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In Intelligent Transportation Systems (ITS), vehicular networks are enabling technologies for onboard data services such as traffic safety, user infotainment, etc. Vehicular networks face many challenges when it comes to providing satisfactory quality of service, mainly because of issues that arise from unreliable communication in unfavorable propagation conditions. One prime example is Vehicle-to-Vehicle (V2V) communication in the presence of big vehicles that present obstacles in the communication path of smaller vehicles, where the signal strength decays drastically due to the big vehicle shadowing. As a result, the communication range is shortened, and the safety message dissemination capability is reduced. In this paper, we analyze the impact of big vehicle shadowing on V2V communications, taking into account Cellular Vehicle-to-Everything (C-V2X) networks. A geometric as well as a stochastic approach is employed to analyze the length of shadow regions for conventional cars and big vehicles on the road in different scenarios. This paper analyses the effect of large vehicles shadowing on a V2V communication link as a function of the shadow region length. A beamforming-based signal reception technique is proposed in order to mitigate packet collisions caused by hidden nodes. Considering relaying operation by big vehicles, three relaying schemes are proposed to improve the V2V message dissemination performance. Extensive simulations are conducted to demonstrate the effectiveness of the proposed schemes. Agency for Science, Technology and Research (A*STAR) Published version The work of Yong Liang Guan and Hieu T. Nguyen was supported by A*STAR, Singapore through the RIE2020 Advanced Manufacturing and Engineering (AME) Industry Alignment Fund-Pre Positioning (IAF-PP) under Grant A19D6a0053.

The hybrid-electric powertrain currently used in Formula 1 race cars draws its energy from the car's fuel tank and battery. The usable battery size is limited, and refueling during a race is forbidden by the regulations of the Formula 1 race series. From a strategic point of view, lap-by-lap targets for the fuel and battery consumption must be chosen and imposed on the energy management controller of the car. This task is non-trivial due to the influence of the on-board fuel mass on the achievable lap time, as well as the cross-couplings between the electric and the combustion part of the powertrain. A systematic approach is thus required to compute the energy allocation strategy that minimizes the total race time. In this paper, we devise an optimization framework in the form of a non-linear program, yielding the optimal battery and fuel consumption targets for each lap of the race. The approach is based on maps that capture the achievable lap time as a function of car mass and allocated battery and fuel energy. These maps are generated beforehand with a model-based single-lap optimization framework and fitted using artificial neural network techniques. To showcase the approach, we present three case studies: First, we compare the optimal strategy to a heuristic method. The improvement of 2s over the entire race is substantial, given that the difference only lies in the energy allocation, but not in the overall consumption. It underlines the importance of optimizing the energy allocation. Second, we leverage the framework to compute the optimal fuel load at the beginning of the race. Finally, we apply the developed non-linear program in a shrinking-horizon fashion. Our simulation results show that the resulting model predictive controller correctly reacts to disturbances that frequently occur during a race., IEEE Transactions on Vehicular Technology, ISSN:0018-9545, ISSN:1939-9359

To identify patient factors associated with improper restraint usage and worse trauma outcomes for pediatric patients involved in motor vehicle collisions (MVCs).Retrospective study performed at a Level I pediatric trauma center for patients (≤18 yr) evaluated after MVC between 2008 and 2018. The Area Deprivation Index (ADI) was used to measure neighborhood socioeconomic disadvantage (NSD) levels based on the patient's home address. Trauma registry data was correlated to ADI and used to analyze appropriate restraint usage by NSD. Proper restraint practices were defined based on national guidelines and state laws. Demographics and clinical outcomes were also analyzed. Chi-square analysis with Bonferroni corrections was used to assess the association of ADI, race, and ethnicity with proper restraint usage.Among 1152 patients included, approximately 50% were male, the median age was 7 years [IQR 4-10], and 53% were of Hispanic ethnicity. Hispanic patients comprised 73% of children in ADI quintile 5 (greatest NSD), yet only 26% of children in ADI quintile 1 (least NSD). No differences were observed across clinical data and outcomes. Hispanic children8 yr were significantly less likely to be in a car seat/booster seat compared to non-Hispanic children (OR 0.69, 95% CI 0.50-0.95, p = 0.025). Furthermore, those with greatest NSD (ADI quintile 5) had the largest proportion of unrestrained patients (21%, see Fig. 1).Hispanic children, especially those who require infant or booster seats (8 yr), and children living in areas with greater neighborhood socioeconomic disadvantage demonstrated poorer restraint practices. ADI can successfully identify high-risk groups for targeted injury prevention programs and improved compliance in the most vulnerable neighborhoods.Retrospective Study.

Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for contextual information extraction and decision making. Beyond modeling advances, the enabler for vehicles to become aware of their surroundings is the availability of visual sensory data, which expand the vehicular perception and realizes vehicular contextual awareness in real-world environments. Research directions for scene understanding pursued by related studies include person/vehicle detection and segmentation, their transition analysis, lane change, and turns detection, among many others Unfortunately, these tasks seem insufficient to completely develop fully-autonomous vehicles i.e. achieving level-5 autonomy, travelling just like human-controlled cars. This latter statement is among the conclusions drawn from this review paper: scene understanding for autonomous driving cars using vision sensors still requires significant improvements. With this motivation, this survey defines, analyzes, and reviews the current achievements of the scene understanding research area that mostly rely on computationally complex deep learning models. Furthermore, it covers the generic scene understanding pipeline, investigates the performance reported by the state-of-the-art, informs about the time complexity analysis of avant garde modeling choices, and highlights major triumphs and noted limitations encountered by current research efforts. The survey also includes a comprehensive discussion on the available datasets, and the challenges that, even if lately confronted by researchers, still remain open to date. Finally, our work outlines future research directions to welcome researchers and practitioners to this exciting domain. This work was supported by the European Commission through European Union (EU) and Japan for Artificial Intelligence (AI) under Grant 957339.

