Lead Car Research Articles

Effect of additional tasks on the reaction time of braking responses in simulated car driving: beyond the PRP effect.

The presentation of one task increases the reaction time on a subsequent task, if stimulus onset asynchrony (SOA) between tasks is short. This psychological refractory period (PRP) effect is typically leveling off as SOA approaches 1 s, which has been documented both in classical laboratory paradigms and in simulated car driving. Here we report a more persistent effect on the subsequent task that goes well beyond the typical duration of the PRP effect. In a driving simulator, 120 healthy older participants followed a lead car that mostly drove at a constant speed. They had to maintain a regular distance from the lead car and had to brake when the lead car braked. Participants also engaged in several additional tasks during driving (two types of tasks: typing three-digit numbers, stating arguments on public issues). SOA between the braking task and the last preceding additional task was 11.49 s ± 1.99 (mean and standard deviation). In a control condition, the braking task was administered without additional tasks. Main performance outcome was Braking Reaction Time (RT, in s), as the interval between onset of brake lights of the lead car and the moment participants released the gas pedal. Additionally, foot movement time (MT, in s), i.e., the difference between gas pedal release and brake pedal onset, was considered for possible compensation behavior. Inter-vehicle distance to the lead car (in m) was taken into account as a moderator. We found that RT averaged 0.77 s without additional tasks, but averaged 1.45 s with additional tasks. This RT difference was less pronounced at smaller inter-vehicle distances, and was not compensated for by faster MT from the gas pedal to the brake pedal. We conclude that detrimental effects of additional tasks on subsequent braking responses can be more persistent than suggested by the PRP effect, possibly because of maintaining multiple task sets, requiring increased executive control. We further conclude that potential detrimental effects can be ameliorated at small inter-vehicle distances by mobilizing extra cognitive resources when response urgency is higher. As a practical implication of our study, distracting stimuli can have persisting detrimental effects on traffic safety.

Abstract C117: Preclinical characterization of allogeneic CAR γδ T Cell therapy for prostate cancer targeting a novel dimeric epitope on PSMA

Abstract Introduction: PSMA is a transmembrane glycosylated homodimer overexpressed in >80% of prostate cancers, with increased expression in advanced stages of the disease. Formation of homodimeric PSMA is necessary for enzymatic function and displays epitopes that are potentially more distinct from alternative PSMA-like proteins. Clinically, autologous anti-PSMA αβ CAR T cells have shown initial efficacy with limited therapeutic index. Compared to αβ T cells and other innate cells, γδ T cells are capable of multifunctional innate and adaptive targeting and infiltrate into tumor-associated tissues, including associated tropism for prostate tumor tissues. Additionally, γδ CAR T cells have demonstrated enhanced tumoricidal activity and activation-induced cytokine profiles that may decrease CRS-associated toxicities. We characterized γδ T cells modified from a set of novel scFv-based CARs targeting PSMA for prostate cancer and mapped unique epitopes for binders associated with the most potent CARs. Methods: Phage panning was used to identify anti-PSMA scFv sequences, which were reformatted into IgGs and characterized for binding to both cells expressing endogenous PSMA and recombinant PSMA. Binders with favorable profiles were reformatted into CARs in VH-VL and VL-VH orientations and transduced into Vδ1 T cells, a primarily tissue-resident subset, activated from healthy donor PBMCs. We identified lead CARs based on anti-tumor efficacy both in vitro in coculture assays and in vivo in tumor xenograft models and compared their activity to Vδ1 CAR T cells transduced with a clinically validated benchmark, J591. Epitope mapping of binders in the lead CARs was performed using a funnel of molecular assays including dot blots, competition assays, ELISAs on recombinant PSMA from different species and cross-linking mass spectrometry (XL-MS). Results: High-affinity PSMA binders yielded potent CARs. Lead PSMA CARs demonstrated robust in vitro cytotoxicity and antigen-specific binding to PSMA-expressing cell lines in a manner comparable to, or greater than the J591-based CAR T cells. Additionally, lead PSMA CARs showed anti-tumor control in 22Rv1 human prostate cancer xenografts, a highly resistant model with heterogenous PSMA expression. Epitope mapping studies on binders in lead PSMA CARs identified conformational, membrane-distal epitopes that are distinct from the predicted linear epitope of J591 and relevant comparators. Conclusion: The epitope for a lead PSMA antibody includes residues in a helix involved in PSMA dimer formation. The γδ CAR T construct derived from this binder demonstrates enhanced preclinical performance when compared to the J591 reference CAR T. Combining the features of this novel target and the potential of the γδ-based CAR T approach, the lead PSMA γδ CAR T cells described here are candidates for further clinical development in the context of additional armoring technologies and CAR architecture modifications designed to complement therapeutic potential. Citation Format: Nitya S. Ramadoss, Elizabeth Speltz, Tonya Capillo, Erika Meaddough, Katherine Wang, Natalia Friedland, Jonathan Wong, Alexander G Teague, Aruna Azameera, Smitha Rao Yelaguli Gundurao, Ramandeep Kaur, Morgan Smith-Boeck, Michael Salum, Yvan Chanthery, Shon Green, Marissa Herrman, Kevin P Nishimoto, Blake T Aftab, Arun Bhat. Preclinical characterization of allogeneic CAR γδ T Cell therapy for prostate cancer targeting a novel dimeric epitope on PSMA [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C117.

