# Comparison of bend-taking on combustion engine and electric motorcycles: qualitative studies

Clémentine Pignat, Pauline Michel, Bruno Larnaudie, Bastien Vincke, Sergio

Alberto Rodriguez Florez, Abdelhafid Elouardi, Flavien Delgehier, Franck

Mars, Stéphane Espié, Abderrahmane Boubezoul

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Clémentine Pignat, Pauline Michel, Bruno Larnaudie, Bastien Vincke, Sergio Alberto Rodriguez Florez, et al.. Comparison of bend-taking on combustion engine and electric motorcycles: qualitative studies. 15th International Motorcycle Conference (IMC 2024), Dec 2024, Köln, Germany. pp.153-165. hal-04831595v3

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<figure><img src="image_2.png" /></figure>
# Comparison of bend-taking on combustion engine and electric motorcycles: qualitative studies

Clémentine PIGNAT*,<fnref n="1" />,<fnref n="3" />, Pauline MICHEL<fnref n="2" />, Bruno LARNAUDIE<fnref n="2" />, Bastien VINCKE<fnref n="2" />, Sergio RODRIGUEZ<fnref n="2" />, Abdelhafid EL OUARDI<fnref n="2" />, Flavien DELGEHIER<fnref n="2" />, Franck MARS<fnref n="3" />, Stéphane ESPIÉ<fnref n="1" />, and Abderrahmane BOUBEZOUL<fnref n="1" />

Thursday 5th December, 2024

## Abstract

Riders of powered two-wheelers are overrepresented in road accidents. With growing environmental concerns, the number of electric vehicles on the road, including electric motorcycles, is expected to increase. However, electric motorcycles have distinct characteristics, notably the absence of a gearbox, as well as engines without sound, vibrations, and inertia. The "electric" rider would have fewer sensory cues available to them and this could put them in danger. This raises the question of the transition from the combustion engine motorcycle to the electric motorcycle. To explore this issue, two preliminary studies were conducted as part of the eMC2 ANR research project: "Electric Motorcycles and Road Safety". Both experienced and novice electric motorcycle riders participated in tests using instrumented electric and combustion engine motorcycles, providing a substantial dataset for analyzing riding behaviors. This dataset was further complemented by subjective measures, particularly on mental workload. The results show a fairly rapid adaptation to the electric motorcycle for most of the participants. They also show an increase in mental workload when novices are riding an electric motorcycle. Novices reported being more disturbed by differences in sensory cues between combustion engine and electric motorcycles than experienced riders. While this trend requires further investigation with non-professional riders, it highlights the potential need for awareness raising campaigns or even targeted training programs to facilitate the transition from combustion engine to electric motorcycles.

**Keywords** — motorcycle riding behavior, motorcycle riders, bend-taking, adaptation to electric motorcycles, specificities of electric motorcycles

<footnote n="1">¹Université Gustave Eiffel, SATIE, 91190, Gif-sur-Yvette</footnote>

<footnote n="2">²Université Paris-Saclay, ENS Paris-Saclay, CNRS, SATIE, 91190, Gif-sur-Yvette</footnote>

<footnote n="3">³Nantes Université, CNRS, LS2N, 44322, Nantes</footnote>

<footnote>*Corresponding author : clementine.pignat@univ-eiffel.fr</footnote>
# 1 Introduction

Powered two-wheeler (PTW) riders are overrepresented in road accidents. In France, although PTW riders account for less than 2% of traffic, they represent 22% of fatalities and 34% of serious injuries (ONISR, 2024). Due to environmental concerns and the announced ban on the sale of combustion engine vehicles in the European Union from 2035, the number of electric vehicles (EVs), and particularly, of electric motorcycles (EMs), is set to increase in road traffic. However, EVs have specific features regarding dynamics and sensory feedback, which influence vehicle control. This raises the question of the transition from combustion engine to electric vehicles and the necessity for drivers to adjust how they control their vehicles, which could be problematic, especially for experienced drivers of combustion engine vehicles.

