Search Results (7)

This article discusses the safety issues of autonomous vehicles using GNSS when transporting particularly dangerous goods, such as flammable and explosive materials. A method for the special processing of GNSS navigation information is presented, which consists of collecting readings of the relative navigation positions of the vehicle. The novelty of the method lies in the substantiation of the refusal to use a standard speedometer and the study of the minimum permissible vehicle speed, measured exclusively on the basis of the results of processing GNSS data. To confirm the assumptions inherent in the described method, a physical experiment was carried out, the results of which showed that the accuracy of the speedometers of standard vehicles is insufficient to ensure sufficient safety if the required driving speed should not exceed several km/h. The methodological basis for conducting a physical experiment is to measure the sequence of calculations of the coordinates {X_i, Y_i}(t), i = 1, 2, … of the vehicle, continuously calculate the vehicle speed in km/h, and use a speed limiting device set to a certain permissible technical state for the transportation of especially dangerous goods. Full article

This paper presents an experimental investigation of drivers’ reading reaction times and errors when reading a speedometer as a part of a complex instrument cluster. The laboratory-based experiment involved 32 participants and 7 instrument clusters from existing passenger cars. The objective of this study was to analyze the effects of different instrument cluster (IC) designs on the time and accuracy of information retrieval from the speedometer, including correlations with participants’ age and gender. Reaction times ranged from 451 ms to 11,116 ms. Reading accuracy was assessed based on the number of coarse errors, among other factors. The results indicated no influence of participants’ gender on performance, while a moderate positive correlation was observed between reaction time and participants’ age. Specific design features of both the speedometer and the IC that could be related to the results were identified. From the point of view of both reaction time and reading accuracy, centrally located speedometers (whether digital or analog) were found to be more effective. The highest number of coarse errors occurred when participants misread information, attributed to unfavorable layouts and designs of two instrument clusters. Full article

Lane-level localization is critical for autonomous vehicles (AVs). However, complex urban scenarios, particularly tunnels, pose significant challenges to AVs’ localization systems. In this paper, we propose a fusion localization method that integrates multiple mass-production sensors, including Global Navigation Satellite Systems (GNSSs), Inertial Measurement Units (IMUs), cameras, and high-definition (HD) maps. Firstly, we use a novel electronic horizon module to assess GNSS integrity and concurrently load the HD map data surrounding the AVs. This map data are then transformed into a visual space to match the corresponding lane lines captured by the on-board camera using an improved BiSeNet. Consequently, the matched HD map data are used to correct our localization algorithm, which is driven by an extended Kalman filter that integrates multiple sources of information, encompassing a GNSS, IMU, speedometer, camera, and HD maps. Our system is designed with redundancy to handle challenging city tunnel scenarios. To evaluate the proposed system, real-world experiments were conducted on a 36-kilometer city route that includes nine consecutive tunnels, totaling near 13 km and accounting for 35% of the entire route. The experimental results reveal that 99% of lateral localization errors are less than 0.29 m, and 90% of longitudinal localization errors are less than 3.25 m, ensuring reliable lane-level localization for AVs in challenging urban tunnel scenarios. Full article

Driving simulators are increasingly being incorporated by driving schools into a training process for a variety of vehicles. The motion platform is a major component integrated into simulators to enhance the sense of presence and fidelity of the driving simulator. However, less effort has been devoted to assessing the motion cues feedback on trainee performance in simulators. To address this gap, we thoroughly study the impact of motion cues on braking at a target point as an elementary behavior that reflects the overall driver’s performance. In this paper, we use an eye-tracking device to evaluate driver behavior in addition to evaluating data from a driving simulator and considering participants’ feedback. Furthermore, we compare the effect of different motion levels (“No motion”, “Mild motion”, and “Full motion”) in two road scenarios: with and without the pre-braking warning signs with the speed feedback given by the speedometer. The results showed that a full level of motion cues had a positive effect on braking smoothness and gaze fixation on the track. In particular, the presence of full motion cues helped the participants to gradually decelerate from 5 to 0 ms⁻¹ in the last 240 m before the stop line in both scenarios, without and with warning signs, compared to the hardest braking from 25 to 0 ms⁻¹ produced under the no motion cues conditions. Moreover, the results showed that a combination of the mild motion conditions and warning signs led to an underestimation of the actual speed and a greater fixation of the gaze on the speedometer. Questionnaire data revealed that 95% of the participants did not suffer from motion sickness symptoms, yet participants’ preferences did not indicate that they were aware of the impact of simulator conditions on their driving behavior. Full article

Various high budget industries that utilize wheel-based vehicles rely on wheel odometry as an integral aspect of their navigation process. This research introduces a low-cost alternative for typical wheel encoders that are typically used to determine the on-track speed of vehicles. The proposed system is referred to as an Accelerometer-based Wheel Odometer for Kinematics determination (AWOK). The AWOK system comprises just a single axis accelerometer mounted radially at the center of any given wheel. The AWOK system can provide direct distances instead of just velocities, which are provided by typical wheel speedometers. Hence, the AWOK system is advantageous in comparison to typical wheel odometers. Besides, the AWOK system comprises a simple assembly with a highly efficient data processing algorithm. Additionally, the AWOK system provides a high capacity to handle high dynamics in comparison to similar approaches found in previous related work. Furthermore, the AWOK system is not affected by the inherited stochastic errors in micro-machined electro-mechanical systems (MEMS) inertial sensors, whether short-term or long-term errors. Above all, the AWOK system reported a relative accuracy of 0.15% in determining the distance covered by a car. Full article

Vehicle speed-over-ground (SoG) radar offers significant advantages over conventional speed measurement systems. Radar sensors enable contactless speed measurement, which is free from wheel slip. One of the key issues in SoG radar is the development of the Doppler shift estimation algorithm. In this paper, we compared two algorithms to estimate a mean Doppler frequency accurately. The first is the center-of-mass algorithm, which based on spectrum center-of-mass estimation with a bandwidth-limiting technique. The second is the cross-correlation algorithm, which is based on a cross-correlation technique by cross-correlating Doppler spectrum with a theoretical Gaussian curve. Analysis shows that both algorithms are computationally efficient and suitable for real-time SoG systems. Our extensive simulated and experimental results show both methods achieved low estimation error between 0.5% and 1.5% for flat road conditions. In terms of reliability, the cross-correlation method shows good performance under low Signal-to-Noise Ratio (SNR) while the center-of-mass method failed in this condition. Full article

Global Navigation Satellite Systems (GNSS) are, in addition to being most widely used vehicle navigation method, becoming popular in sport-related tests. There is a lack of knowledge regarding tracking speed using GNSS, therefore the aims of this study were to examine under dynamic conditions: (1) how accurate technologically different GNSS measure speed and (2) how large is latency in speed measurements in real time applications. Five GNSSs were tested. They were fixed to a car’s roof-rack: a smart phone, a wrist watch, a handheld device, a professional system for testing vehicles and a high-end Real Time Kinematics (RTK) GNSS. The speed data were recorded and analyzed during rapid acceleration and deceleration as well as at steady speed. The study produced four main findings. Higher frequency and high quality GNSS receivers track speed at least at comparable accuracy to a vehicle speedometer. All GNSS systems measured maximum speed and movement at a constant speed well. Acceleration and deceleration have different level of error at different speeds. Low cost GNSS receivers operating at 1 Hz sampling rate had high latency (up to 2.16 s) and are not appropriate for tracking speed in real time, especially during dynamic movements. Full article