Personal Mobility Vehicle Research Articles

Attribute annotation and bias evaluation in visual datasets for autonomous driving

This paper addresses the often overlooked issue of fairness in the autonomous driving domain, particularly in vision-based perception and prediction systems, which play a pivotal role in the overall functioning of Autonomous Vehicles (AVs). We focus our analysis on biases present in some of the most commonly used visual datasets for training person and vehicle detection systems. We introduce an annotation methodology and a specialised annotation tool, both designed to annotate protected attributes of agents in visual datasets. We validate our methodology through an inter-rater agreement analysis and provide the distribution of attributes across all datasets. These include annotations for the attributes age, sex, skin tone, group, and means of transport for more than 90K people, as well as vehicle type, colour, and car type for over 50K vehicles. Generally, diversity is very low for most attributes, with some groups, such as children, wheelchair users, or personal mobility vehicle users, being extremely underrepresented in the analysed datasets. The study contributes significantly to efforts to consider fairness in the evaluation of perception and prediction systems for AVs. This paper follows reproducibility principles. The annotation tool, scripts and the annotated attributes can be accessed publicly at https://github.com/ec-jrc/humaint_annotator.

Pedestrian’s Avoidance Behavior Characteristics Against Autonomous Personal Mobility Vehicles for Smooth Avoidance

Autonomous personal mobility vehicles (PMVs), such as electric wheelchairs, are meant to drive through pedestrian spaces. Cooperative pedestrian avoidance by PMVs is necessary in these spaces to maintain smooth traffic. Previous studies suggested that PMVs can avoid pedestrians on a shorter path without compromising each other’s acceptability. This avoidance can be realized by understanding how pedestrians react to the behavior of PMVs and considering those characteristics in the autonomous navigation of PMVs. In this study, the characteristics of pedestrian’s avoidance behavior were investigated. Experiments were conducted to understand the influence of the parameters of the PMV’s avoidance behavior on pedestrians. Results showed that the angular velocity of the PMV during avoidance affects the pedestrian’s avoidance width and tolerance against the PMV’s behavior. These results suggest that it is possible to avoid pedestrians in smaller avoidance spaces by controlling the angular velocity of the PMV and maintaining smooth traffic.

Subjective Vertical Conflict Model With Visual Vertical: Predicting Motion Sickness on Autonomous Personal Mobility Vehicles

Subjective Vertical Conflict Model With Visual Vertical: Predicting Motion Sickness on Autonomous Personal Mobility Vehicles

Is Silent External Human–Machine Interface (eHMI) Enough? A Passenger-Centric Study on Effective eHMI for Autonomous Personal Mobility Vehicles in the Field

Autonomous personal mobility vehicle (APMV) is a miniaturized autonomous vehicle designed for short-distance mobility to everyone. Due to its open design, APMV’s passengers are exposed to communications between the external human-machine interface (eHMI) on APMV and pedestrians. Therefore, effective eHMI designs for APMV need to consider potential impacts of APMV-pedestrian interactions on passengers’ subjective feelings. This study from the perspective of APMV passengers discussed three eHMI designs: (1) graphical user interface (GUI)-based eHMI with text message (eHMI-T), (2) multimodal user interface (MUI)-based eHMI with neutral voice (eHMI-NV), and (3) MUI-based eHMI with affective voice (eHMI-AV). In a riding field experiment (N = 24), eHMI-T made passengers feel awkward during the “silent time” when eHMI-T conveyed information exclusively to pedestrians, not passengers. MUI-based eHMIs with voice cues showed advantages, with eHMI-NV excelling in pragmatic quality and eHMI-AV in hedonic quality. Considering passengers’ personalities and genders in APMV eHMI design is also highlighted.

Navigation System for Personal Mobility Vehicles Following a Cluster of Pedestrians in a Corridor Using Median of Candidate Vectors Observer

In recent years, personal mobility vehicles have been required to operate autonomously in places with numerous pedestrians. A navigation method using a single human-following scheme is used to avoid collision with pedestrians. However, in many cases, a single human-following method cannot be successfully used for guidance. In crowded places, pedestrians do not always keep walking in the desired direction a user wants to go, and the vehicle must change the target pedestrian frequently. Instead of following a single pedestrian, we propose a method for the vehicle to follow a cluster of pedestrians for stable and robust following. First, the pedestrians around the vehicle are detected by multiple RGB-D cameras, and the pedestrians are tracked using YOLO and Deep Sort. Pedestrians are classified according to their walking direction, and the cluster of pedestrians walking toward the goal is selected and followed. However, the position of pedestrian is sometimes lost in occlusions and the accuracy of the walking direction depends on the distance and pose detected by the sensors. A notable problem is that the cluster of pedestrians is unstable in the cluster following; therefore, a median of candidate vectors (MCV) observer is used to remove outliers caused by observation errors. The proposed method is applied to a scenario involving pedestrians walking toward an elevator hall in a building, and its effectiveness is verified through experiments.