Difficulties drivers and riders encounter when transitioning to EVs could be linked to changes in environmental information gathering, leading to changes in driving behavior. Indeed, the differences between combustion engine and electric vehicles are numerous. EVs are silent, generally have no gearbox, little vibration, and have different dynamics due to high engine torque from the first seconds of acceleration (Toman et al., 2021). The dynamics of EVs could be problematic during re-acceleration out of bends, with the risk of losing grip.

The absence of engine noise also raises questions since studies have shown that when car drivers were entirely deprived of auditory feedback, their perceived driving speed was lower than their actual speed (Evans, 1970; Merat & Jamson, 2011). When drivers were partially deprived of auditory feedback, their driving speed increased (Horswill & Plooy, 2008; Knowles et al., 2012). Another study showed that when an auditory feedback was available to the driver, they perceived their speed as higher than it was (Bringoux et al., 2017). In simple terms, speed is perceived by the driver according to a combination of sensory cues: visual information from the optic flow, vestibular information induced by the dynamics of the vehicle, and auditory information, resulting mainly from the engine and airflow in the case of motorcycles. This information is further supplemented by perceived vibrations (such as road contact and engine vibrations). For vehicles with manual gearboxes, knowing the engaged gear provides additional information.

Because of the silence of the vehicle, the absence of engine vibrations, and the lack of gearbox, the “electric” rider would have fewer sensory cues available to them. During the transition from combustion engine motorcycles (CMs) to EMs, control difficulties could arise, putting the rider in danger (for example, over-speeding when approaching a bend).

The eMC2¹ project, which the studies presented in this article are part of, examines the safety implications of switching from CMs to EMs. The project focuses on two main concerns: on one hand, the differences in riding characteristics, i.e. of vehicle dynamics, between CMs and EMs, and on the other hand, the differences in sensory cues available to riders, and aims to measure and analyze the impact of these differences on motorcycle users’ riding behaviors. We place particular emphasis on the need for appropriate measures to ensure road safety during the transition from CMs to EMs for experienced CM riders. For this reason, we are par-

<footnote n="1">¹https://anr.hal.science/search/index/?q=*&anrProjectReference_s=ANR-22-CE22-0012</footnote>
ticularly interested in the adaptation or learning phase of an EM (as a new vehicle for experienced CM riders), and in riding behaviors observed during this phase.

Some studies have been carried out on the adaptation from combustion engine to electric vehicles, though most focused on car drivers. It was pointed out that drivers, after a learning process, adapted to the specificities of electric vehicles. Among other things, studies have shown that drivers learn to master the regenerative braking of EVs and use it when it is needed and/or beneficial (Helmbrecht et al., 2014; Knowles et al., 2012; Vilimek et al., 2012). For in-depth analysis of the adaptation/learning phase and driving behaviors during this phase, several types of data could be used, but these ideas have not often been employed in studies focused on motorcycle riders: riding time, amount of braking actions, timing of braking and acceleration, steering activity (steering angle and steering jerk), etc. (Freydier, 2014; Negi et al., 2019).

The two exploratory studies presented in this article aimed to investigate the differences in riding behavior between CMs and EMs. The first study compared the riding behaviors of novice EM riders with those of relatively experienced EM riders to assess potential adaptation effects. The second study focused on how experienced CM riders adjusted their behavior when riding an EM for the first time. This second study was designed to identify potential transitional difficulties that may arise during the initial discovery of EM riding.

# 2 Method

## 2.1 Qualitative study 1

### 2.1.1 Participants

Four men participated in the study, with an average age of 48.8 years (SD = 7.7). These participants were riding professionals and instructors recruited by their hierarchy, and each rider signed a consent form. Two participants were novices in EM riding (having never ridden an electric motorcycle), while the other two were relatively experienced in EM riding. All four participants also regularly rode CMs, with an annual mean distance of 26000 km.

### 2.1.2 Apparatus

All participants rode on the La Ferté-Gaucher race track in the Île-de-France region of France. Only one part of the race track was used for the study, which measured two kilometers for a lap (Figure 1).

