with Compressed Natural Gas Based on On-Road and Chassis Dynamometer Tests

In response to increasingly stringent global environmental policies, this study addresses the pressing need for accurate prediction models of CO2 emissions from vehicles powered by alternative fuels, such as compressed natural gas (CNG). Through experimentation and modelling, one of the pioneering CO2 emission models specifically designed for CNG-powered vehicles is presented. Using data from chassis dynamometer tests and road assessments conducted with a portable emission measurement system (PEMS), the study employs the XGBoost technique within the Optuna Python programming language framework. The validation of the models produced impressive results, with R2 values of 0.9 and 0.7 and RMSE values of 0.49 and 0.71 for chassis dynamometer and road test data, respectively. The robustness and precision of these models offer invaluable information to transportation decision-makers engaged in environmental analyses and policymaking for urban areas, facilitating informed strategies to mitigate vehicular emissions and foster sustainable transportation practices.

Signal synchronization methods when measuring tailpipe emissions with PEMS

This study describes the effects of using different signal synchronization methods on the tailpipe emission factors obtained by on-road tests using PEMS (Portable Emission Measurement Systems). The event-based, static correlation, and dynamics correlation methods were applied to data obtained using different PEMS. The first database included 36 cargo vehicles following the same driving cycle in various cities in Colombia. The second database involved 16 passenger transport vehicles monitored under real operating conditions in Mexico. When comparing results with the event-based synchronization method as the reference, significant differences in emission factors (>25 %) were observed. Those differences depend directly on the physical setup of the PEMS. The dynamic correlation method exhibited the best performance in all cases. When using this method, we recommend to synchronize the CO2 mass flow and fuel consumption variables first and then adjust the obtained synchronization to other species to account for differences in species diffusivities.

Development and Analysis of an On-Road Torque Measurement Device for Trucks

BackgroundRolling resistance and aerodynamic losses cause a significant part of a truck’s energy consumption. Therefore there is an interest from both vehicle manufacturers and regulators to measure these losses to understand, quantify and reduce the energy consumption of vehicles. On-road measurements are particularly interesting because it enables testing in various ambient conditions and road surfaces with vehicles in service.ObjectiveCommon driving loss measurement devices require unique instrumented measurement wheels, which hinders effective measurements of multiple tyre sets or measurements of vehicles in service. For this purpose, the objective is to develop a novel load-sensing device for measuring braking or driving torque.MethodsThe strength of the measurement device is calculated using finite element methods, and the output signal is simulated using virtual strain gauge simulations. In addition to the signal simulation, the device is calibrated using a torsional test rig.ResultsThe simulation results confirm that the device fulfils the strength requirements and is able to resolve low torque levels. The output signal is simulated for the novel cascaded multi-Wheatstone bridge using the strains extracted from the finite element analysis. The simulations and measurements show that the measurement signal is linear and not sensitive to other load directions. The device is tested on a truck, and the effort of mounting the device is comparable to a regular tyre change.ConclusionsA novel driving loss measurement device design is presented with an innovative positioning of strain gauges decoupling the parasitic loads from the driving loss measurements. The design allows on-road testing using conventional wheels without requiring special measurement wheels or instrumentation of drive shafts, enabling more affordable and accurate measurements.

Performance Analysis of Driving Ability (P-Drive): Investigating Construct Validity and Concordance of Australasian Data.

On-road assessment is optimal for determining medical fitness-to-drive but unreliable if determined by global pass/fail decisions alone. Occupational therapists need standardized, psychometrically sound on-road scoring procedures. Performance Analysis of Driving Ability (P-Drive) is a promising on-road test developed in Sweden, but it has not been standardized for Australasia. We investigated the psychometric properties and concordance with an on-road decision of data gathered with the Australasian version of P-Drive. P-Drive was administered to older and cognitively impaired drivers (N = 134) aged 18 to 91 years (mean age 68) who were referred to 10 driving clinics in Australia and New Zealand to determine driving performance. Rasch analysis provided evidence for construct validity and concordance of the data gathered. An optimal cut-off score of 85 was set, yielding evidence of good sensitivity at 88% and specificity at 88%. The Australasian version of P-Drive produces valid and reliable data regarding on-road driving performance.

Validation of a computerized driving simulator test of cognitive abilities for fitness-to-drive assessments.

Driving requires a series of cognitive abilities, many of which are affected by age and medical conditions. The psychosocial importance of continued driving ushers the need for valid measurements in fitness-to-drive assessments. A driving simulator test could prove useful in these assessments, having greater face validity than other off-road tests and being more cost-effective and safer than ordinary on-road testing. The aim of this study was to validate a driving simulator test for assessment of cognitive ability in fitness-to-drive assessments. The study included 67 healthy participants. Internal consistency of the simulator subtests was estimated. A correlation analysis between results on the simulator and the cognitive tests Trail Making Test (TMT) A and B and the Useful field of View test (UFOV) and multiple regression analysis were conducted. Finally, a comparison of results between age groups (>65 years) and (<65 years) was done. Results showed good internal consistency. Significant and moderate correlations were found for all reaction time in the simulator's subtests and UFOV 3, and all but two with TMT A. Lane positioning in the simulator showed significant and low to moderate correlations with UFOV 3 in all subtests. Reaction time and Double reaction time on subtest 3 were significantly correlated with UFOV 2 and UFOV 3 and TMT A, respectively. Test on Centerline (position) in subtest 3 as dependent variable was significantly correlated with UFOV 3. Significant means differences and large effect sizes between the age groups were found for all reaction time and lane positioning tests. The findings of concurrent validity, especially with TMT A and UFOV 3 and its sensitivity for age-related differences, indicate potential for the simulator to be used as a complement in fitness-to-drive assessments. However, a clinical study is necessary to further examine its usefulness for patients with cognitive deficits.