Development of a Novel, Allogeneic GPRC5D-Directed CAR for Treatment of Multiple Myeloma Patients

Despite the success of BCMA-targeted therapy in advanced multiple myeloma, the disease is still considered incurable. Relapse following BCMA-directed cellular and antibody-based therapies is commonly associated with decreased surface expression of BCMA on malignant plasma cells. The G protein-coupled receptor, class C group 5 member D (GPRC5D) represents an additional target whose expression is limited to bone marrow and hair follicles, with selectively increased expression on malignant plasma cells. Thus far, the use of GPRC5D-targeted CAR T cells has provided a strong clinical benefit in multiple myeloma with limited on-target, off-tumor effects. To this end, we have validated novel, fully human GPRC5D-specific CARs for use with our hypoimmune (HIP), allogeneic CAR T cell platform. This will allow rapid delivery of allogeneic GPRC5D CAR T cells from healthy donors that simultaneously circumvent “non-self” recognition through TCR, B2M and CIITA gene disruption and promote persistence through innate immune evasion by leveraging CD47 overexpression. For early selection of candidate GPRC5D binders, T cells from healthy donors were transduced with VSV-G pseudotyped lentivirus containing second-generation, fully-human GPRC5D CARs. A clinically validated GPRC5D CAR was produced in similar fashion and used as benchmark control for initial characterization experiments. Transduction efficiency of GPRC5D CARs was analyzed via flow cytometry. GPRC5D CAR efficacy was analyzed in vitro via 24-hour luciferase or long-term Incucyte cytotoxicity assays against RPMI-8226 and MM.1S multiple myeloma target cells. Systemic MM.1S in vivo tumor models were performed in NSG mice to further assess efficacy of lead CAR candidates. Here we show our candidate GPRC5D CARs demonstrate in vitro cytotoxicity and effector cytokine production that is comparable to clinically validated benchmark controls. In 5-day Incucyte cytotoxicity assays, GPRC5D CAR T cells expand up to 10-fold and reduce tumor cell counts at starting E:T ratios of 1:8. Furthermore, in MM.1S in vivo tumor challenge models, these GPRC5D CARs significantly reduce flux and prolonged survival relative to tumor only controls with tumor clearance that was in line with clinical benchmark controls. Using ex vivo VSV-G production, our GPRC5D CAR T cells control multiple myeloma tumor cells both in vitro and in vivo, demonstrating efficacy that is on par with GPRC5D clinical benchmark CAR T cells. Studies to further define the efficacy of HIP-modified GPRC5D CAR T cells are ongoing. Moving forward, further interrogating GPRC5D CAR activity against multiple myeloma tumor cells with varying levels of target antigen expression will be critical to understanding the benefit of deploying GPRC5D CAR T cells within the multiple myeloma clinical landscape.

