Search Results (279)

Transportation is often cited as a significant barrier to healthcare access by Veterans, particularly those from minority groups, who have disabilities, or live in rural areas. Autonomous shuttles (AS) offer a potential solution, yet limited research has explored Veterans’ experiences with this technology. This study qualitatively investigated Veterans’ lived experiences with AS through focus groups, enrolling participants aged 18+ from Gainesville, The Villages, and Lake Nona, Florida. Via a directed content analysis, six key themes were identified: Perceived Benefits, Safety, Experience with Autonomous Vehicles (AV), AS Experience, AV Adoption, and Perception Change. Among 26 participants (aged 30–85; 77% men; 88% urban residents), prominent themes included Safety (n = 161), Perceived Benefits (n = 153), and AS Experience (n = 118), with predominantly positive counts in all themes except AS Experience. Participants acknowledged safety advantages and multitasking potential of AS over human-operated vehicles while recommending improvements to the shuttle’s slow speed, availability and convenience. While the AS ride was positively received overall, some participants noted issues with comfort and braking, emphasizing the need for further technological enhancements. Real-world exposure to AS appeared to influence acceptance positively, offering insights for policymakers and industry stakeholders aiming to optimize AS deployment for mobility-vulnerable Veterans. Full article

Sensor fusion in intelligent suspension systems constitutes a fundamental technology for optimizing vehicle dynamic stability, ride comfort, and occupant safety. By integrating data from multiple sensor modalities, this study proposes a hierarchical multi-sensor fusion framework for active suspension control, aiming to enhance control precision. Initially, a binocular vision system is employed for target detection, enabling the identification of lane curvature initiation points and speed bumps, with real-time distance measurements. Subsequently, the integration of Global Positioning System (GPS) and inertial measurement unit (IMU) data facilitates the extraction of road elevation profiles ahead of the vehicle. A BP-PID control strategy is implemented to formulate mode-switching rules for the active suspension under three distinct road conditions: flat road, curved road, and obstacle road. Additionally, an ant colony optimization algorithm is utilized to fine-tune four suspension parameters. Utilizing the hardware-in-the-loop (HIL) simulation platform, the observed reductions in vertical, pitch, and roll accelerations were 5.37%, 9.63%, and 11.58%, respectively, thereby substantiating the efficacy and robustness of this approach. Full article

The increasing presence of high-rise buildings with curved and convex facades poses significant challenges for facade-cleaning robots, particularly in terms of mobility and anchoring. To address this, we propose a rope-riding mobile anchor (RMA) system capable of repositioning the anchor point of a cleaning robot on convex building surfaces. The RMA travels horizontally along a roof-mounted nylon rope using caterpillar tracks with U-shaped grooves, and employs a four-bar linkage mechanism to fix its position securely by increasing rope contact friction. This structural principle was selected for its simplicity, stability under heavy loads, and efficient actuation. Experimental results show that the RMA can support a payload of 50.5 kg without slippage under tensions up to 495.24 N, and contributes to reducing the power consumption of the cleaning robot during operation. These findings demonstrate the RMA’s effectiveness in extending the robot’s working range and enhancing safety and stability in facade-cleaning tasks on complex curved surfaces. Full article

The automotive suspension must perform competently to support comfort and safety when driving. Traditionally, car suspension control tuning is performed through trial and error or with classical techniques that cannot guarantee optimal performance under varying road conditions. The study aims at designing a Linear Quadratic Regulator-based Bacterial Memetic Algorithm (LQR-BMA) for suspension systems of automobiles. BMA combines the bacterial foraging optimization algorithm (BFOA) and the memetic algorithm (MA) to enhance the effectiveness of its search process. An LQR control system adjusts the suspension’s behavior by determining the optimal feedback gains using BMA. The control objective is to significantly reduce the random vibration and oscillation of both the vehicle and the suspension system while driving, thereby making the ride smoother and enhancing road handling. The BMA adopts control parameters that support biological attraction, reproduction, and elimination-dispersal processes to accelerate the search and enhance the program’s stability. By using an algorithm, it explores several parts of space and improves its value to determine the optimal setting for the control gains. MATLAB 2024b software is used to run simulations with a randomly generated road profile that has a power spectral density (PSD) value obtained using the Fast Fourier Transform (FFT) method. The results of the LQR-BMA are compared with those of the optimized LQR based on the genetic algorithm (LQR-GA) and the Virus Evolutionary Genetic Algorithm (LQR-VEGA) to substantiate the potency of the proposed model. The outcomes reveal that the LQR-BMA effectuates efficient and highly stable control system performance compared to the LQR-GA and LQR-VEGA methods. From the results, the BMA-optimized model achieves reductions of 77.78%, 60.96%, 70.37%, and 73.81% in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the GA-optimized model. Moreover, the BMA-optimized model achieved a −59.57%, 38.76%, 94.67%, and 95.49% reduction in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the VEGA-optimized model. Full article

