In vehicular accident reconstruction, a number of parameters need to be estimated, as commonly no specific measurement data or convenient measurement methods are available. One of these parameters is ...the position of a car’s centre of gravity. Depending on the impact configuration, the centre of gravity may have a significant influence on the reconstruction result. A number of regression models and rules of thumb have already been developed in the past to calculate the position of the centre of gravity. The further automotive vehicle development in recent years has led to different vehicle architectures with larger masses. This study therefore deals with developing and testing a new regression model for vehicles, distinguishing between conventional and electric drives. That is based on the analysis of 147 rollover stability measurements of road vehicles from the years 2016–2022. The model developed from these tests for the centre of gravity height shows a good fit with the measurement data and only requires knowledge of the roof height.
•Evaluation of latest rollover stability measurement data•Development of an regression model for approximation of CG height of CEVs•Development of an regression model for approximation of CG height of BEVs
Though the battery capacity is increasing, in day-to-day operation, battery-electric buses (BEB) are still not able to replace buses with combustion engine one by one. Determining the best option to ...purchase or the daily operation of a BEB requires consumption estimation. Generally, the consumption is calculated using real data from test runs; however, testing an electric bus has a high cost. Without preliminary data collection, estimating the consumption is a barely studied area. The paper aims to elaborate a consumption estimation method applied in a data-deficient and inexperienced environment using general route characteristics. The consumptions of the drivetrain and auxiliary system are calculated considering uncertainties affecting fluctuations, such as ambient temperature, topography, stop spacing, and passenger load.
The method developed was applied as a case study and verified by real-time consumption data. The minimum energy consumption is determined by considering the largest consumers, which correlate with the data measured in real conditions. According to the application, the calculated consumption of buses is feasible and basically provides a fairly good approximation. Estimating the driving dynamics also gives a good approximation; however, the differences are significant if the consumption of cooling and heating and other electric auxiliaries are also considered.
The result of the method is a rough estimation of the energy consumption in a line which can be applied for decision making before purchasing a new BEB or introducing a BEB on a new route.
•Consumption estimation method using general route characteristics.•Instead of consumption data, vehicle dynamics and power of consumers are used.•Factors considered: ambient temperature, topography, stop distance, passenger load.•Lower temperature results in higher consumption.•Lower passenger load and longer stop spacing result in lower consumption.
•Influence of VR and inclusion of the test subject on the evaluation of drive-off procedures has been investigated.•A study with three parts has been conducted with a total number of 76 test ...subjects.•Sense of presence has been measured using the IPQ questionnaire.•Multisensory cueing shows a negligible effect on the evaluation of the drive-off behaviour under the tested conditions.•The interaction of the test subject with the virtual vehicle results in a better VR experience.
The importance of a realistic driving feeling for the validity of driving simulator studies has been investigated by many researchers. These investigations focus on rather abstract test objectives like driving experience or safety aspects and indicate that a high sense of presence is important to achieve realistic behaviour of the driver. However, it is not clear if this must similarly be true for driving dynamic studies with precise test objectives like acceleration or jerk. In this paper, we investigate the influence of multisensory cues and interaction with the virtual vehicle on the experienced sense of presence and the evaluation of drive-off procedures. In a three-part experimental study with different variations of the virtual reality and the driver’s interaction with the virtual vehicle, the sense of presence is measured and compared in a between-groups design. Furthermore, the evaluations of nine drive-off acceleration profiles are compared. The results show that diverse multisensory cues do not significantly impact the experienced sense of presence regarding the general presence, spatial presence or realism. As expected, interacting with the virtual vehicle leads to higher involvement ratings. The results of the acceleration profiles evaluations indicate that multisensory cueing has a negligible effect on the evaluation of the drive-off behaviour under the tested conditions. The interaction of the driver with the virtual vehicle offers the test subject a better experience in virtual reality.
Route topography is an important boundary condition for the regulated real driving emission (RDE) test. However, accurately and comprehensively evaluating the influence of route topography on the RDE ...test is difficult, because the effect cannot be easily separated from those of other test boundaries. We selected two light-duty gasoline vehicles to complete two rounds of RDE tests on four different test routes, and conducted the correlation analysis between pollutant emissions and route topography quantified by the cumulative positive altitude gains of the test routes based on the moving averaging window method. Since the small number of sample data at the total trip and road section level were not sufficiently representative of the population, we proposed to use the pollutant emission data of the data windows to analyze the complex coupling effect of the cumulative positive altitude gains and trip dynamic parameters of v·apos95 on the RDE tests. At data window level, thousands of data windows were treated as the road section subsets of the RDE test, and the sample space of road section emission data was expanded by several orders of magnitude. With the help of the large data sample space, the influence mechanism of the random test boundaries on the RDE tests was demonstrated.
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•Correlation analysis of the RED test data was extended to the data window level.•Emission data space was greatly expanded by treating the data window as a sample.•Coupling effect mechanism of route topography and trip dynamics was demonstrated.•Pollutant emission characteristics affected by route topography were revealed.•The joint limitation of test boundaries should be considered in the RDE regulation.
Whereas autonomous vehicles are expected to provide several advantages, the current scenarios envisioned for self-driving vehicles are expected to increase the incidence of motion sickness. This ...study investigates the effects of dynamic visual stimuli on the development of carsickness under two different view conditions. A prototypical light-emitting diode (LED) feedback system visualizing longitudinal driving dynamics in the passenger's peripheral visual field was installed in the rear of a modified serial vehicle. A real driving experiment was conducted on the test track of a major car manufacturer. Subjective motion sickness ratings were recorded. It was hypothesized that carsickness can be mitigated with the information from the visual feedback system. Subjective motion sickness scores tended to be lower with the LED feedback system while there was no substantial interaction effect with the view condition. Although the results indicate potential benefits of the LED feedback system for the mitigation of motion sickness, further development of the system and its functionalities and the inclusion of psychophysiological measures to objectively quantify motion sickness is necessary to confirm these findings.