Promotion of driver compliance with V2V information in car-following tasks via multimodal display

The success of vehicle-to-vehicle (V2V) communication in improving the driving safety and efficiency primarily depends on driver compliance with the transmitted information. In this study, driver compliance with V2V information in simulated car-following tasks was measured and analyzed under different information display settings, such as baseline without information, visual information only, and multimodal information. Car-following data were collected from 30 participants in a driving simulation environment. The results revealed that V2V information could significantly reduce the driver's response time to the lead car’s speed change, resulting in an increase in the minimum time-to-collision when the lead car slowed down. Driver compliance was significantly higher under multimodal information settings than when using visual information alone. Moreover, driver compliance was higher when facing a decelerating lead car than when facing an accelerating lead car. No significant differences in driver compliance between the deceleration levels was observed; however, differences existed among different car-following preference groups. The findings of this study can be applied to V2V car-following models to improve the simulation accuracy for connected-vehicle traffic. Additionally, multimodal information presentation can provide a reference for V2V communication design.

Driver Vigilance State Estimation Based on Multisource Data

Accurate estimation of driver vigilance state is important for improving driving safety and preventing accidents. Previous studies have extensively investigated the potential of driving performance measures (e.g., lane position, steering wheel angle, and lateral acceleration) and eye movement measures (e.g., glance frequency and duration) on the driver’s vigilance state estimation. However, the change in these measures may be caused by various factors. Therefore, comprehensively involving more direct measures (e.g., drivers’ electroencephalogram (EEG) response) is expected to increase the vigilance estimation performance. This study comprehensively uses measures across different functional domains (i.e., driving performance, eye movement, and EEG) to establish an estimation model of the driver’s vigilance state. Twenty participants were assigned a 2-h sustained-attention driving task in a simulator, in which they followed a lead car closely. According to their brake reaction times (RTs) to the brake signal of the lead vehicle, their vigilance states were divided into three levels (i.e., low, medium, and high). A logistic regression model that estimates drivers’ vigilance state level based on multisource data was established. This model is a promising approach to driver states detection and reveals the factors that should be considered in subsequent model development processes. It can be combined with driver vigilance arousal methods to improve driving safety.

Peripheral target detection can be modulated by target distance but not attended distance in 3D space simulated by monocular depth cues

Most studies of visuo-spatial attention present stimuli on a 2D plane, and less is known about how attention varies in 3D space. Previous studies found better peripheral detection performance for targets at a near compared to a far depth, simulated by pictorial cues and optical flow. The current study examined whether target detectability is monotonically related to distance along the depth axis, and whether the attended distance modulates the effect of target distance. We investigated these questions in two experiments that measured how apparent distance and target eccentricity affects peripheral target detection when performed alone during passive simulated self-motion, or during a simultaneous, active central car-following task. Experiment 1 found that targets at an apparent distance of 18.5 virtual meters were detected faster and more accurately than targets at 9.25 and 37 virtual meters, and detectability declined with eccentricity. Experiment 2 examined the effect of the attended location by varying the distance between the viewer and the lead car on which participants were instructed to fixate (i.e. the headway) while equating target distances across headway conditions. Experiment 2 replicated the effects found in Experiment 1, and headway did not modulate the effect of target distance. These results are consistent with the hypothesis that target detection depends non-monotonically on the distance between the viewer and the target, and is not affected by the distance between the target and attended location. However, target detection may also have been affected by stimulus characteristics that co-varied with apparent depth, rather than depth per se.