Unbalanced accelerations occurring during tram travel have a significant impact on passenger comfort and safety, as well as on the rate of wear and tear on infrastructure and rolling stock. Ideally, these dynamic forces should be monitored continuously in real-time; however, traditional systems require high-precision accelerometers and proprietary software—investments often beyond the reach of municipally funded tram operators. To this end, as part of the research project “Accelerometer Measurements in Rail Passenger Transport Vehicles”, pilot measurement campaigns were conducted in Poland on tram lines in Gdańsk, Toruń, Bydgoszcz, and Olsztyn. Off-the-shelf smartphones equipped with MEMS accelerometers and GPS modules, running the Physics Toolbox Sensor Suite Pro app, were used. Although the research employs widely known methods, this paper addresses part of the gap in affordable real-time monitoring by demonstrating that, in the future, equipment equipped solely with consumer-grade MEMS accelerometers can deliver sufficiently accurate data in applications where high precision is not critical. This paper presents an analysis of a subset of results from the Gdańsk tram network. Lateral (x) and vertical (z) accelerations were recorded at three fixed points inside two tram models (Pesa 128NG Jazz Duo and Düwag N8C), while longitudinal accelerations were deliberately omitted at this stage due to their strong dependence on driver behavior. Raw data were exported as CSV files, processed and analyzed in R version 4.2.2, and then mapped spatially using ArcGIS cartograms. Vehicle speed was calculated both via the haversine formula—accounting for Earth’s curvature—and via a Cartesian approximation. Over the ~7 km route, both methods yielded virtually identical results, validating the simpler approach for short distances. Acceleration histograms approximated Gaussian distributions, with most values between 0.05 and 0.15 m/s², and extreme values approaching 1 m/s². The results demonstrate that low-cost mobile devices, after future calibration against certified accelerometers, can provide sufficiently rich data for ride-comfort assessment and show promise for cost-effective condition monitoring of both track and rolling stock. Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors. Full article

Ride-pooling (RP) services, in which passengers with similar destinations share a ride, offer considerable potential for enhancing urban mobility by bridging gaps in public transportation (PT) networks and providing a convenient alternative to private car use. For the effective design and operation of such services, a detailed understanding of user preferences and usage patterns is essential. This study investigates differences in RP preferences and usage between day and night (with nighttime defined as 10:00 p.m. to 5:00 a.m.), drawing on both a stated choice experiment (SCE) and revealed preference data collected in Mannheim, Germany. The focus lies on the local RP service fips, which is integrated into the PT system. The SCE, conducted in 2024 with 566 participants, was analyzed using a nested logit model. The analysis of the SCE reveals that nighttime preferences for RP are characterized by reduced sensitivity to travel time and cost, creating an opportunity for RP operators to optimize stop network designs during nighttime hours by increasing pooling rates. In addition, it indicates a greater likelihood of private car usage at night, especially among women, likely due to safety concerns and limited PT availability. The analysis of revealed preference data provides a complementary perspective. It shows that the RP nighttime service primarily attracts younger users, while many respondents report not being active on weekend nights. However, the combination of low public awareness and limited service availability, evidenced by rejected booking requests, suggests that existing demand is not being fully captured. This implies that low usage is not merely the result of low demand, but also of structural barriers on both the supply and information side. Overcoming these barriers through targeted information campaigns and expansion of nighttime service capacity could substantially enhance sustainable urban travel options during nighttime. Full article

Train–bridge dynamic interaction analysis is critical for the dynamic design of bridges and the safety and comfort assessment of trains. This study introduces a train–bridge dynamic model of a straddle monorail train and a steel–concrete composite track beam to investigate the dynamic performance of the bridge and train. It explores the influence of track irregularities and passenger loads on the dynamic response of train–bridge systems at various traveling speeds. The numerical results indicate that there is no significant resonance between the straddle monorail train and the steel–concrete composite bridge. However, track irregularities and train speed significantly amplify the responses of the train and bridge, including displacement, acceleration, and impact coefficient. Additionally, increased passenger load leads to a substantial rise in the vertical displacement of the bridge while reducing the vibration of the train, thereby improving riding comfort. The findings of this study provide valuable scientific insights and have significant practical applications for the use of steel–concrete composite bridges in straddle monorail systems. Full article