The two motorcycles used were: a combustion engine sport motorcycle (RSV4, Aprilia, subsequently designated as CM1) and an electric roadster motorcycle (SR/F 2020, Zero Motorcycles, subsequently designated as EM). The CM1 was chosen because its maximum torque was close to the torque of the EM (122 Nm and 190 Nm respectively).

All motorcycles ridden by the participants were instrumented specifically for the needs of these experiments, based on the instrumentation work carried out in a previous research project (Smaiah et al., 2018). Based on the extensive motorcycle
instrumentation developed for this project, we are able to select the sensors needed to investigate a specific research question (Vincke et al., 2024).

The analysis detailed in this paper relies on the data measured by a GoPro 360° camera placed on the right side mirror of the motorcycles. The data (GPS location and cinematic data) was collected at a frequency of 10 Hz.

<figure><img src="image_3.png" /><figcaption>**Figure 1:** Aerial photography (Google Earth) of the La Ferté-Gaucher race track used in the two studies, with distance scale.</figcaption></figure>

### 2.1.3 Design

The mixed factorial experimental design was composed of a between-participants factor, "level of electric motorcycle-riding experience", and two within-participants factors: "motorization" and "riding style", for a total of six conditions (2*3). The two modes of the "motorization" factor were "combustion engine motorization" represented by the CM1 and "electric motorization" represented by the EM. The three modes of the "riding style" factor were "free riding", where riders were told to ride as they usually would in their daily life, "smooth riding", where participants had to minimize acceleration and braking and ride without trying to perform, and finally "dynamic riding" where they had to adopt active, sporty, and energetic riding. The two modes of the "level of electric motorcycle-riding experience" were "novice to EMs" and "confirmed EM riders". The first mode was always in free riding to allow participants to discover the race track at their own rhythm. The order of presentation of the "smooth" and "dynamic" riding conditions was counterbalanced. The "motorization" factor was not counterbalanced since the focus of the study was the transition from CM to EM.

### 2.1.4 Data collection / Measures

To limit the overall duration of the experimentation, questionnaires and interviews (psychological data) were conducted only when the participants had completed the
riding with one type of motorization. There were two phases of interviews: one after the CM riding period and one after the EM riding period. The psychological dependent variables were submitted to a two-modality factor (combustion engine motorization and electric motorization). All other data was retrieved for all experimental conditions. Given the small sample of riders, only descriptive statistics were produced and are detailed and analyzed in the following.

Psychological data: participants completed a French version of the NASA-TLX questionnaire, which allows a subjective assessment of workload (Cegarra & Morgado, 2009; Hart & Staveland, 1988). They also completed three other questionnaires designed by the experimenters, namely on the difficulty of the bends or on perceived differences between the two ridden motorcycles. Open-ended semi-directive interviews were also conducted (for example<fnref n="2" />: "Did you find it was easy to apprehend, estimate and manage your straight-line speed?"; "Did you have any difficulty measuring your acceleration and/or braking?"; "Did you find differences between these two vehicles? If so, which ones?").

Vehicle data: The vehicles were equipped with a GoPro 360° camera, which was used to obtain data such as GPS location, speed, longitudinal and lateral acceleration, etc.

Training data: These data were calculated from vehicle data. Learning to drive a vehicle can be reflected by observing the evolution of variables. Here, we chose to focus on the evolution of the time spent completing a series of bends. For this purpose, a 950-meter section of the circuit was selected: the zone chosen was in the center of the circuit to avoid the influence of starting and braking during stands starts and returns (Figure 2).

<figure><img src="image_4.png" /><figcaption>**Figure 2:** Trajectories for one condition and for one participant (blue line) with the analyzed trajectory section highlighted (red rectangle).</figcaption></figure>

### 2.1.5 Procedure

The entire first block of the study was carried out in CM1. They were asked to adopt a “free riding” mode, in other words, they could ride the vehicle as they wished, the aim being to discover the circuit over three laps. They made a stands stop where the experimenter gave instructions for the next laps. They rode three laps in the

<footnote n="2">²All examples of questions asked are translated from French for the benefit of the reader of this paper.</footnote>
requested condition (smooth or dynamic riding), made a second stands stop and set off again for three laps in the other riding condition. Then, they left the CM1 in the stands, completed questionnaires and had an interview with an experimenter about the riding they had just done. The second block took place in the same way as the first, except that the participants rode the EM. Once the ride was over, participants left the vehicle at the stands, completed the same questionnaires and had an interview with the same questions, this time about the EM. In a final debriefing interview, participants were asked about the differences they had perceived between the two motorcycles they had ridden, followed by open discussions about riding the motorcycles.