Enhanced Cognitive Training in a Driving Simulator Improves Cognition in Older Adults

<h3>Research Objectives</h3> A few cognitive training studies have purported that maximal gains are achieved with intense, challenging, and multitask training. Yet, proof-of-concept is currently lacking. Our aim was to evaluate the effects of an enhanced cognitive training program to improve cognitive functions in older adults. <h3>Design</h3> Within-group pre- to post-training quasi-experimental design. <h3>Setting</h3> Academic institution. <h3>Participants</h3> Eighteen older adults (age 76±6); 18% women; MMSE scores 28±2) enrolled in the study. Fourteen (78%) completed pre-training and post-training assessments. <h3>Interventions</h3> Participants trained on the driving simulator for four weeks, three days per week for a total of 12 hours. Training involved following a lead car. The difficulty level of the training sessions was altered by changing the speed of the lead car, the following distance of the driver, visibility and weather conditions, and ambient traffic. <h3>Main Outcome Measures</h3> Participants completed a comprehensive battery of cognitive tests evaluating memory, visuospatial skills, word finding, and cognitive flexibility pre- and post-intervention. <h3>Results</h3> Pre- to post-training changes were examined using Wilcoxon Signed Rank test. Participants improved on the California Verbal Learning Test short delay free recall (2.31±1.75; p=0.001) and delayed recall (1.69±1.89; p=0.009); Rey-Osterrieth Complex Figure immediate recall (5.73±6.10; p=0.002) and delayed recall (2.54±4.61; p=0.05); Logical Memory immediate (3.61±4.89; p=0.02) and delayed (4.38±4.77; p=0.009) total scores; and Boston Naming Test total score (3.58±8.67; p=0.002). No changes were observed in performance on Delis-Kaplan Executive Function System and Wechsler Adult Intelligence Scale tests. <h3>Conclusions</h3> The enhanced cognitive training in a driving simulator improved several memory domains. This pilot study warrants an adequately powered randomized controlled trial to better determine the short- and long-term effects of enhanced cognitive training on cognition and daily-life activities in older adults. <h3>Author(s) Disclosures</h3> The authors report a financial conflict of interest. The training scenarios were played on the Portable Driving Simulator. H.D. and A.E.A. stand to profit from the sales of the Portable Driving Simulator. H.D. and A.E.A. were not involved in the training sessions or assessments.

The effect of speed-stress on driving behavior: A diffusion model analysis.

In everyday driving on the road, people are often required to make fast decisions that could compromise the accuracy of choices. We present a diffusion model analysis of the adjustments drivers make to the decision process under speed-stress. Participants operated a PC-based driving simulator while performing one of two decision-making tasks that required a driving action as a response to the stimulus. In a one-choice driving task, participants were asked to drive around a lead car when its brake lights were turned on. A two-choice driving task used a brightness-discrimination task in which participants were asked to drive to the left and back behind a lead car if there were more black than white pixels in a display and to the right and back if there were more white than black pixels. Speed-stress was operationalized by instructing drivers to respond as quickly as possible and by manipulating the distance drivers were required to maintain behind the lead car. Results showed the expected speed-accuracy tradeoff; however, the cost on accuracy in the two-choice task was relatively small. The model-based analysis showed that this was achieved by lowering the decision criteria and speeding up nondecision processes without disrupting components that produce evidence for the decision process. In fact, in the one-choice task, evidence accumulation rate in the speed-stress condition was found to be higher than in the accuracy-stress condition. We concluded that drivers were able to comply with speed-stress demands with relatively safe adjustments that imposed minimal costs on the accuracy of choices.

Modelling and simulation of adaptive cruise control and overtake assist system

The following paper presents an approach to model the Adaptive cruise control and Overtake Assist ADAS features for a vehicle. The physical structure for Adaptive Cruise Control (ACC) is modelled with the ego car equipped with a longitudinal Model Predictive Controller (MPC) & the lead car which we wish to follow at a safe distance. The long-range RADAR sensor would measure the real time relative velocity and relative distance as inputs to the MPC controller, a safe distance is calculated by the MPC with the help of a suitable time gap and compared with relative distance given as input to switch between the speed control and spacing control. Accordingly, a longitudinal output in the form of brake or acceleration is generated. MATLAB-SIMULINK have been used to model and simulate scenarios. The Flying type overtake is modelled to suit the Indian National Highway driving scenario with a single lane divided road. A decision tree is proposed for a four-car driving scenario with the vehicle of interest sandwiched between cars and a vehicle in the oncoming lane all driving at a constant speed. SCILAB-XCOS have been used to model the decision tree for the same.

Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-Control for Intelligent Vehicles

Intelligent vehicles can effectively improve traffic congestion and road traffic safety. Adaptive cruise following-control (ACFC) is a vital part of intelligent vehicles. In this paper, a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model, type-2 fuzzy control, feedforward + fuzzy proportion integration (PI) feedback (F+FPIF) control, and inverse longitudinal dynamics model of vehicles. Firstly, a traditional variable time headway model is improved considering the acceleration of the lead car. Secondly, an interval type-2 fuzzy logic controller (lT2 FLC) is designed for the upper structure of the ACFC system to simulate the driver's operating habits. To reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration, the control strategy of F+FPIF is given for the lower control structure. Thirdly, the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method (no lower controller for tracking desired acceleration) separately. Meanwhile, the proportion integration differentiation (PID), linear quadratic regulator (LQR), subsection function control (SFC) and type-l fuzzy logic control (Tl FLC) are respectively compared with the IT2 FLC in control performance under different scenes. Finally, the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

Intelligent Driver Assistance and Energy Management Systems of Hybrid Electric Autonomous Vehicles

Automotive companies continue to develop integrated safety, sustainability, and reliability features that can help mitigate some of the most common driving risks associated with autonomous vehicles (AVs). Hybrid electric vehicles (HEVs) offer practical solutions to use control strategies to cut down fuel usage and emissions. AVs and HEVs are combined to take the advantages of each kind to solve the problem of wasting energy. This paper presents an intelligent driver assistance system, including adaptive cruise control (ACC) and an energy management system (EMS), for HEVs. Our proposed ACC determines the desired acceleration and safe distance with the lead car through a switched model predictive control (MPC) and a neuro-fuzzy (NF) system. The performance criteria of the switched MPC toggles between speed and distance control appropriately and its stability is mathematically proven. The EMS intelligently control the energy consumption based on ACC commands. The results show that the driving risk is extremely reduced by using ACC-MPC and ACC-NF, and the vehicle energy consumption by driver assistance system based on ACC-NF is improved by 2.6%.

Abstract LB210: Preclinical development and evaluation of allogeneic CAR T cells targeting CD70 for the treatment of renal cell carcinoma

Abstract CD70 is highly expressed on renal cell carcinoma (RCC), with limited normal tissue expression, making it an attractive CAR T target for an immunogenic solid tumor indication. Here we generated and characterized a panel of anti-CD70 scFv-based CAR T cells. Despite the expression of CD70 on T cells, production of CAR T from a subset of scFvs with potent in vitro activity was achieved. Expression of CD70 CARs was found to mask CD70 detection in cis and provide protection from CD70 CAR T-mediated fratricide. Two unique classes of CAR T cells were identified with differing memory phenotype, activation status, and cytotoxic activity. Epitope mapping revealed CARs binding to the membrane distal region of the CD70 extracellular domain (ECD) fall into the more active and differentiated class, as compared to CARs binding the membrane proximal region of the CD70 ECD. CD70 CAR T cells were evaluated with rituximab-based off switches to provide control over CAR T function and displayed robust antitumor activity against RCC cell lines and patient-derived xenografts in mouse models. Tissue cross reactivity studies to evaluate off-target binding with two lead CARs showed membrane staining in rare tissue-resident lymphocytes, thus matching the known expression pattern of CD70. Expected findings related to T cell activation, and elimination of CD70-expressing cells were observed in a cynomolgus monkey CD3-CD70 bispecific toxicity study and included cytokine release and loss of cellularity in lymphoid tissues. Lastly, highly functional CD70 allogeneic CAR T cells were produced at large scale through elimination of the T cell receptor by TALEN® gene editing. Taken together, these efficacy and safety data support the evaluation of CD70 CAR T cells for the treatment of RCC and led to the advancement of an allogeneic CD70 CAR T candidate into Phase I clinical trials. Citation Format: Siler Panowski, Surabhi Srinivasan, Nguyen Tan, Silvia Tacheva-Grigorova, Bryan Smith, Yvonne Mak, Hongxiu Ning, Jonathan Villanueva, Dinali Wijewarnasuriya, Shanshan Lang, Zea Melton, Adit Ghosh, Mathilde Dusseaux, Roman Galetto, Jonathan Heyen, Tao Sai, Thomas Van Blarcom, Javier Chaparro-Riggers, Barbra Sasu. Preclinical development and evaluation of allogeneic CAR T cells targeting CD70 for the treatment of renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB210.