Distributed-drive electric vehicles (DDEVs), through independent, rapid, and precise control of the driving/braking torque of each wheel, offer unprecedented opportunities to enhance their handling stability, ride comfort, energy economy, and safety. However, their inherent over-actuation characteristics and multi-degree-of-freedom motion coupling pose significant challenges to the vehicle chassis control system. Chassis coordinated control, by coordinating multiple subsystems such as drive, braking, steering, and suspension, has become a key technology to fully leverage the advantages of distributed drive and address its challenges. This paper reviews the core issues in chassis coordinated control for DDEVs, comparatively analyzes several distributed electric drive coordinated control architectures, and systematically outlines recent research progress in lateral–longitudinal, lateral–vertical, longitudinal–vertical, and combined three-dimensional (lateral–longitudinal–vertical) coordinated control, including control architectures, key technologies, commonly used algorithms, and control allocation strategies. By analyzing and comparing the advantages, disadvantages, and application scenarios of different coordinated control schemes, this paper summarizes the key scientific problems and technical bottlenecks in this field and looks forward to development trends in intelligence, integration, and scenario-based fusion, aiming to provide a reference for the development of high-performance chassis control technology for DDEVs. Full article

Existing studies on platoon trajectory optimization of connected and automated vehicles face challenges in balancing computational efficiency, privacy, and safety. This study proposes a distributed optimization method that decomposes the platoon trajectory planning problem into independent individual vehicle tasks while ensuring safe inter-vehicle following gaps and maximizing travel efficiencyand ride comfort. The individual vehicle problems independently optimize their trajectory to improve computational efficiency, and only exchange dual variables related to safe following gaps to preserve privacy. Simulation experiments were conducted under single-platoon scenarios with different simulation horizons, as well as multi-platoon and platoon-merging scenarios, to analyze the control performance of the distributed method in contrast to the centralized method. Simulation results demonstrate that the mean computation time is reduced by 50% and the fuel consumption is decreased by 4% compared to the centralized method while effectively maintaining the safe inter-vehicle following gaps. The distributed method shows its scalability and adaptability for large-scale problems. Full article

This paper proposes a dynamic weight model predictive control (DWMPC) strategy for adaptive cruise control (ACC) in pure electric vehicles, aiming to enhance robustness, energy efficiency, and ride comfort under complex traffic conditions. Unlike conventional MPC with static weights, the proposed method integrates a fuzzy inference system that evaluates driving urgency based on real-time spacing and velocity errors. The resulting emergency coefficient is mapped through a nonlinear function to dynamically adjust the velocity tracking weight in the MPC cost function. Additionally, a four-mode coordination mechanism adaptively modifies acceleration and jerk penalties according to risk levels, enabling balanced responses between safety and comfort. A composite performance evaluation index (PEI) is formulated to quantitatively assess energy consumption, ride comfort, spacing accuracy, and emergency responsiveness. Simulation results under WLTC and typical urban driving scenarios demonstrate that DWMPC outperforms fixed-weight MPC and PI controllers, reducing energy consumption by 6.5%, jerk by 42.9%, and response time by 41.8% while improving coordination in speed tracking, inter-vehicle distance regulation, and energy-efficient control. Full article

This paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, with the dual goals of enhancing ride comfort and safety while ensuring system stability and robustness against road disturbances. The proposed approach deliberately avoids the use of Lyapunov-Krasovskii functionals, offering a more practical and computationally efficient alternative. Experimental results confirm that the proposed MR damper model outperforms traditional Lyapunov-Krasovskii-based methods. Additionally, two simulated road profiles are used to evaluate the suspension system’s behavior, further demonstrating the effectiveness of the proposed control strategy. Full article

To enhance energy efficiency and reduce emissions in public transportation systems, this study proposes a novel electro-hydraulic energy-regenerative suspension system for urban buses. A comprehensive co-simulation framework was established to evaluate system performance. Targeting ride comfort and energy regeneration performance as dual optimization objectives, we conducted systematic parameter analysis through design-of-experiments methodology to identify critical structural parameters. To streamline multi-objective optimization processes, a particle swarm optimization–back propagation (PSO-BP) neural network surrogate model was developed to approximate the complex co-simulation system. Subsequent non-dominated sorting genetic algorithm II (NSGA-II) implementation enabled effective multi-objective optimization of key suspension parameters. Comparative simulations revealed that the optimized configuration achieves the following: (1) maintains ride comfort within human perception thresholds despite slight performance reduction, (2) enhances energy recovery efficiency, and (3) improves roll stability characteristics. These findings demonstrate the proposed system’s capability to balance passenger comfort with energy conservation and safety requirements. Full article