In this paper, based on model predictive control algorithm, a torque demand control approach is proposed to optimize driving energy consumption of battery electric vehicle, which consists of demand ...control approach and model predictive controller. The demand control approach is developed to compute the driving mode and the desired vehicle speed. For the design of control law, a novel driving dynamics model of battery electric vehicle is formulated into a set of differential equations by vehicle speed, the front and rear wheel speed. A model predictive control law is designed to compute the optimized torque of electric motor. The torque demand model predictive control algorithm is downloaded into vehicle control unit, which is equipped on the battery electric vehicle for experimental validation. The New European Driving Cycle is utilized to test the control law on the real road. The experimental results indicate that the proposed model predictive controller has a preferable performance in reducing energy consumption, which can improve 1.81% over the original control strategy in the urban road cycle and 1.67% in the city highway condition. It can be considered that the torque demand model predictive control approach is a good candidate for driving energy optimization of battery electric vehicle.
•Geometric design consistency of two-lane rural highways is correlated with run-off-road crashes.•Three design consistency measures are alignment consistency, operating speed consistency and driving ...dynamics consistency.•Multiple road geometric characteristics captured through design consistency are critical for run-off-road crashes.•Sudden changes in roadway alignment increase the risk of run-off-road crashes.•High variations in operating speed are associated with run-off-road crash risks.
Run-off-road crashes are one of the most common crash types, especially in rural roadway environments contributing significantly to fatalities and severe injuries. These crashes are complex and multi-dimensional events, and factors like road geometry, driver behaviour, traffic characteristics and roadside features contribute to their occurrence, separately or interactively. Sudden changes in road geometry, in particular, can influence driver behaviour, and therefore, in developing a micro-level crash risk model for run-off-road crashes, one of the challenges is incorporating the effects of driver behaviour (disaggregated information) that may arise from the variations in road geometry (aggregated information). This study aims to examine the interaction between road geometry and driver behaviour through a set of measures for design consistency on two-lane rural roads. Multiple data sources, including crash data for 2014–18, traffic data, probe speed data and roadway geometric data, for twenty-three highways in Queensland, Australia, have been fused for this study. Seventeen types of design consistency measures with regard to alignment consistency, operating speed consistency and driving dynamics are tested. A run-off-road crash risk model is estimated by employing the Random Parameters Negative Binomial Lindley regression framework, which accounts for excess zeros in the crash counts and captures the effects of unobserved heterogeneity in the parameter estimates. Results indicate that the geometric design consistency capturing the interaction between driver behaviour and operational factors better predicts run-off-road crashes along rural highways. In addition, roadside attributes like clear zone width, infrastructures, terrain, and roadway remoteness also contribute to run-off-road crashes. The findings of the study provide a comprehensive understanding of the influence of variations in roadway geometry on driver behaviour and run-off-road crashes along rural highways.
Step increase of electric motor torque results in wheel slip during the acceleration of battery electric vehicle (BEV), making vehicle body instability paramount. This is particularly challenging for ...regulating the torque of electric motor to keep stability in the process of acceleration, for which regulating the wheel slip to an ideal set-point is difficult for the central driving powertrain that adopts one electric motor to drive both left and right wheels by a differential. While much of the research on acceleration slip regulation has focused on solving the wheel anti-slip of internal combustion powertrain by electronic stability programme, comparatively little is known about the wheel slip control by electric motor torque of the central driving powertrain that is the most common style of driveline in the market of BEV currently. Here we discuss a series of studies on the acceleration slip regulation by electric motor torque that, collectively, design an approach of how the nonlinear model predictive controller based on a novel driving dynamics model regulates the wheel slip to an ideal set-point from the ideal slip ratio curve. Testing and validating this approach embedded into vehicle control unit are carried out in a BEV to fully realise the wheel slip control by electric motor torque during the acceleration.
We present a coupled macroscopic traffic and emission modelling system tailored to the Barcelona metropolitan area that allows estimating hourly road transport emissions at road link level. We use ...the developed system to perform an emission sensitivity analysis of typically high uncertainty emission features and assess their impact. We also explore the uncertainties of our system compared to a microscopic approach in a representative area of Barcelona. The developed macroscopic system shows a high sensitivity to spatially-resolved vehicle fleet composition inputs, meteorological effects on diesel engines (+19% in NOx) and non-exhaust sources (80% of total PM emissions). The comparison with the microscopic system shows that discrepancies grow as a function of the congestion level, up to +65% in NOx. The resulting coupled system will be used in further steps of the research to evaluate the impact of traffic management strategies upon urban emissions and air quality levels in Barcelona.
•The coupled system provides dynamic street-level emissions across 265k street segments.•Satisfactory overall behaviour despite some limitations in heavy traffic conditions.•Accounting for real public bus routes and non-exhaust PM sources has a strong impact.•The system will help evaluating the impact of mobility policies on air quality.
Motorcycle riders are vulnerable road users, who suffer fatal accident outcomes at significantly higher rates than car drivers. Lifesaving assistance systems are considerably harder to integrate in ...the operation of a motorcycle, compared to the operation of a more predictably moving car. Here we present a methodology of estimating an individual rider's classifier of “risky” dynamics from their riding behaviour on several popular motorcycling routes in an experimental set up. Using clustering of common motions and data obtained at known accident sites, as well as an updating regime for the model fit to the individual rider, we are able to identify potential riding risks in an online methodology and determine the driving factors (i.e., the most relevant dynamics for a motion to be classified as risky) in the risk estimate, to potentially base interventions on.
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