The effect of aging on decision-making while driving: A diffusion model analysis.

We present a diffusion model analysis of the effect of aging on decision processes during driving. Our goal was to examine the changes in the underlying components as a function of age and both task and environment difficulty. Younger and older adults performed each of three decision-making tasks while operating a computer-based driving simulator in which the task required a driving action. The first task was a one-choice task in which the response to brake lights turning on was to drive around a lead car. The second and third tasks were two-choice brightness-discrimination tasks in which participants were asked to drive the car to the left/right if there were more black/white pixels in an array of black and white pixels. Results showed that older adults were slower in the one-choice task and made more errors in the two-choice tasks than younger adults. The behavioral data were fitted well by one- and two-choice diffusion models, showing lower evidence accumulation rates (drift rates) in older than younger adults. Moreover, in the two-choice tasks under higher environmental demands, older adults showed a lower decision criterion (boundary separation) to compensate for a slower decision process. Together, the differences we found in the decision components between age groups provided an example of a subtle interaction between speed and accuracy in older versus younger adults, and this demonstrates the utility of this modeling approach in studying age effects in driving. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Stochastic dynamic simulation of railway vehicles collision using data-driven modelling approach

Using stochastic dynamic simulation for railway vehicle collision still faces many challenges, such as high modelling complexity and time-consuming. To address the challenges, we introduce a novel data-driven stochastic process modelling (DSPM) approach into dynamic simulation of the railway vehicle collision. This DSPM approach consists of two steps: (i) process description, four kinds of kernels are used to describe the uncertainty inherent in collision processes; (ii) solving, stochastic variational inferences and mini-batch algorithms can then be used to accelerate computations of stochastic processes. By applying DSPM, Gaussian process regression (GPR) and finite element (FE) methods to two collision scenarios (i.e. lead car colliding with a rigid wall, and the lead car colliding with another lead car), we are able to achieve a comprehensive analysis. The comparison between the DSPM approach and the FE method revealed that the DSPM approach is capable of calculating the corresponding confidence interval, simultaneously improving the overall computational efficiency. Comparing the DSPM approach with the GPR method indicates that the DSPM approach has the ability to accurately describe the dynamic response under unknown conditions. Overall, this research demonstrates the feasibility and usability of the proposed DSPM approach for stochastic dynamics simulation of the railway vehicle collision.

The EEG correlates and dangerous behavioral consequences of drowsy driving after a single night of mild sleep deprivation