Despite the plausibility that diabetes may increase the risk of motor vehicle crashes (MVCs) due to various diabetes related complications and co-morbidity, findings from epidemiological studies on the relationship between diabetes and MVCs remained inclusive mainly due to heterogeneity in the study design and failure to complete consideration of potential confounders. This study re-visited this putative association with an improved study design.This study employed a controlled before-after study design and included 1,264,280 people aged 18-75 years with T2D newly diagnosed from 2009-2014 and an equal number of age-, sex-, and time-matched controls. The rate ratios (RRs) of vehicle type-specific incidence rates of MVCs in the 1 and 2 years before and after diabetes diagnosis (or the matched dates) were compared between the individuals with type 2 diabetes (T2D) and their matched controls.The rate of MVCs increased slightly among people with T2D over 1 and 2 years following diabetes diagnosis, with RRs of 1.04 (95% confidence interval [CI]=1.02-1.07) and 1.11 (95% CI=1.09-1.13), respectively. These RRs were comparable to those obtained for controls (1.06 and 1.12, respectively). By contrast, the RRs of scooter crashes were significantly higher in the T2D group than in the control group during the 1 year (1.28 vs. 1.08, p 0.001) and 2 years (1.32 vs. 1.08, p 0.001) following diabetes diagnosis.T2D diagnosis was associated with a moderate but significant increase in the risk of MVCs among scooter drivers, but not among car drivers.

The naphthol reds are a family of intermediate performance monoazo organic pigments and three of its members, C.I. Pigment Red 148, C.I. Pigment Red 170 (Naphthol Red), and C.I. Pigment Red 188, have been cited as having original automotive paint applications. This study sought to determine which were used in North American vehicle original finishes (1974 to 2019) and how they can be differentiated and identified in situ in paint infrared spectra. Naphthol Red was the only such pigment found and based on a comprehensive survey, absorptions of this pigment were identified in spectra of 12 of the 373 (3%) red or maroon nonmetallic original finishes examined. Identification of Naphthol Red in an unknown finish can thus serve to limit the number of possible source vehicles and spectra of the twelve are presented to facilitate this examination, along with a list of the vehicles that the twelve were used on. For a comparative analysis, identification of this pigment in questioned and known specimens may provide some means of assessing the significance of the finding. Two Inmont red nonmetallic acrylic melamine basecoats, one of which contains Naphthol Red, were found to have quite unusual infrared spectra that are readily distinguished from those of the other 371 finishes examined, and they are discussed. Naphthol Red was also identified in some color-coordinated automotive paint primers and its use appears to be more common in these than in the finish layers.

This study aimed to evaluate the occupational health risks of benzene, toluene, and xylenes (BTX) exposure in the automobile repair industry in Beijing city in China. The concentrations of BTX were monitored at 140 operating positions of 51 randomly selected automobile repair enterprises in 2018. Samples analysis showed that all monitoring concentrations were not higher than the occupational exposure limits. The long-term exposure concentration ranges of benzene, toluene, and xylenes were 0.1 to 0.3, 0.1 to 49.7, and 0.2 to 49.5 mg/m3, respectively. The short-term exposure concentration ranges of benzene, toluene, and xylenes were 0.1 to 0.3, 0.1 to 98.7, and 0.2 to 100.0 mg/m3, respectively. But assessment results revealed unneglectable occupational health risks, especially the combined health risks of BTX exposure. Thereafter, effective control and improvement measures were put forward, including strengthening the management of the production, sale, and use of vehicle paints and coatings; improving ventilation; and implementing hierarchical management measures for occupational health risks.

This article develops a discrete choice model of demand with optimal sequential consumer search. Consumers first choose a product to search; then, once they learn the utility they get from the searched product, they choose whether to buy it or to keep searching. We characterize the search problem as a standard discrete choice problem and propose a parametric search cost distribution that generates closed-form expressions for the probability of purchasing a product. We propose a method to estimate the model that supplements aggregate product data with individual-specific data which allows for the separate identification of search costs and preferences. We estimate the model using data from the automobile industry and find that search costs have non-trivial implications for elasticities and markups. We study the effects of exclusive dealing regulation and find that firms benefit at the expense of consumers, who face higher search costs and higher prices than would be the case if multi-brand dealerships were used.

Although the use of plastic components is increasing in the automotive industry, yet the recovery rates of these materials in end-of-life vehicle (ELV) is lower compared to metals. One of the main problems of ELV plastic waste is poor separation and sorting. Large car plastic parts consist of fibre-reinforced plastics, whereas other components end up in the automotive shredder residue (ASR), featuring a very heterogeneous mix of light materials that contains mostly non-metallic materials such as textiles, plastics, cartridges and wood. Generally, ASR was disposed in landfill or diverted to thermal treatments, such as pyrolysis or gasification, for energy recovery. Currently, the recovery of raw materials from various waste streams plays a key role in new European strategy for plastics in a circular economy. The approach of physical recycling methods described in this mini-review helps to maintain the value of polymer materials in the value chain allowing the reuse in the original or similar application.

While many states have legalized medical cannabis, many unintended consequences remain under-studied. We focus on one potential detriment-the effect of cannabis legalization on automobile safety. We examine this relationship through auto insurance premiums. Employing a modern difference-in-differences framework and zip code-level premium data from 2014 to 2019, we find that premiums declined, on average, by $22 per year following medical cannabis legalization. The effect is more substantial in areas near a dispensary and in areas with a higher prevalence of drunk driving before legalization. We estimate that existing legalization has reduced health expenditures related to auto accidents by almost $820 million per year with the potential for a further $350 million reduction if legalized nationally.

Allowing young drivers to gain experience while being supervised by an experienced driver is a widely used measure to try to reduce crash risk. On 1 January 2017, the Danish licensing system was updated to allow licensing at age 17 with post-license supervised driving until solo driving at age 18.Based on data from the Danish Driving License register and Statistics Denmark, including the entire population, the purpose of this study is to determine if sociodemographic characteristics and a history of violations and crash involvement among youth predict licensing at age 17. A second purpose is to estimate the time period from licensing until the driver turns 18 and to explore changes in license demand in the context of Denmark's updated licensing system.An increasing proportion choose to license at the age of 17, but the proportion below 19 with a driver's license is unchanged. On average, the license is obtained 5.3 months before turning 18. Living in rural areas, with both parents, and in a family with several cars and higher income increases the likelihood of licensing at age 17. Young people with a history of involvement in non-traffic-related accidents or violations are more likely to license at age 17.Lowering the license age to allow supervised driving increases early licensing. The average time period from licensing until the driver turns 18 is less than six months. Sociodemographic characteristics predict early licensing.Minimum requirements for the time period from licensing until the driver turns 18 are needed to support a safety benefit. Follow-up studies mapping supervised driving, crash involvement, and possible changes in crash risk associated with the change in the Danish licensing system are needed to specify the requirements.