## 2.2 Qualitative study 2

### 2.2.1 Participants

New participants were recruited in the same way than the first study and each rider signed the consent form. Four men took part in the study and had an average age of 46.8 years (SD = 6.7). All participants were novice to EM riding. These four participants also regularly rode CMs (annual mean = 21000 km).

### 2.2.2 Apparatus

Participants rode motorcycles on the race track previously shown. For this study, modifications were made to help riders consider the circuit as a two-way road. To induce bend-taking equivalent to that on an open road, cups were added to the circuit to mimic the center line separating the two lanes. The two motorcycles used were a combustion engine roadster motorcycle (ER6, Kawasaki, subsequently designated as CM2) and the EM. This change has been carried out so that the motorcycle types could be more comparable in terms of the type of vehicle driven and riding posture than in terms of maximum engine torque (see 4 section).

All motorcycles ridden by the participants were instrumented specifically for the needs of these experiments, based on the instrumentation work carried out in a previous research project (Smaiah et al., 2018). Based on the extensive motorcycle instrumentation developed for this project, we are able to select the sensors needed to investigate a specific research question (Vincke et al., 2024). The analysis detailed in this paper relies on the data measured by a GoPro 360° camera placed on the right side mirror of the motorcycles. The data (GPS location and cinematic data) was collected at a frequency of 10 Hz.

### 2.2.3 Design

The experimental design was composed of two within-participants factors with two modalities: the "motorization" factor and the "riding style" factor, for a total of four conditions (2*2). The two modes of the "motorization" factor were "combustion engine motorization" represented by the CM2 and "electric motorization" represented by the EM. The two modes of the "riding style" factor were "smooth riding" and "dynamic riding". The participants were always instructed to ride "smoothly" first for each motorcycle and they always started by riding the CM2. This is because the focus of this study was the transition from CM to EM.
### 2.2.4 Data collections / Measures

The dependent variables were the same as in the first study.

### 2.2.5 Procedure

The procedure was relatively similar. Participants were introduced to the track (three laps) on their own motorcycles used daily in their work (subsequently designated as control motorcycle). Then, participants parked their motorcycles and went into the interview room to answer various questionnaires. In block one, participants rode the CM2 (three laps in smooth riding, then three laps in dynamic riding), then went to answer the questionnaires. Block two took place in the same way, but with the EM. The study ended with a debriefing interview.

## 3 Results of the studies

Although the dependent variables were similar in both studies, it was not possible to mutualize their results due to changes in protocol. They are to be considered and discussed separately.

### 3.1 Learning

The results show few inter-individual differences in terms of lap times between the participants, whereas there are no real differences between EM and the CMs (CM1 and CM2): the lap times are relatively similar (Figure 3). The main trend is that time per lap decreases with each lap. Some riders show a decrease in time from lap 1 to lap 2 and an increase for lap 3 (S3-CM, S4-EM and S8-CM-EM). S6 has bucked the trend, increasing his time with each lap when riding the EM. The best time (i.e. shorter time) is obtained by S1-EM (mean = 40.4 s).