ObjectiveHere, we investigated the behavioral, cognitive, and electrophysiological impact of mild, acute sleep loss via simultaneously recorded behavioral and electrophysiological measures of vigilance during a "real-world", simulated driving task. MethodsParticipants (N = 34) visited the lab for two testing days where their brain activity and vigilance were simultaneously recorded during a driving simulator task. The driving task lasted approximately 70 mins and consisted of tailgating the lead car at high speed, which braked randomly, requiring participants to react quickly to avoid crashing. The night before testing, participants either slept from 12am-9am (Normally Rested), or 1am-6am (Sleep Restriction). ResultsAfter a single night of mild sleep restriction, sleepiness was increased, participants took longer to brake, missed more braking events, and crashed more often. Brain activity showed more intense alpha burst activity and significant changes in EEG spectral power frequencies related to arousal (e.g., delta, theta, alpha). Importantly, increases in amplitude and number of alpha bursts predicted delays in reaction time when braking. ConclusionsThe findings of this study suggest that a single night of mild sleep loss has significant, negative consequences on driving performance and vigilance, and a clear impact on the physiology of the brain in ways that reflect reduced arousal. SignificanceUnderstanding neural and cognitive changes associated with sleep loss may lead to important advancements in identifying and preventing potentially dangerous sleep-related lapses in vigilance.

DDPG-based controller of enhanced adaptive cruise control with lane-change assistance for an articulated vehicle

Traditional adaptive cruise control (ACC) would choose to follow when encountering low-speed cars in front, but this may lead to low driving efficiency. This paper proposes a controller of enhanced adaptive cruise control with lane-change assistance (LCACC) for an articulated vehicle. A two-layer hierarchical control structure is adopted in this study. The upper determines high-level commands, while the bottom consisting of two modified deep deterministic policy gradient (DDPG) networks, controls the steering wheel and throttle/brake, respectively, according to the commands made by the upper layer. The vehicle’s lateral and longitudinal control are decoupled and controlled by two modified DDPG networks. Through proper design of the state and reward function, the actions of the articulated vehicle such as steering and acceleration/braking are closer to those of humans, thus ensuring ride comfort. Compared with traditional ACC, the LCACC proposed in this study increases the driving efficiency of the articulated vehicle by an average of 16% when there is a low-speed lead car.

Sex differences in cognitive-motor components of braking in older adults.

Fast and accurate braking is essential for safe driving and relies on efficient cognitive and motor processes. Despite the known sex differences in overall driving behavior, it is unclear whether sex differences exist in the objective assessment of driving-related tasks in older adults. Furthermore, it is unknown whether cognitive-motor processes are differentially affected in men and women with advancing age. We aimed to determine sex differences in the cognitive-motor components of the braking performance in older adults. Fourteen men (63.06 ± 8.53 years) and 14 women (67.89 ± 11.81 years) performed a braking task in a simulated driving environment. Participants followed a lead car and applied a quick and controlled braking force in response to the rear lights of the lead car. We quantified braking accuracy and response time. Importantly, we also decomposed response time in its cognitive (pre-motor response time) and motor (motor response time) components. Lastly, we examined whether sex differences in the activation and coordination of the involved muscles could explain differences in performance. We found sex differences in the cognitive-motor components of braking performance with advancing age. Specifically, the cognitive processing speed is 27.41% slower in women, while the motor execution speed is 24.31% slower in men during the braking task. The opposite directions of impairment in the cognitive and motor speeds contributed to comparable overall braking speed across sexes. The sex differences in the activation of the involved muscles did not relate to response time differences between men and women. The exponential increase in the number of older drivers raises concerns about potential effects on traffic and driver safety. We demonstrate the presence of sex differences in the cognitive-motor components of braking performance with advancing age. Driving rehabilitation should consider differential strategies for ameliorating sex-specific deficits in cognitive and motor speeds to enhance braking performance in older adults.

Cognition and driving ability in isolated and symptomatic REM sleep behavior disorder.