Using a new propagation measurement set-up, which produces a high number of data, enabling a proper statistical analysis, and resulting in very concise results, propagation measurements were performed and analized at 16 residential locations in The Netherlands in the frequency range from 1.8 to 28 MHz. In the whole frequency range the propagation loss appear to be higher than according the International Telecommunication Union ground-wave propagation model might be expected. Also typical characteristics of that model are not present, but instead the propagation shows a constant roll-off in dBs per decade, which slope is increasing with frequency. A regression curve could be established, and constants filled in. This statistical information may be used for building an accumulation model to lay a causality between source powers, source densities, and local Man-Made Noise levels.

In this paper, afull-car prototype of the recently proposed mechatronic suspension, Series Active Variable Geometry Suspension (SAVGS), is developed for on-road driving experimental proof of concept, aiming to be adopted by suspension OEMs (original equipment manufacturers) as an alternative solution to fully active suspensions. Particularly, mechanical modifications are performed to both corners of the front double-wishbone suspensionof a production car, with active single-links attached to the upper-ends of the spring-damper units, while both corners of the rear suspension remain inthe original (passive) configurations.The mechanical modifications involve innovatively designed parts to enable the desired suspension performance improvements, while maintaining ride harshness at conventional levels.Areal-time embedded system is further developed to primarily implement:1) power supply, data acquisition and measurementsof the vehicle dynamics related variables, and 2) robust control application for the ride comfort and road holding enhancement, which is based on a derived linearized model of the full-car dynamics and a newly synthesizedH-infinity control scheme. Results obtained from on-road driving experiments are inessential agreement with numerical simulation results also produced. Overall, the full-car prototypeof SAVGS demonstrates promising suspension performance,with anaverage 3 dB attenuation (or equivalently 30% reduction) of the chassis vertical acceleration at aroundthe human-sensitive frequencies (2-5Hz),as compared to the original vehicle with the passive suspension system. More importantly, the prototype also indicatesthe practicality of the solution, as the SAVGS retrofit to a real car is achieved by simple mechanical modifications, compact actuator packaging, smallmass increment(21.5kg increase with respect to the original vehicle), limited power usage (an average value of 134W in DC batteries with a Class D random road) and acceptable economic cost.

OBJECTIVE The Health Promotion Act was revised in 2018 and prohibits smoking inside taxis and buses. However, there is no regulation for smoking in the business vehicles of companies or private cars. This paper examined exposure to secondhand smoke in vehicles with digital dust monitors. MATERIAL AND METHODS A cigarette was smoked inside of a five-seat car, and particulate matter 2.5 (PM2.5) concentrations were measured at front and rear seats. RESULTS The concentration of PM2.5 reached 3,500 μg/m3 with all windows closed and decreased to approximately 3,000 μg/m3 when driver's window and passengers' windows were opened by 10 cm. However, the PM2.5 concentration did not decrease to levels below 1,500 μg/m3 with all windows fully opened. DISCUSSION AND CONCLUSION To prevent exposure to secondhand smoke, smoking should not be allowed inside any vehicle when non-smokers are present.

The demand for improved indoor air quality, especially during the pandemic of Covid-19, has led to renewed interest in antiviral and antibacterial air-conditioning systems. Here, air filters of vehicles made of nonwoven polyester filter media were sonochemically coated with CuO nanoparticles by a roll-to-roll coating method. The product, aimed at providing commuters with high air quality, showed good stability and mechanical properties and potent activity against

Styrene butadiene rubber (SBR), is a synthetic polymer and the most abundantly used in the tire industry, which have good collaborative properties with additives and fillers. In present work, we aim to synthesize SBR composite having the properties of graphene oxide filler and made it to be biodegradable. In composite preparation, we fabricated styrene-butadiene rubber/graphene oxide/lignin composites by adding biodegradable biomolecule of lignin fillers at varying 1-3 wt% quantities amount. Those prepared SBR composites were characterized using advanced analysis techniques, and also their biodegradability was. From microscopy examination results, the morphology of pure SBR composite had been improved after the addition of graphene oxide, while the 1 wt% lignin filled SBR sample revealed well-integrated morphology with crest-and-trough-like feature, showcasing the lignin fibrils could strengthen the molecular interaction between graphene oxide nano sheet and SBR rubber. For 2 wt% lignin filled SBR sample, it exhibited large protuberants due to the aggregation effect of lignin fibrils. However, bulky and bundle structure of protuberant was more significantly formed in 3 wt% lignin filled SBR, as a result of poor interface between lignin and SBR rubber. The porosity had also been improved for 1 wt% lignin filled SBR sample, imparting it with great surface area to act as tire in automobile application. The physico-chemical analysis also detected the trace of graphene oxide and lignin functional groups in the SBR composite. In addition, the thermal analysis revealed those lignin-filled composites had stable heat tolerance behavior, which suitably used in extreme weather condition. Moreover, the 1 wt% lignin filled SBR sample exhibited good characteristics in both mechanical and biodegradable properties. Thus, the composite of 1 wt% lignin filled SBR could be regarded as a promising candidate for green tire application in the future.

From sirens to lane markings, the urban environment is full of sounds that are designed to navigate the attention of the driver towards events that require special care. Microphone-equipped autonomous vehicles can also use these acoustic cues for increasing safety and performance. This article explores auditory perception in the context of autonomous driving and smart vehicles in general, examining the potential of exploiting acoustic cues in driverless vehicle technology. With a journey through the literature, we discuss various applications of auditory perception in driverless vehicles, ranging from the identification and localisation of external acoustic objects to leveraging ego-noise for motion estimation and engine fault detection. In addition to solutions already proposed in the literature, we also point out directions for further investigations, focusing in particular on parallel studies in the areas of acoustics and audio signal processing that demonstrate the potential for improving the performance of driverless cars.