<figure><img src="image_5.png" /><figcaption>**Figure 3:** Evolution of lap time (in seconds) in the selected part of the race track, for the “dynamic riding” mode, per motorcycle and per subject for the two studies. S = subject.</figcaption></figure>
## 3.2 Semi-directive interview

After the session of EM riding, in the first study, to the question “*Did you find it easy to capture, estimate and manage your straight-line speed?*”, one participant replied: “*Yes because I have already ridden the electric motorcycle. [...] The electric it goes less fast at the end of the straight line than the combustion engine one when accelerating in the dynamic riding condition. [...] There is a 30 or 40 km/h gap at the end of the straight line. [...] I looked at the meter at one point and saw 170 km/h. [...] And with RSV4, I think in perception of things, 190-200 km/h, or even more.*”<fnref n="3" />. Actual speeds were calculated from recorded data and compared with the perceived and observed (i.e. read on the speedometer) speeds by this participant. The maximum speed reached by this subject with the EM was 176 km/h and that reached with the CM1 was 182 km/h, a deviation of 6 km/h.

## 3.3 Workload

A comparison of the workload associated with riding the motorcycles was carried out for the second study. The workload when riding the EM is rated higher by participants than when riding the CM2 (Figure 4.A). The lowest workload is associated with their usual motorcycle (mean = 7.0; SE = 0.4) followed by that associated with the CM2 (mean = 7.2; SE = 0.8) followed by that of the EM (mean = 8.7; SE = 1.6). Details of each item are shown in Figure 4.B. The results show that the EM almost systematically generated a higher workload than the CM2 and the control motorcycle (mental activity, physical activity, time pressure, effort and frustration). The greatest differences between EM and CM2 are found for physical pressure, effort, frustration (Δ = 9%) and time pressure (Δ = 7%).

<figure><img src="image_6.png" /><figcaption>**Figure 4:** A. NASA-TLX mean score (and standard error) as a function of the motorcycle ridden for study two. B. Mean score obtained for each item (and standard error) of the NASA-TLX as a function of the motorcycle ridden for study two.</figcaption></figure>

<footnote n="3">³All comments made by the participants during the interviews were translated from French for the benefit of the reader of this paper.</footnote>
## 3.4 Perceived disturbance

These results come from the questionnaire completed by the participants at the end of the first study (Figure 5). They were asked whether they thought the difference in the item in question (e.g. auditory feedback) had affected their riding. For all items, the trends show that motorcyclists who had already ridden an EM found that the differences between the EM and the CM1 posed few riding difficulties, unlike novices. For example, for the auditory feedback change, experienced riders were not disturbed, unlike novices ($\Delta = 63.7\%$).

<figure><img src="image_7.png" /><figcaption>**Figure 5:** Average level (and standard error) of riding disturbance for professionals as a function of the level of expertise in EM riding. Auditory = engine noise, behavior = vehicle behavior, dynamics = vehicle dynamics, gearbox = presence of gearbox, trajectories and vibrations = engine vibrations.</figcaption></figure>

# 4 Discussion

## 4.1 Learning

Riders are adapted similarly to the different types of motorization, with trends indicating an improvement in lap times for each. These improvements suggest that professional riders can quickly adapt to EMs. This conclusion is supported by the lap times of S1, the most experienced electric motorcycle rider. Indeed, he performed best when driving the EM, showing how well he adapted to electric motorization over time. Experienced electric motorcycle riders rode the EM faster than novices, with a 3.1 s lower lap time. These results are in line with the literature, since motorcyclists who had already ridden an EM showed better performance (Negi et al., 2019).

## 4.2 Semi-directive interview

One participant commented on speed perception while riding in a straight line. He perceived a speed difference of over 30 km/h, whereas the actual difference was only 6 km/h. In other words, his perceived speed was lower than his actual speed when riding the EM. This misperception of speed aligns with findings in the literature. For instance, the study by (Bringoux et al., 2017) conducted on a car-driving simulator suggested that perceived speed was higher than the actual speed when
auditory feedback was present. This observation raises an important road safety concern, as riders may be prone to underestimating their speed when riding an EM if they do not frequently check their speedometer. Conversely, they might need to check their speedometer more often, which could reduce their attention to the road and potentially increase the risk of accidents.