A heterogeneous Social Force Model for Personal Mobility Vehicles on futuristic sidewalks

Electric scooters are becoming popular in public spaces, and autonomous robots will join soon. However, integrating these Personal Mobility Vehicles (PMV) without proper provisions challenges the safety and comfort of all users. While Social Force Model (SFM) commonly replicates pedestrians’ movements, directly applying it to PMVs is challenging and inaccurate. We propose a heterogeneous SFM considering the dynamic personal spaces of various agents on futuristic sidewalks, addressing the impracticalities of SFM. Additionally, subjective safety estimation relaxes the constant desired-velocity assumption, and the influence weight reduces the complexity by omitting pairwise calibration. Experiments calibrate the model for e-scooters, validating it in realistic scenarios with multiple e-scooters passing through pedestrians. The proposed model has higher accuracy than previous models regarding behavioral naturalness metrics. In addition, the models’ performance in replicating experimental observations is analyzed. This research contributes to safer and more efficient transportation with PMVs, particularly e-scooters, and provides a novel approach to modeling multi-type agents on heterogeneous sidewalks.

Feeling Your Way with Navibar: A Navigation System using Vibrotactile Feedback for Personal Mobility Vehicle Users

Navigating routes using navigation systems while using Personal Mobility Vehicles (PMVs) like bikes or scooters can lead to visual distraction in outdoor environments, creating possibilities for an accident. This article proposes a new navigation system called NaVibar for PMVs that uses vibrotactile feedback on the handlebar to enhance route information delivery and reduce visual distraction. The study aims to answer four research questions about visual distraction, route recognition, mental workload, and usability. The results of the study showed that vibrotactile feedback can be an effective and useful addition to the PMVs navigation system, reducing visual distraction, and enhancing the user experience. Also, vibrotactile feedback did not affect the participants' route recognition, but it positively affected the participants’ lower workload levels. Therefore, our study demonstrates that the addition of vibrotactile feedback could enhance the usability and safety of PMV navigation systems.

Empirical Study on the Development of Driving Environments for Personal Mobility Vehicles

Personal mobility vehicles (PMVs) are the potential future travel mode, typically for “first-mile and last-mile trips,” in urban areas. Accordingly, the popularity of PMVs is increasing, and the purpose of using PMVs is diversifying in South Korea. Before revision of the law concerning PMVs, the driving ways and roads for PMVs were not defined by regulations in South Korea. Therefore, most PMV users preferred to drive on sidewalks and bicycle lanes to avoid collisions with larger vehicles. Furthermore, PMVs have been involved in many accidents. To solve these problems, the government of South Korea revised the Road Traffic Act to permit PMVs to travel on bicycle lanes and considered building a new type of lane for PMVs based on the results of field experiments conducted in this study. In these experiments, the minimum turning radius with various speeds, driving performance on roads with vertical alignments, lateral placements in curved sections were examined. In addition, conflicts and inconvenience of PMVs driving on bicycle lanes were tested. In the experiments, three different types of PMVs—electric scooter (e-scooter), electric unicycle (e-unicycle), and segway—were used. Through the experiments, the feasibility of using PMVs on bicycle lanes was assessed, and the design criteria for PMV lanes were derived.

팟홀 검출을 통한 안전하고 지능적인 개인 이동체에 대한 연구

This paper presents the design and implementation of a personal mobility vehicle. The safe and intelligent kickboard (Sikick) is a three-wheeled kickboard that guarantees stable standing for autonomous driving by self-riding. One wheel was attached to the front and two were connected to the rear. The vehicle ensured safety by preventing two people onboard simultaneously. Sensors such as a camera and a LiDAR were used to detect potholes on the ground. Moreover, sensor processing and Sikick control were performed using ROS. For recognizing potholes on the ground, a camera and a 2D LiDAR were used. For a static case, images of potholes were learned to detect potholes on the ground. System implementation enabled it to move autonomously using RTK GPS.

Attitudinal Factors Associated with the Use of Bicycles and Electric Scooters

The use of personal mobility vehicles (PMVs) has increased, given the consumption characteristics of the population as well as the impact on the environment that other means of transport generate. In this work, the attitudinal factors associated with the use of PMVs are identified, making use of the theory of planned behaviour and a modified technological acceptance model. For the collection of information, a sample of 457 individuals was used. For the analysis of this information, a structural equation model was generated through SmartPLS 4. The results reveal that of the attitudinal factors associated with the use of these vehicles, green attitudes, perceived green value and loyalty stand out, with the latter being one of the latent predictive variables of the model, which is why feelings of enjoyment, usefulness generated and a perception of caring for the environment by PMV users have a greater influence on their loyalty to this type of green technology.