Regenerative braking is one of the most promising and ecologically friendly solutions for improving energy efficiency and vehicle stability in electric and hybrid electric cars. This research describes a data-driven method for detecting and diagnosing issues in hybrid electric vehicle regenerative braking systems. Early fault identification can help enhance system performance and health. This study is centered on the construction of an inference system for fault diagnosis in a generalized fuzzy environment. For such an inference system, finite-state deterministic fully intuitionistic fuzzy automata (FDFIFA) are established. Semigroup of FDFIFA and its algebraic properties including substructures and structure-preserving maps are investigated. The inference system uses FDFIFA semigroups as variables, and FDFIFA semigroup homomorphisms are employed to illustrate the relationship between variables. The newly established model is then applied to diagnose the possible fault and their nature in the regenerative braking systems of hybrid electric vehicles by modeling the performance of superchargers and air coolers. The method may be used to evaluate faults in a wide range of systems, including autos and aerospace systems.

Facing the challenges of organic industrial solid waste (OISW) disposal, co-processing of OISW by power plants has become a developing trend. In order to avoid feeding problems of OISW and enhance the combustion adaptability of the furnace, pyrolysis coupled with incineration technology is proposed as a potential method. Among various OISW, automobile shredder residue (ASR) is regarded as a promising fuel due to its high heating value. In view of engineering application, the researches focused on the products' properties and economic evaluation under a wide range of heating rates which are insufficient. In this study, regarding the rapid pyrolysis by conducting the high-temperature flue gas as heating source in power plants, the pyrolysis behavior of ASR was correspondingly studied under a wide range of heating rates. The formation of volatiles and property's improvement were further investigated for generating high-valued oil. Results showed that the high heating rate is not only beneficial to the homogenization of pyrolytic products but also the aromatization in oil and radical generation in gases. Importantly, it also contributed to the cleavage of the single bond connected to the benzene ring and carbon-oxygen single bond for esters. By conducting the enhanced cracking of volatiles, the wax-like fraction was significantly reduced. In addition, the deoxygenation in oil (oxygen content decreased by 20 wt%) and high heating value of gases (increased by 73%) were improved. Our findings demonstrated the feasibility and economic efficiency for the co-processing of ASR in coal-fired power plants via pyrolysis and thus provide guidance for future commercial application.

Isocyanates are known to induce occupational diseases. The aim of this work was to assess the health effects of exposure to isocyanates and to test the sensitivity of selected parameters for early detection of isocyanate-related allergic diseases.In total, 35 employees from one factory were tested: 26 workers exposed to isocyanates (exposed group) and nine office workers (control group). All subjects filled in a questionnaire regarding possible health problems. Fractional exhaled nitric oxide (FeNO) and spirometry were measured for each subject at the same time during two consecutive working days. A urine sample was taken for a biological exposure test (BET).No significant difference was found between the exposed and control groups for spirometry parameters and FeNO. However, in the exposed group, FeNO was highly elevated (50 ppb) in five subjects (all reporting health problems at the workplace, all with normal spirometry and non-smokers). The BET revealed a significant difference (p0.001) between the exposed and control groups for 4,4´-methylenediphenyl diamine (MDA) in the urine.Our examination showed the usefulness of the BET in monitoring of workplace exposure to isocyanates and the importance of FeNO in monitoring of allergic inflammation of airways in non-smoking employees with normal spirometry.

Wiper motor noise has an important impact on vehicle comfort. Accurate prediction of wiper motor noise can obtain motor NVH performance in motor manufacturing or earlier stage and provide necessary support for NVH performance design of parts and vehicles. However, the prediction accuracy of wiper motor noise by the traditional CAE or testing method is low. Data-driven technology provides a new idea for wiper motor noise prediction with its advantages of high efficiency and high precision. This paper studies the wiper motor noise prediction algorithm based on the motor vibration signal, respectively, using the transmission path analysis theory and the support vector machine theory, and carries on the test verification and comparative analysis of the effect. The results show that the method based on support vector machine is more accurate in the prediction of wiper motor noise and has higher practical engineering value.

This study evaluates consumer preference from the perspective of neuroscience when a choice is made among a number of cars, one of which is an electric car. Consumer neuroscience contributes to a systematic understanding of the underlying information processing and cognitions involved in choosing or preferring a product. This study aims to evaluate whether neural measures, which were implicitly extracted from brain activities, can be reliable or consistent with self-reported measures such as preference or liking. In an EEG-based experiment, the participants viewed images of automobiles and their specifications. Emotional and attentional stimuli and the participants’ responses, in the form of decisions made, were meticulously distinguished and analyzed via signal processing techniques, statistical tests, and brain mapping tools. Long-range temporal correlations (LRTCs) were also calculated to investigate whether the preference of a product could affect the dynamic of neuronal fluctuations. Statistically significant spatiotemporal dynamical differences were then evaluated between those who select an electric car (which seemingly demands specific memory and long-term attention) and participants who choose other cars. The results showed increased PSD and central-parietal and central-frontal coherences at the alpha frequency band for those who selected the electric car. In addition, the findings showed the emergence of LRTCs or the ability of this group to integrate information over extended periods. Furthermore, the result of clustering subjects into two groups, using statistically significant discriminative EEG measures, was associated with the self-report data. The obtained results highlighted the promising role of intrinsically extracted measures on consumers’ buying behavior.

This article describes a study examining fatal road crashes in South Australia (SA) according to the safety model developed by the Swedish Road Administration (STA). The STA model is based on the biomechanical limits that human beings can tolerate and specifies a number of elements that must be present for ���compliance��� with the model: driving at or below the speed limit, driver not intoxicated by alcohol or drugs, vehicle occupants wearing a seatbelt, car with a EuroNCAP rating of 5 stars, car equipped with electronic stability control, and a road with an EuroRAP rating of 4 stars. The study used a sample of 105 fatal crashes in SA in 2010 and 2011 and a comparison sample of 136 serious injury crashes from 2014 to 2017. It was found that there were high levels of noncompliance with all elements of the STA model, with multiple forms of noncompliance in a clear majority of fatal cases. Considerable gains in safety could occur with greater penetration into the SA fleet of 5-star cars fitted with ESC and other vehicle safety technology, especially as the majority of both sets of crashes were of a type involving loss of vehicular control. It is also important to note that risky road user behavior was less common in the serious injury crashes and so a road safety strategy focusing on changing road user behavior will be ineffective for addressing the major factors contributing to non-fatal road trauma.