During discussions, several participants reported that the EM was more challenging to control when approaching bends due to an underestimation of perceived speed. However, they also noted that the absence of a gearbox on EMs facilitated motorcycle handling within bends. For example, if the rider arrived too fast in a bend, it would be easier for him to slow down with an EM: "there's no gearshift, so we don't waste time clutching, declutching, looking for the selector, etc."³ and also "we don't have any jerks with the electric when we go back on the throttle."³. Not all EM novices had the same experience, some were "more confident in corners or on the go-around because it's easier"³, but one of these riders slipped in a corner because he accelerated too hard and "took the throttle back too soon"³.

## 4.3 Workload

It is widely accepted that workload is influenced by task complexity, attentional resources, expertise, and other factors. In this study, only the workload attributed to the riding task in the second experiment was analyzed. The CM1 was considered too exclusive, requiring significant concentration from participants, which introduced a bias related to motorcycle type (sport vs. roadster). This bias was corrected in the second study, where both CM2 and EM were roadsters. It was hypothesized that workload would increase when riding the EM, likely due to riders' unfamiliarity with this type of vehicle. The results support this hypothesis, showing that the lowest workload is associated with participants' professional motorcycles and is nearly identical to that of the CM2, which share characteristics with their usual motorcycles. In contrast, the EM induces a 7% higher mental workload.

## 4.4 Perceived disturbance

The results indicate that motorcyclists with prior experience riding an EM are less affected by the change in motorization compared to novices. This reduced disturbance was expected, as these riders had already adapted to the characteristics of electric motorization. However, all motorcyclists concurred on one aspect of vehicle dynamics: it was consistently reported that the absence of a gearbox and clutch in the EM would make it easier for beginners to handle.

## 4.5 In-depth data analysis

The extensive instrumentation available for this project has allowed for the collection of additional data that have not yet been analyzed due to time constraints but will be presented at the conference. These data will facilitate a more detailed analysis of the transition from CM to EM. Specifically, they include parameters such as steering angle and motorcycle roll angle, which could contribute to a better understanding of adaptation to this new motorization. Previous research has demonstrated that expert car drivers exhibit higher steering activity (e.g., greater steering wheel angle and steering jerk), while novice drivers experience greater difficulty in regulating
vehicle speed and perform a higher number of braking actions (Freydier, 2014; Negi et al., 2019).

# 5 Limits and prospects

A key limitation in generalizing these results is the high level of expertise of the participants, who are professional riders and instructors. We hypothesize that their daily and professional experience in motorcycle riding allowed them to adapt rapidly to the change in motorization, likely reducing the observed effects. Additionally, the study was conducted on a racetrack, where riding conditions are simplified: full visibility of the environment, absence of traffic, and no interaction with other vehicles or road users. Furthermore, the track's sinuosity restricted the use of the motorcycles' full performance capabilities. These factors could limit the effect of motorization on riding performance.

Another limitation concerns the sample size, as the number of participants was low, and each experimental condition was limited to three laps. This restriction was imposed by the limited battery autonomy of the EM under dynamic conditions and the relatively long recharging time. Lastly, the initial selection of motorcycles (CM1 and EM) aimed to match engine torque; however, this resulted in significant differences in motorcycle type and rideability. To isolate the effects of electric power from those of motorcycle type, the sport motorcycle (CM1) was subsequently replaced with a roadster model (CM2).

As part of the eMC2 project, longitudinal and naturalistic studies have been conducted to investigate the adaptation of riders from CM to EM in the general population.

# 6 Conclusion

These initial findings support the hypothesis that riders adapt their behavior when transitioning from a combustion engine motorcycle to an electric motorcycle due to the specific characteristics of electric motorization. The results also indicate an increase in workload when participants switch to riding an electric motorcycle. On the road, with non-professional riders, the workload increase could be even more pronounced, potentially raising safety concerns.

This observed trend, which requires confirmation through further studies involving non-professional riders, suggests the need for awareness raising and even specialized training to facilitate this transition. Some of these future studies will be conducted using our riding simulator. Ultimately, all planned investigations share a common objective: to further explore the transition from CM to EM and to identify potential road safety issues.

# 7 Acknowledgment

This research was funded in whole by the Agence Nationale de la Recherche (ANR, France national research agency) for the ANR-22-CE22-0012 project, eMC2: "Electric Motorcycles and Road Safety".
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