Experimental thermal characterization of the in-wheel electric motor with loop heat pipe thermal management system

Current trends in technology toward the elimination of fossil fuels are increasing the value of electric vehicles (EVs). In turn, one of the main components of EVs is an electric motor (EM). The lifetime, reliability and output power of the EMs depend on the performance of their cooling systems. The cooling systems that are based on two-phase technologies of heat transfer, such as loop heat pipes (LHPs), have important advantages over traditional air- and liquid systems. On the other hand, LHP EM thermal control application is slowed down by the complication of their manufacturing and high production expenses. However, in recent years, new technologies are constantly being developed that can reduce the customization of LHP and, therefore, the cost of its production. In this paper the technology based on modular standardized approach for LHP design and manufacturing is applied to demonstrate the cooling performance of LHP in an in-wheel motor of a personal mobility vehicle (electric bike, wheelchair etc.) and compare it to the standard cooling solution. For this purpose, a double-capillary pump unit evaporator LHP was produced and coupled with an EM. EM thermal characteristics were studied and compared to the values obtained prior to LHP installation. Studies have shown that the use of two-phase cooling can increase motor performance up to 2.5 times.

Pedestrian Avoidance Method Considering Passenger Comfort for Autonomous Personal Mobility Vehicles

During the autonomous navigation of personal mobility vehicles (PMVs) in pedestrian spaces, avoiding collisions with pedestrians walking nearby is necessary. The avoidance paths of PMVs are affected by the behaviors of the pedestrians, which may also affect passenger comfort. Herein, a local path-planning method that considers passenger comfort to realize comfortable pedestrian avoidance during the autonomous navigation of PMVs in pedestrian spaces is proposed. First, the avoidance path and pedestrian behavior parameters affecting passenger comfort are investigated by evaluating passenger comfort in scenarios with different avoidance paths and pedestrian behaviors. Next, the requirements of a pedestrian avoidance method that considers passenger comfort are set based on the parameters affecting passenger comfort. Finally, a novel path-planning method that satisfies the requirements is proposed. The method is shown to generate comfortable paths in pedestrian spaces via a numerical simulation and participant experiment.

Design Requirements for Personal Mobility Vehicle (PMV) with Inward Tilt Mechanism to Minimize Steering Disturbances Caused by Uneven Road Surface

The Personal Mobility Vehicle (PMV), which has an inward-tilting angle, turns with lateral force due to a large camber angle, so it is necessary to consider the lateral movement of the tire vertical load axis during turning. Although the steering torque mechanisms are very different from those of automobiles, there are not many studies of the steering torque mechanisms of PMVs. In this paper, based on the effects of the force of six components acting on the tires, a method for setting the steering axis specifications is derived, including the geometrical minimization of steering moment disturbance due to the vertical load reaction force during turning. Automobile tires have a significant ground camber angle when traveling on rutted roads, but they do not have it on slanted roads because the vehicle body tilts along the road surface. On the other hand, in PMVs, the vehicle body always keeps upright when traveling both on slanted roads and on rutted roads. Therefore, the tires have ground camber angles on both types of road surface. We study the straight running ability under such road surface disturbances based on the geometrical minimization of steering moment disturbance due to the vertical load reaction force during turning. This straight running ability can be a remarkable strong point of PMVs with an inward tilt mechanism. In this study, it was proved that the steering axis parameters can be derived uniquely by taking into consideration the requirement to zero the moment (disturbance) around the steering axis due to the reaction force against the vertical load at all internal tilt angles.

Exploring the effects of COVID-19 on motorcycle riding patterns and its importance.