Assisted and autonomous driving technologies may be a new paradigm shift for the driving rehabilitation field to enable less restricted driving, increase driving confidence, and maintain driving safety for drivers with vision impairment.This study aimed to document how a driver with vision impairment uses assistance and automation systems in a Tesla car based on real-world experiences of using these technologies.A 53-year-old man with Stargardt disease and 20/182 visual acuity self-explored the use of driver assistance technologies, which resulted in purchasing a Tesla Model Y with the full self-driving package in 2020. Two semistructured interviews were administered to quantify the driver's driving habits, adaptive strategies, use of the assisted and semiautonomous driving features in the Tesla car, and use of his bioptic telescope.When driving a Tesla car, the patient developed new driving strategies by codriving with different assisted and semiautonomous functions (e.g., Traffic-Aware Cruise Control, Traffic Light and Stop Sign Control, Autopilot) in different road environments. He shifted his main task from active driving to supervising the car automation systems in most driving situations. He also integrated a new use of his bioptic telescope to support him with monitoring the road environment before granting permission to the automated systems for car maneuver changes. The patient reported that driving confidence greatly increased and that he is able to drive more often and in situations that he would otherwise avoid because of difficulties related to his vision.This clinical report demonstrates how assisted and semiautonomous driving systems in a Tesla car were used to support daily driving by a driver with vision impairment. Codriving with these systems allows him to confidently drive more often and to avoid less situations than he used to.

This paper studies and compares the gap selection process of multiple vehicle classes (passenger cars, delivery vans, and trucks) within their discretionary lane changing activities. Given a trajectory or a sequence of gap selection decisions, we aim to predict whether a vehicle will change or keep a lane. For this purpose, we use a large trajectory dataset, collected for the Netherlands, consisting of 3,647 trajectories of passenger car drivers, 1,080 trajectories of delivery van drivers, and 2,226 trajectories of truck drivers. We apply gated recurrent unit neural networks to separately model their gap selection processes. These three models can not only handle class imbalance but also capture long-term interdependencies. The models can predict gap selection of three vehicle classes with geometric mean accuracies of 84% or higher. To obtain insights into their gap selection processes, we apply a gradient-based technique to analyze what neural networks have learned. Our results suggest that there exist significant differences between vehicle classes in terms of the importance of historical information and features. Trucks seem to value a relatively long period, recent 6 seconds, of driving experience to select gaps compared to passenger cars and delivery vans. In addition, the perception of road topology seems to be a significant factor for delivery vans and trucks, contrary to passenger cars which highly value their kinematic features and interactions with surrounding vehicles, to select gaps. These insights offer a novel contribution towards better understanding and modeling of the driving behavior of multiple vehicle classes.

A surface plasmon resonance (SPR) chemical sensor with gold as the sensitive material has been designed to detect the adulteration of petrol by kerosene. Samples of petrol adulterated with kerosene were prepared in different ratios by volume (v/v). Kerosene concentrations ranging from 0% to 80% can be detected by monitoring the optical spectra, and the properties of the sensor were analyzed using the COMSOL Multiphysics software. The sensor shows a high spectral sensitivity of 7117 nm per RIU and a sensing resolution of 1.4 × 10

In-car devices are growing both in complexity and capacity, integrating functionalities that used to be divided among other controls in the vehicles. These systems appear increasingly in the form of touchscreens as a cost-saving measure. Screens lack the physicality of traditional buttons or switches, requiring drivers to look away from the road to operate them. This paper presents the design, implementation, and two studies that evaluated HapWheel, a system that provides the driver with haptic feedback in the steering wheel while interacting with an Infotainment System. Results show that the proposed system reduced both the duration of and the number of times a driver looked away from the road. HapWheel was also successful at reducing the number of mistakes during the interaction.

Automobiles should be as quiet as possible, so noise emissions need to be minimized and controlled. Polyolefin foams are ideal for efficient noise absorption and sound deadening systems in vehicles and play an important role to reduce the overall weight of cars. The paper describes acoustic noise control concepts and exemplifies how polyolefin foam solutions can address vehicle noise challenges., Autos sollen heutzutage möglichst lautlos sein. Damit dies gelingt, müssen Lärmemissionen minimiert und kontrolliert werden. Mit Polyolefin-Schaumstoffen lässt sich eine effiziente Geräuschabsorption und -dämmung in Fahrzeugen perfekt umsetzen und sie spielen gleichzeitig eine wichtige Rolle das Gesamtgewicht des Fahrzeugs zu reduzieren. In diesem Artikel werden Konzepte vorgestellt, wie Geräusche vermindert werden können und es wird an Beispielen veranschaulicht, wie Polyolefin-Schaumstoffe dazu beitragen können, die akustischen Herausforderungen in Automobilen zu meistern.

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies.

Much has been documented that the experience of a bombing is associated with posttraumatic stress disorder and psychiatric co-morbidity. Whether the co-existing relationship between death anxiety, meaning in life and coping styles would influence the aforementioned association is unknown. The present study aimed to identify latent classes of victims with different levels of death anxiety, meaning in life and coping styles, and to examine whether the severity of PTSD and co-morbid psychiatric symptoms differed between classes. One hundred and eighty-five victims who had experienced the first car bombing completed a demographic page, the Posttraumatic Stress Diagnosis Scale, General Health Questionnaire-28, Multidimensional Fear of Death Scale, Meaning in Life Questionnaire and Coping Responses Inventory. The results showed that 82% and 18% of the victims met the criteria for PTSD and no-PTSD, respectively. Four classes of victims were identified: Class 1 victims were approach copers with low levels of death anxiety and meaning. Class 2 victims were minimal copers with high levels of death anxiety and meaning. Class 3 victims were approach copers with a high level of death anxiety and meaning. Class 4 victims were avoidance copers with high levels of death anxiety. Individuals in Class 1 reported significantly lower levels of PTSD and psychiatric co-morbidity than the other three classes. Class 3 victims also reported significantly lower levels of psychiatric co-morbidity than Class 2 victims. To conclude, victims exposed to a car bombing were likely to exhibit posttraumatic stress symptoms in addition to other psychological symptoms. The severity of these symptoms tended to be lower among those who had little fear of death, did not search for meaning in life and approached their distress proactively.