On-Road Vehicle Measurement of Tire Wear Particle Emissions and Approach for Emission Prediction

ABSTRACT Airborne particulate matter has long been associated with negative environmental and health impacts. Tire wear, in the form of particulate matter and microplastics, also poses a potential hazard to human health and the ecosystem. In order to develop measures minimizing tire related pollution, it is necessary to identify and classify all relevant influencing parameters. Within the scope of this study, a measurement vehicle is presented enabling sampling and measurement of tire-induced particles under varying operating conditions. The measurement setup ensures the separation of brake and tire wear and includes particle measurement devices as well as numerous vehicle motion sensors. Based on on-road tests, correlations between driving dynamic parameters and particle emission were analyzed. Furthermore, a first approach for tire-induced particle emission prediction is presented.

Toward better drivability: Investigating user preferences for tip-in acceleration profiles in electric vehicles.

Vehicle drivability, defined as the smooth operation and stability of a vehicle in response to driver inputs, significantly influences the performance of passenger cars. Among various driving conditions, tip-in acceleration is one of the most frequently encountered and crucial factors affecting drivability. This study investigates preferred longitudinal acceleration profiles for electric vehicles through subjective evaluations obtained from on-road tests. Five distinctive acceleration profiles were designed for tip-in conditions and evaluated by 15 highly experienced experts using the paired comparison method. Evaluations were conducted across three scenarios: light tip-in at 30 km/h, middle tip-in at 30 km/h, and middle tip-in at 60 km/h. Experimental results revealed distinct preferences based on driving conditions. For light tip-in at 30 km/h, drivers favored linear acceleration profiles with smaller jerk magnitudes and kurtosis. Conversely, for middle tip-in conditions at both 30 and 60 km/h, drivers preferred acceleration profiles exhibiting rapid initial acceleration followed by a smooth transition. However, at 60 km/h, a preference for higher jerk and steeper gradients was observed. Correlation analyses provided insights into the relationship between subjective preferences and dynamic characteristics of acceleration profiles. This study contributes practical guidance for designing optimal acceleration profiles aligned with driver preferences, thereby enhancing drivability and overall user experience in electric vehicles.

LABORATORY AND ON-ROAD CHARACTERIZATION OF EXHAUST EMISSIONS FROM PLUG-IN HYBRID VEHICLES AT MULTIPLE BATTERY STATES OF CHARGE CONDITIONS

This paper discusses emissions from plug-in hybrid vehicles under various driving scenarios and reports experimental data obtained under laboratory and real-world conditions. Two European plug-in hybrid passenger cars were tested using the two test types in use in the EU (chassis dynamometer and on-road), with some modifications. The best-case and near-worst-case battery states of charge were used for testing. Behavior in terms of CO2 emissions, regulated emissions, and unregulated emissions was characterized and analyzed. Differences were generally much greater for on-road testing, especially for urban driving, during which the potential for purely electrical propulsion of the vehicle is greatest. The long distances covered by current EU legislative test procedures limit the impacts of some effects. Regardless of the traction battery’s state of charge, regulated emissions were well below the applicable EU limits under all driving conditions—for example, combined emissions of reactive nitrogen compounds (nitrogen oxides, ammonia, and nitrous oxide) were consistently &lt; 10 mg/km when tested under laboratory conditions. The two vehicles tested showed that the state of the battery had a large impact on the proportion of electrical propulsion and the resulting CO2 emissions, but differences in regulated pollutants decrease with increasing distance and are generally relatively limited for longer journeys, which include non-urban driving.

Risky driving behavior among individuals with Autism, ADHD, and typically developing persons

IntroductionMany individuals with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) often experience difficulty with driving, including difficulty with obtaining a driver’s license as well as driving safely and efficiently. Such difficulties negatively impact their ability to function independently and participate in daily activities that require driving. ASD and ADHD commonly occur co-morbidly and share many overlapping clinical features. Few studies have directly compared the nature of difficulties in driving safety outcomes between ASD and ADHD. The overarching goal of the current study was to characterize and compare self-reported driving behavior among young autistic drivers, ADHD drivers, and typically developing (TD) drivers. MethodFifty-four participants (14 ASD, 20 ADHD, 20 TD); ages 16–30) completed the Autism Spectrum Quotient and ADHD Adult Rating scale as a method of screening of symptoms. All three groups then completed the Driving Behavior Questionnaire (DBQ), which measured self-reported driving violations, driving errors, and overall risky driving behavior. The three groups of ASD, ADHD, and TD individuals were then compared regarding symptomology and driving behavior differences. ResultsOne-way ANOVAs indicated group differences in DBQ total scores and DBQ errors. Drivers with ADHD reported significantly greater overall risky driving behaviors and driving errors compared to ASD and TD drivers. There were no significant differences between ASD and TD drivers in reported risky driving behaviors and errors. Linear regressions indicated that among all drivers, self-reported ADHD symptoms were significantly associated with higher levels of self-reported overall risky driving and driving errors, regardless of diagnostic group. DiscussionRisky driving and driving errors may be more closely related to symptoms that are characteristic of ADHD. This has implications for individuals with ADHD and autistic individuals who often show or report higher rates of ADHD symptoms. Future studies should compare driving skills of ASD and ADHD drivers using objective measures of driving performance, such as driving simulators or on-road tests.