A motorcycle refers to a two-wheeled, personal mobility vehicle used for daily transportation and leisure activities. Leisure enables social interaction, and motorcycle riding could be an activity that facilitates social interactions and distancing. Therefore, grasping the importance of riding motorcycles during the pandemic-which involved social distancing and limited leisure activities-can be valuable. However, researchers have yet to examine its potential importance during the pandemic. Therefore, this study aimed to determine the importance of personal space and time spent with others in the context of motorcycle riding during the COVID-19 pandemic. We specifically explored the effects of COVID-19 on riding patterns and importance of riding motorcycle by examining whether these factors differed regarding changes in the frequency of motorcycle riding before and during the pandemic in daily and leisure-oriented transportation. Data were collected from 1,800 motorcycle users in Japan using a web-based survey conducted in November 2021. Respondents replied to questions concerning the importance of personal space and time spent with others attributed to motorcycle riding before and during the pandemic. Following the survey, we conducted a two-way repeated measures analysis of variance (two-factor ANOVA) and performed a simple main effect analysis using the SPSS syntax editor in case of interactions. The valid samples for motorcyclists with leisure motive (leisure-oriented users) and daily transportation motive (daily users) numbered n = 890 and n = 870, respectively (total n = 1,760, 95.5%). Each valid sample was divided into three groups based on the differences in motorcycle riding frequency before and during the pandemic: unchanged, increased frequency, and decreased frequency. The two-factor ANOVA results showed significant differences in the interaction effects for leisure-oriented and daily users regarding personal space and time spent with others. The mean value of the "increased frequency" group during the pandemic indicated significantly higher importance of personal space and time spent with others than the other groups. Motorcycle riding could enable daily transportation and leisure-oriented users to practice social distancing while simultaneously spending time with companions and alleviating loneliness and isolation during the pandemic.

Live Field Validation of an Islanded Microgrid Based on Renewables and Electric Vehicles

This paper presents a live field experience of creating an isolated microgrid for the Expoelectric fair during 2018 and 2019. The islanded microgrid comprises a Master Inverter with grid-forming capabilities and fault management. The Master Inverter and stationary batteries, and EVs with V2G capabilities provide storage. A PV generation system supplies the microgrid. The loads are the fair booths, mainly lighting and chargers for personal mobility vehicles. All the equipment used in the experimental microgrid is from different manufacturers. The operation and control of the islanded microgrid are based on the VDE-AR-N-4105 standard. The paper also presents the operation of the Master Inverter during faults. The live field experience shows that the proposed operation method is valid for operating different converters from different manufacturers without needing any communication layer between them. The experimental results also show that faults can be handled correctly by the Master Inverter to operate the entire microgrid safely. In conclusion, islanded microgrids based on power electronics are feasible to replace diesel generators in faires, conventions or temporary events.

Influence of Running Position in Lane on Automatic Collision Avoidance in Personal Mobility Vehicle

Influence of Running Position in Lane on Automatic Collision Avoidance in Personal Mobility Vehicle

A Study of Suspension Geometry for Personal Mobility Vehicles (PMVs) with Inward Tilt Mechanism

A Study of Suspension Geometry for Personal Mobility Vehicles (PMVs) with Inward Tilt Mechanism

Differences in Driver Behavior between Manual and Automatic Turning of an Inverted Pendulum Vehicle

Personal mobility vehicles (PMVs) are compact and lightweight compared to automobiles; hence, human dynamic behavior affects a vehicle's postural stability. In this study, the dynamic behaviors of drivers of inverted pendulum vehicles (IPV) under manual and automatic driving were investigated. One particular feature of applying automatic driving to IPV is constant posture stabilization control. In this study, the drivers' center of gravity (COG)/center of foot pressure position (COP) and joint moments during turning were investigated experimentally. It was found that the drivers' COG shifted backward during turning and deceleration. For COP, it was found that drivers maintained balance by moving their inner foot more inward and their outer foot more outward during turning. These results are significant for understanding the steps taken to withstand centrifugal forces during turning. The joint moments of the foot were more significant in automatic turning than in manual turning to prevent falling owing to centrifugal force. These findings can facilitate the development of an automatic control method that shifts the COG of a driver, as in manual turning.

Proposing a model of centralized control system on personal mobility vehicles

Proposing a model of centralized control system on personal mobility vehicles

Implementation of a Low-Cost Data Acquisition System on an E-Scooter for Micromobility Research.

In recent years, cities are experiencing changes in the ways of moving around, increasing the use of micromobility vehicles. Bicycles are the most widespread transport mode and, therefore, cyclists' behaviour, safety, and comfort have been widely studied. However, the use of other personal mobility vehicles is increasing, especially e-scooters, and related studies are scarce. This paper proposes a low-cost open-source data acquisition system to be installed on an e-scooter. This system is based on Raspberry Pi and allows collecting speed, acceleration, and position of the e-scooter, the lateral clearance during meeting and overtaking manoeuvres, and the vibrations experienced by the micromobility users when riding on a bike lane. The system has been evaluated and tested on a bike lane segment to ensure the accuracy and reliability of the collected data. As a result, the use of the proposed system allows highway engineers and urban mobility planners to analyse the behaviour, safety, and comfort of the users of e-scooters. Additionally, the system can be easily adapted to another micromobility vehicle and used to assess pavement condition and micromobility users' riding comfort on a cycling network when the budget is limited.