International audience; In this article, we assess the string stability of seven 2018 model year adaptive cruise control (ACC) equipped vehicles that are widely available in the US market. Seven distinct vehicle models from two different vehicle makes are analyzed using data collected from more than 1,200 miles of driving in car-following experiments with ACC engaged by the follower vehicle. The resulting dataset is used to identify the parameters of a linear second order delay differential equation model that approximates the behavior of the black box ACC systems. The string stability of the data-fitted model associated with each vehicle is assessed, and the main finding is that all seven vehicle models have string unstable ACC systems. For one commonly available vehicle model that offers ACC as a standard feature on all trim levels, we validate the string stability finding with a multi-vehicle platoon experiment in which all vehicles are the same year, make, and model. In this test, an initial disturbance of 6 mph is amplified to a 25 mph disturbance, at which point the last vehicle in the platoon is observed to disengage the ACC. The data collected in the driving experiments is made available, representing the largest publicly available comparative driving dataset on ACC equipped vehicles.

The American Academy of Pediatrics recommends pre-discharge Car Seat Tolerance Screening (CSTS) for all neonates born37 weeks estimated gestational age (EGA), or otherwise at risk for cardiorespiratory compromise. Screening is burdensome and there remains tremendous variation in testing criteria and methodology.We conducted a retrospective chart review of 1,072 infants who underwent CSTS between 11/2013 and 7/2016 at a single academic health center. CSTS outcomes (failure and, separately, significant cardiorespiratory instability (CRI)), including those not meeting failure thresholds) were analyzed for all infants screened, and for preterm infants by screening location (Neonatal Intensive Care Unit (NICU) and Mother/Baby Unit (MBU)). Logistic regression was used to estimate associations between infant characteristics and CSTS outcomes.Overall incidence of CSTS failure was 9.2%. Among all infants, hemodynamically significant congenital heart disease, apnea, chronic lung disease, and being small for EGA were associated with failure. Additionally, those born ≤28 weeks EGA had 2.4 times greater likelihood of failure than those 34-36 weeks EGA. Among preterm infants in the NICU and MBU, those of earlier EGA were also more likely to fail. Almost half (47.5%) of all preterm infants demonstrated CRI during CSTS.We found high CSTS failure rates, and identified key infant characteristics that were associated with increased likelihood of failure. Significant CRI events were remarkably common. Larger, prospective studies are needed to elucidate risk factors for instability and failure and define practical criteria for CSTS recommendations.

Background:Automobile car repair requires intensive activities. Several studies have described different work characteristics of automobile artisans’ work. However, the effects of physical work conditions (PWC) on worker health outcomes are largely unknown.Objective:This study aimed to explore which of the PWC have high negative impact on worker’s health outcomes, and whether the same conditions affected both illnesses and injuries.Methods:A cross-sectional design and a multistage method were used to randomly select 632 workers. A structured self-reported questionnaire was used to obtain information on dependent variables (illness/injuries) and independent variables (PWC). The results were analysed using the chi-square test and logistic regression analysis, while controlling for occupation.Results:Workers who manually lifted heavy items or orally sucked petrol regularly reported illnesses and injuries. Long work experience and long working hours were significantly associated with illness, whereas prolonged standing was significantly related to injuries. Contrary to our initial expectation, workers who regularly worked at 2 m or higher above the ground level tended to report less illness and injury.Conclusions:PWCs were more significantly related to work-related illnesses than injuries. Therefore, interventional programs for automobile artisans should focus on the PWC that increase worker vulnerability to work-related illnesses.

Lead is an occupational toxicant and a recognised health threat particularly in developing countries. Hence, this study explored the interaction of blood lead level (BLL), a conventional marker of lead exposure, with indices of calcium metabolism and biomarkers of bone-turnover in 120 adult male automobile technicians (AT) with ≥ 1 year duration in professional practice. The AT as well as the control group, which comprised 120 age, body-size and socio-economically matched male administrative workers, were recruited from Sagamu, South West Nigeria. Levels of blood lead, serum indices of calcium metabolism [total calcium (tCa), ionised calcium (iCa), phosphate, albumin, magnesium (Mg) and 25-Hydroxycholecalceferol (25-OHCC)], biomarkers of bone formation [bone alkaline phosphatase (BALP) and osteocalcin (OC)] and biomarkers of bone resorption [tartarate-resistant acid phosphatase-5b (TACRP-5b) and urinary hydroxyproline (UHYP)] were determined in all participants. The BLL, 25-OHCC, TRACP-5b and UHYP significantly increased while tCa and iCa significantly reduced in AT compared to control. However, no significant difference was observed in phosphate, albumin, Mg, BALP and OC in AT compared to control. Interestingly, BLL demonstrated a significant negative association with tCa and iCa but a significant positive association with 25-OHCC, TRACP-5b and UHYP. However, BLL did not show significant association with phosphate, albumin, Mg, BALP and OC. Increased lead exposure as well as altered calcium metabolism and bone-turnover demonstrated by the automobile technicians may be suggestive of lead-induced accelerated bone demineralisation. These workers may be predisposed to high risk of increased susceptibility to bone diseases if this sub-clinical picture is sustained.

This article concerns the study of mixed Pareto-lexicographic multiobjective optimization problems where the objectives must be partitioned in multiple priority levels (PLs). A PL is a group of objectives having the same importance in terms of optimization and subsequent decision making, while between PLs a lexicographic ordering exists. A naive approach would be to define a multilevel dominance relationship and apply a standard EMO/EMaO algorithm, but the concept does not conform to a stable optimization process as the resulting dominance relationship violates the transitive property needed to achieve consistent comparisons. To overcome this, we present a novel approach that merges a custom nondominance relation with the Grossone methodology, a mathematical framework to handle infinite and infinitesimal quantities. The proposed method is implemented on a popular multiobjective optimization algorithm (NSGA-II), deriving a generalization of it called by us PL-NSGA-II. We also demonstrate the usability of our strategy by quantitatively comparing the results obtained by PL-NSGA-II against other priority and nonpriority-based approaches. Among the test cases, we include two real-world applications: one 10-objective aircraft design problem and one 3-objective crash safety vehicle design task. The obtained results show that PL-NSGA-II is more suited to solve lexicographical many-objective problems than the general purpose EMaO algorithms.

Peer reviewed: True, Funder: DAAD-University of Cambridge Research Hub, It is the aim of this article to put questions of maintenance and repair in the history of science and technology under scrutiny, with a special focus on technologies and methods of transportation. The history of transportation is a history of trying to avoid shipwrecks and plane crashes. It is also a history of broken masts, worm-eaten hulls, the flat tires of cars, and endless delays at airports. This introductory article assesses the technological, scientific, and cultural implications of repairing and maintaining transportation networks. We argue that infrastructures for maintenance and repair played just as important a role in the history of transportation as the wharves and factories where ships, cars, trains, and airplanes were originally built. We also suggest that maintenance and repair are important sites of knowledge production, and a historical account of these practices provides a new, decentered narrative for the development of modern science and technology.