The Dujiangyan–Siguniangshan mountain rack railway project is China’s first mountain rail transit. Most of its lines are located in mountainous areas and close to natural ecological protection areas, which have strict restrictions on the vibration and noise of train operation. At the same time, the vibration of mountain rack railway trains is also an important factor affecting the safety and riding comfort of trains. However, due to the multi-source vibration of gear teeth, wheels, rails, and suspensions, it is difficult to clearly define the vibration characteristics and vibration transmission path of the train, which has a serious impact on its vibration noise suppression and optimization. To this end, this study proposed a set of evaluation methods for the vibration characteristics and transfer paths of mountain rack trains based on a combination of dynamics and operational transfer path analysis (OTPA). Considering the interaction between the dynamic behaviors of the primary and secondary suspensions, the gear tooth contact behavior, the wheel–rail contact behavior and the dynamic behaviors of the track system, a dynamic model of a mountain rack train based on the finite element method was established, and the effectiveness of the model was verified through field experiments. On this basis, the OTPA method was used to establish a vibration transfer path model between the secondary suspension and the center of mass of the car body, and it was used to analyze the vibration mechanism and transfer path of the train body at the rated speed (20 km/h) and the limited speed (30 km/h). This study is of great significance for suppressing the vibration noise of mountain rack trains, reducing the impact on the ecological environment and improving ride comfort. Full article

In the field of active safety technology for intelligent connected vehicles (ICVs), the reliability and safety of the Automatic Emergency Braking (AEB) system is recognized as critical to driving safety. However, existing evaluation methods have been constrained by the inadequacy of static weight assessments in adapting to diverse driving conditions, as well as by the disconnect between conventional evaluation frameworks and experimental validation. To address these limitations, a comprehensive Vehicle-in-the-Loop (VIL) evaluation system based on the dynamic weight analytic hierarchy process (DWAHP) was proposed in this study. A two-tier dynamic weighting architecture was established. At the criterion level, a bivariate variable–weight function, incorporating the vehicle speed and road surface adhesion coefficient, was developed to enable the dynamic coupling modeling of road environment parameters. At the scheme level, a five-dimensional indicator system—integrating braking distance, collision speed, and other key metrics—was constructed to support an adaptive evaluation model under multi-condition scenarios. By establishing a dynamic mapping between weight functions and driving condition parameters, the DWAHP methodology effectively overcame the limitations associated with fixed-weight mechanisms in varying operating conditions. Based on this framework, a dedicated AEB system performance test platform was designed and developed. Validation was conducted using both VIL simulations and real-world road tests, with a Volvo S90L as the test vehicle. The experimental results demonstrated high consistency between VIL and real-world road evaluations across three dimensions: safety (deviation: 0.1833/9.5%), reliability (deviation: 0.2478/13.1%), and riding comfort (deviation: 0.05/2.7%), with an overall comprehensive score deviation of 0.0707 (relative deviation: 0.51%). This study not only verified the technical advantages of the dynamic weight model in adapting to complex driving environments and analyzing multi-parameter coupling effects but also established a systematic methodological framework for evaluating AEB system performance via VIL. The findings provide a robust foundation for the testing and assessment of AEB system, offer a structured approach to advancing the performance evaluation of advanced driver assistance systems (ADASs), facilitate the safe and reliable validation of ICVs’ commercial applications, and ultimately contribute to enhancing road traffic safety. Full article

This study introduces a novel magnetorheological (MR) damper for semi-active vehicle suspension systems that enhance ride comfort and handling stability. The proposed damper integrates reverse and normal damping modes, enabling independent control of rebound and compression strokes through an external MR valve. This configuration supports four damping modes—Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard—allowing adaptability to varying driving conditions. Magnetic circuit optimization ensures rapid damping force adjustments (≈10 ms), while a semi-active control algorithm incorporating skyhook logic, roll, dive, and squat control strategies was implemented. Experimental validation on a mid-sized sedan demonstrated significant improvements, including a 30–40% reduction in vertical acceleration and pitch/roll rates. These enhancements improve vehicle safety by reducing body motion during critical maneuvers, potentially lowering accident risk and driver fatigue. In addition to performance gains, the simplified MR damper architecture and modular control facilitate easier integration into diverse vehicle platforms, potentially streamlining vehicle design and manufacturing processes and enabling cost-effective adoption in mass-market applications. These findings highlight the potential of MR dampers to support next-generation vehicle architectures with enhanced adaptability and manufacturability. Full article