To analyze cognitive deficits leading to unsafe driving in patients with REM Sleep Behavior Disorder (RBD), strongly associated with cognitive impairment and synucleinopathy-related neurodegeneration. Twenty isolated RBD (iRBD), 10 symptomatic RBD (sRBD), and 20 age- and education-matched controls participated in a prospective case-control driving simulation study. Group mean differences were compared with correlations between cognitive and driving safety measures. iRBD and sRBD patients were more cognitively impaired than controls in global neurocognitive functioning, processing speeds, visuospatial attention, and distractibility (p < .05). sRBD patients drove slower with more collisions than iRBD patients and controls (p < .05), required more warnings, and had greater difficulty following and matching speed of a lead car during simulated car-following tasks (p < .05). Driving safety measures were similar between iRBD patients and controls. Slower psychomotor speed correlated with more off-road accidents (r = 0.65) while processing speed (-0.88), executive function (-0.90), and visuospatial impairment (0.74) correlated with safety warnings in sRBD patients. Slower stimulus recognition was associated with more signal-light (0.64) and stop-sign (0.56) infractions in iRBD patients. iRBD and sRBD patients have greater selective cognitive impairments than controls, particularly visuospatial abilities and processing speed. sRBD patients exhibited unsafe driving behaviors, associated with processing speed, visuospatial awareness, and attentional impairments. Our results suggest that iRBD patients have similar driving-simulator performance as healthy controls but that driving capabilities regress as RBD progresses to symptomatic RBD with overt signs of cognitive, autonomic, and motor impairment. Longitudinal studies with serial driving simulator evaluations and objective on-road driving performance are needed.

Distracting tasks have persisting effects on young and older drivers’ braking performance

It is well established that car driving performance suffers when the driver concurrently engages in a distracting activity, such as talking on a cell phone. The present study investigates whether the effects of driver distraction are short-lived, or rather persist for some time. Age-related differences are evaluated as well. Sixty-three young and 61 older adults were tested in a driving simulator. They were asked to follow a lead car that drove at a constant speed, and to concurrently engage in a pseudorandom sequence of distracting tasks (typing, reasoning, memorizing). When the lead car braked, participants had to brake as well to prevent a collision. The stimulus onset asynchrony between the braking task and the last preceding distraction was 11.49 ± 1.99 s. Each person was tested once in a multitasking condition (as described above), and once in a control condition without distracting tasks. Outcome measures quantified distance keeping and lane keeping while participants braked to the lead car. We found that braking responses differed significantly between conditions; this difference could be interpreted as a combination of performance deficits and compensatory strategies in the multitasking condition compared to the control condition. We also found significant differences between age groups, which could be interpreted similarly. Differences between age groups were less pronounced in the multitasking than in the control condition. All observed effects were associated with participants’ executive functioning. Our findings confirm that distractions have an impact on braking responses, and they document for the first time that this impact can persist for about 11.5 s. We attribute this persistence to a task set effect, and discuss the practical relevance of our findings.

Driving performance and road sign identification by multifocal contact lens wearers in a driving simulator

PurposeThe purpose of this study was to compare sign identification distances and driving performance metrics in presbyopic participants while wearing multifocal contact lenses (MFCL) and while wearing progressive addition lens (PAL) spectacles. Methods19 presbyopic participants completed PAL spectacle assessments and contact lens fitting and follow up visits before driving assessments began. These assessments occurred in a simulator equipped with a full-sized sedan on a motion platform and a 260 degree screen. Participants completed the driving task with PAL and with MFCL. Participants followed a lead car and identified signs at various distances from the road. For the two wearing conditions, comparisons of the distance along the road at which signs were identified were made using repeated measures ANOVA. Paired t-tests were used to compare driving performance for the two conditions. ResultsThere was no statistical difference in sign identification distance between PAL and MFLC for signs 32.0 m from the road side of the road (182 ± 46 m for MFCL; 205 ± 45 m for PAL; P = 0.07) or 51.4 m from the side of the road (204 ± 43 m for MFCL; 216 ± 36 m for PAL; P = 0.3). Only signs 70.2 m from the roadside showed a significant difference (207 ± 42 m with MFCL; 232 ± 39 m with PAL; P = 0.01), All distances were greater than those required to safely stop a vehicle. There were no significant differences in the driving performance metrics between the refractive corrections. ConclusionDriving performance metrics were similar for MFCL and PAL spectacles. Sign identification distances with both eyewear types were well within the distances required for safe vehicle stopping.