Alcohol and drugs misuse represents an important social problem. There is no agreement about influence of ethanol and drugs on trauma severity and clinical course. The aim of this study was to investigate the impact of alcohol and drugs abuse on road related trauma managed to our Level I Trauma Center. Data of 1067 car or motorcycle drivers consecutively admitted in a 5 years period were retrospectively analyzed. The sample was divided into two groups: patients with alcohol and/or drugs misuse and patients without detectable plasmatic levels or not screened because no clinical suspicion of these substance. Demographic data, mechanism of trauma, severity of injury, daily and season time of trauma distribution, alcohol and drugs levels and outcomes were retrieved. Alcohol or drugs misuse were detected in 242 patients. Heavy alcohols levels were the 62.3%. Among drugs cannabis was the most detected substance. These patients were significantly younger than the overall study population (p = 0.011), with a higher ISS (p = 0.012) a lower RTS (p = 0.047), a lower GCS (p = 0.005) and an higher head injuries severity (p = 0.030). Regarding time distribution, Saturday was the day with the highest percentage of trauma associated with substance misuse (21%). Alcohol/drugs misuse plays a very important role in the epidemiology of road related trauma. Despite the higher severity of trauma scores and the higher incidence of severe head injuries in patients with alcohol or drugs consumption, there were no effects of this substances on mortality of injured patients involved in road crashes.

Introduction: Driver’s evasive action is closely associated with collision risk in a critical traffic event. To quantify collision risk, surrogate safety measures (SSMs) have been estimated using vehicle trajectories. However, vehicle trajectories cannot clearly capture presence and time of driver’s evasive action. Thus, this study determines the driver’s evasive action based on his/her use of accelerator and brake pedals, and analyzes the effects of the driver’s evasive action time (i.e., duration of evasive action) on rear-end collision risk. Method: Fifty drivers’ car-following behavior on a freeway was observed using a driving simulator. An SSM called “Deceleration Rate to Avoid Crash (DRAC)” and the evasive action time were determined for each driver using the data from the driving simulator. Each driver tested two traffic scenarios – Cars and Trucks scenarios where conflicting vehicles were cars and trucks, respectively. The factors related to DRAC were identified and their effects on DRAC were analyzed using the Generalized Linear Models and random effects models. Results: DRAC decreased with the evasive action time and DRAC was closely related to drivers’ gender and driving experience at the road sections where evasive action to avoid collision was required. DRAC was also significantly different between Cars and Trucks scenarios. The effect of the evasive action time on DRAC varied among different drivers, particularly in the Trucks scenario. Conclusions: Longer evasive action time can significantly reduce crash risk. Driver characteristics are more closely related to effective evasive action in complex driving conditions. Practical Applications: Based on the findings of this study, driver warning information can be developed to alert drivers to take specific evasive action that reduces collision risk in a critical traffic event. The information is likely to reduce the variability of the driver’s evasive action and the speed variations among different drivers.

IntroductionThere is widespread use of all-terrain vehicles (ATVs) in the USA for both work-related and recreational activities. In this study, we aimed to determine the difference in injury severity, Glasgow Coma scales and length of stay between ATV-related injuries and injuries sustained from motorcycles (MOTOs) and automobiles (AUTOs).MethodsWe retrospectively analysed ATV, MOTO and AUTO injuries from a Level 2 Trauma Center between 01 January 2015 and 31 August 2020. Proportional odds regression analyses, as well as multivariable regression models, were used to analyse the data.ResultsThere were significantly more male and paediatric patients that suffered ATV-related injuries compared with MOTO or AUTO injuries. Victims of ATV-related injuries were also more likely to have open fractures. Paediatric patients were less likely to sustain an injury from either AUTO or MOTO accidents compared with ATV accidents. Patients with no drug use during injury and those who used protective equipment such as seat belts and child seats were significantly associated with lower Injury Severity Scores and higher Glasgow Coma Scale scores, indicating less severe injuries.DiscussionPaediatric patients are very likely to suffer sequela and long-term disability due to the severity of ATV-related injuries. Public awareness campaigns to educate our population, especially our youth, about the danger of ATV use are highly needed.

Public transportation (PT) is important in urban areas for the movement of people and helps create a sustainable transport system in most cities. In 2008, the Lagos State Government, in collaboration with the World Bank, established a bus rapid transit (BRT) system of PT to address the lingering problem of chaotic, uncoordinated, and unreliable public transportation in the Lagos metropolis. The BRT system seems to offer higher service quality than the traditional buses in the metropolis. It attracts a mammoth crowd of commuters, including car owners, along its corridors. However, there are concerns by commuters over the deterioration in the service quality of the buses. It is on this note that this paper attempts to examine the transport system using the Ikorodu-CMS corridor as a case study using the SERVQUALmodel to evaluate the service quality of the BRT services along the five dimensions of the model, namely, tangibles, reliability, responsiveness, assurance, and empathy. Data was collected from a valid sample of 545 respondents from both Ikorodu and Agric BRT Bus terminals. The analysis of data showed that Lagos-BRT service quality is below the expectations of several commuters. The results indicated that the service quality of the buses along the four of the five dimensions fell below the expectations of commuters, making them perceive the quality as significantly low. The buses' unreliability contributed immensely to the perception of the buses' low service quality. Understanding commuters' perception of the service quality of Lagos BRT will enable both the bus operator, Primerio Bus Services, and the regulator, LAMATA, to monitor, review and improve the service quality of the buses and make the buses attractive to all categories of commuters in the state.

Thanks to their strong maneuverability and high load capacity, car-like robots with non-holonomic constraints are often used in logistics to improve efficiency. However, it is difficult to plan a safe and smooth optimal path in real time on the restricted narrow roads of the logistics park. To solve this problem, an optimization-based motion planning method inspired by the Timed-Elastic-Band algorithm is proposed, called Narrow-Roads-Timed-Elastic-Band (NRTEB). Three optimization modules are added to the inner and outer workflow of the Timed-Elastic-Band framework. The simulation results show that the proposed method achieves safe reversing planning on narrow roads while the jerk of the trajectory is reduced by 72.11% compared to the original method. Real-world experiments reveal that the proposed method safely and smoothly avoids dynamic obstacles in real time when navigating forward and backward. The motion planner provides a safer and smoother trajectory for car-like robots on narrow roads in real time, which greatly enhances the safety, robustness and reliability of the Timed-Elastic-Band planner in logistics parks.

The supply of fresh air for underground rail transit systems is not as simple as opening windows, which is a conventional ventilation (CV) measure adopted in aboveground vehicles. This study aims to improve contaminant dilution and air purification in subway car ventilation systems and the safety of rail transit post-coronavirus disease pandemic era. We designed an air conditioning (AC) terminal system combined with stratum ventilation (SV) to enable energy consumption reduction for subway cars. We experimentally tested the effectiveness of a turbulence model to investigate ventilation in subway cars. Further, we compared the velocity fields of CV and SV in subway cars to understand the differences in their airflow organizations and contaminant removal efficiencies, along with the energy savings of four ventilation scenarios, based on the calculations carried out using computational fluid dynamics. At a ventilation flow rate of 7200 m3/h, the CO2 concentration and temperature in the breathing areas of seated passengers were better in the SV than in the CV at a rate of 8500 m3/h. Additionally, the energy-saving rate of SV with AC cooling was 14.05%. The study provides new ideas for reducing the energy consumption of rail transit and broadens indoor application scenarios of SV technology.

Aim An increasing number of older adults in Japan are at an increased risk of road traffic crashes. This study aimed to investigate the prevalence of potential underlying medical factors that increase the risk of road traffic crashes among older people. Methods This cross-sectional observational study was conducted in 11 medical institutions in Japan using self-administered questionnaires and physical examination from January to May 2021. The background and social data, data on the use of nursing care insurance, and clinical data suggestive of polypharmacy, sarcopenia, cognitive impairment, and frailty/oral frailty were obtained. The prevalence of these factors was compared between everyday and occasional drivers. Results Data of 127 patients were collected; their median (interquartile range) age was 73 (70–78) years. Of the total participants, 82 were men (64.6%) and 45 were women (35.4%). There were 77 everyday drivers and 50 occasional drivers. Of these, 121 (95.3%) had not applied for nursing care insurance, but the numbers of those who required help 1 and 2 were 1 (0.8%) and 3 (2.4%), respectively. Prevalence of medical factors was as follows: polypharmacy, 27.6%; sarcopenia, 8.7%; dementia, 16.4%; frailty, 15.0%; and oral frailty, 54.3%; it was not significantly different between every day and occasional drivers. Intention to return the car license was significantly higher among the occasional drivers (2.6% vs. 14.0%; odds ratio: 6.7, 95% confidence interval: 1.2–70.6, p = 0.024). Conclusion We uncovered the prevalence of medical factors that can be associated with road traffic crashes among Japanese older people aged ≥ 65 years in our community.

ObjectiveThe objectives of this study were to assess the prevalence of self-reported secondhand smoke exposure in cars among adults in Poland and to characterise public attitudes towards the implementation of the ban on smoking in cars with children.DesignCross-sectional survey was carried out between 4 March 2022 and 7 March 2022 on a national sample of 1090 adult Polish residents. The questionnaire included 12 closed questions on smoking behaviours, secondhand smoke exposure as well as attitudes towards different smoke-free laws.ParticipantsData were obtained from 1090 individuals, aged 18–84 years, 52.6% were females.ResultsAlmost every fifth respondent (17.7%) declared secondhand smoke exposure in cars in the past 30 days (31.8% of smokers and 12.0% of non-smokers; pConclusionsThis study showed high public support for the implementation of the ban on smoking in cars with children. Social support for smoke-free environments in Poland should be used by public health specialists and policy-makers to strengthen the national tobacco control act.

Understanding human mobility is of great significance for sustainable transportation planning. Long-term travel delay change is a key metric to measure human mobility evolution in cities. However, it is challenging to quantify the long-term travel delay because it happens in different modalities, e.g., subway, taxi, bus, and personal cars, with implicated coupling. More importantly, the data for long-term multi-modal delay modeling is challenging to obtain in practice. As a result, the existing travel delay measurements mainly focus on either single-modal system or short-term mobility patterns, which cannot reveal the long-term travel dynamics and the impact among multi-modal systems. In this paper, we perform a travel delay measurement study to quantify and understand long-term multi-modal travel delay. Our measurement study utilizes a 5-year dataset of 8 million residents from 2013 to 2017 including a subway system with 3 million daily passengers, a 15 thousand taxi system, a 10 thousand personal car system, and a 13 thousand bus system in the Chinese city Shenzhen. We share new observations as follows: (1) the aboveground system has a higher delay increase overall than that of the underground system but the increase of it is slow down; (2) the underground system infrastructure upgrades decreases the aboveground system travel delay increase in contrast to the increase the underground system travel delay caused by the aboveground system infrastructure upgrades; (3) the travel delays of the underground system decreases in the higher population region and during the peak hours.

Background: Based on data regarding the prevalence of Parkinson’s disease (PD), the prevalence of impulsive control disorders (ICD) in PD, and the percentage of PD patients driving a car, it has to be assumed that at least 50,000 PD patients with ICD in Germany actively drive a car. However, these patients might be at risk for unsafe driving due to ICD-related dysfunctions such as failure to resist an impulse or temptation, to control an act or other altered neurobehavioral processes. Objective: This study determines the influence of ICD on driving ability in PD. Methods: We prospectively compared driving simulator performance of 23 PD patients with and 23 matched patients without ICD. ICD had to be socially compensated and presence was defined clinically for primary and questionnaire-based (QUIP-RS) for post-hoc analyses. Furthermore, between-group comparisons of driving-relevant neuropsychological tests were executed. Results: Except from a lower blinking frequency when changing lanes, overall driving safety of patients with ICD did not differ significantly from those without—regardless of the clinical or QUIP-RS-based ICD definition. ICD severity did not correlate with driving performance, but the latter correlated significantly with mean reaction times and certain neuropsychiatric tests (MoCA, TMT-A, TAP-M “flexibility” and DBQ “error”). Conclusion: Clinically compensated ICD does not seem to impair driving safety in PD patients. Rather, cognitive and attentional deficits appear to be clinical markers for driving uncertainty.