HCI in Mobility, Transport, and Automotive Systems

Driving automation systems are capable of continuously performing part or all of the dynamic driving task. Driving automation is intended to reduce the probability and severity of traffic crashes by minimizing manual operation. However, inadequate automation systems (including advanced driver assistance systems mounted on Level 2 vehicles and automated driving systems mounted on Level 3 or higher levels vehicles) and inappropriate human-automation interaction will threaten road safety. This study analyzed the factors of crashes related to driving automation from the perspective of human factor risks. We summarized the crashes and categorized the probable causes mentioned in six accident reports from National Transportation Safety Board. We extracted common causal factors related to human drivers, including inappropriate using ways of driving automation, human distraction or disengagement, and complacency (overreliance) on vehicle automation. Finally, we discussed the relationship between the extracted common causes and previous insights in the driving automation domain, such as the rationality of complacency as a causal factor, and provided potential countermeasures.

Speeding is the primary cause of traffic accidents. To improve road safety, the European Union started implementing a new regulation mandating that all new vehicles coming to the EU market must be equipped with an Intelligent Speed Assistance (ISA) system from 2022 onwards. However, the rule did not include existing vehicles on the roads. Our research aims to fulfill this gap by investigating user experiences and acceptance with a retrofit system developed by V-tron, a Dutch company. Seven participants signed up for our study and our technicians installed the ISA system on their cars. They then used the car for more than one month and reported their experiences weekly. We also recruited a driving school and conducted a focus group with five instructors. Using interview and questionnaire methods to collect their first-person experiences, we saw that all participants acknowledged the vision and potential of ISA systems in reducing speeding and improving traffic safety. While the retrofit system is easy to use, the technology needs to be improved in accuracy and robustness. The overruling mechanism also needs to minimize the latency and consider secondary users unfamiliar with the speed control. Three design concepts were proposed to improve user experiences and eventually promote the adaptation of ISA systems.

Recent developments of advanced Human-Vehicle Interactions rely on Internet-of-Vehicles (IoV), to achieve large-scale communications and synchronizations of data in practice. IoV is highly similar to a distributed system, where each vehicle is considered as a node and all nodes are grouped with a centralized server. In this manner, concerns of data privacy are rising, since privacy leak possibly occurs when all vehicles collect, process and share personal statistics (e.g. driver’s heart rate, skin conductance and etc.). Therefore, it’s important to understand how to efficiently apply modern privacy-preserving techniques on IoV. In this work, we first present a comprehensive study to characterize modern privacy-preserving techniques for IoV, and then propose a Differential Privacy(DP) privacy-protection framework specialized for unique characteristics of IoV. Our characterization focuses on DP, a representative set of mathematically-guaranteed mechanisms for both privacy-preserving processing and sharing of sensitive data. It demystifies the tradeoffs of deploying DP techniques, in terms of service quality and privacy-preserving effects. The lessons learned from characterization reveal the importance of data utility in DP-protected IoV and motivate us to examine new opportunities. To better balance tradeoffs and improve service quality, we introduce HUT, for high-utility, batched queries under DP-protection on IoV. We quantitatively examine the benefits of HUT, and experimentally show that, in an IoV context, HUT can reduce information loss by 95.69% while enabling strong mathematically-guaranteed protection over sensitive data. Based on our characterization and optimizations, we identify key challenges and opportunities for future studies, to enable privacy-preserving IoV with low service quality degradation.

Hub-to-hub transport will be one of the first use cases for automated driving in the transportation industry. As current in-hub processes are based on a driver being present, it is important to investigate how automated trucks are to be integrated in future in-hub processes when they arrive driverless. Following on from previous research, the in-hub tasks that will still have to be carried out manually in and around the truck were identified. By conducting individual workshops with seven experts of the logistics industry, four different processes were developed for the integration of automated trucks in future in-hub processes. The results show that hub personnel will still be needed for all of the processes. The processes developed differ in that they either include a trailer exchange or truck and trailer are not separated. The respective future roles and responsibilities are described for each process, and the necessary prerequisites and possible problems are discussed.

Autonomous vehicles (AV) are predicted to change our current transportation system, however, how and when they become fully adopted is still an uncertain matter. One essential aspect to consider is how people form trust towards AV. In the context of AV, trust in technology is critical for safety considerations. Although humans are capable of making instinctive assessments of the trustworthiness of other people, this ability does not directly translate to technological systems. The rising complexity of autonomous systems (AS) (e.g., cruise control) requires the operators to calibrate their trust in the system to achieve their safety and performance goals. As such, a detailed understanding of how trust develops, and especially the underlying mental processes, will facilitate the prediction of how trust levels influence behavior mode and decision-making strategies when interacting with AV. To investigate this in the context of AV, we conducted interviews and follow-up surveys to examine users’ current behavior with an analogous system (cruise control) and explored its relationship with the perception of AV trustworthiness. Our findings suggest that external factors play a role in the adoption of cruise control (an analogous system), while internal factors determine non-adoption. Trustworthiness in AV is affected by external factors, users’ trust in others, and their knowledge of advanced vehicle technology.

Research shows that drivers rarely consult the vehicle owner’s manual to learn to operate advanced safety features, like Adaptive Cruise Control (ACC). Students from a United States university participated in a national competition, called EcoCAR Mobility Challenge (sponsored by the Department of Energy), to develop an engaging solution that is efficient and effective in educating drivers about the operation of ACC while adhering to user-centered design methodology. Students used an iterative design process and collected quantitative and qualitative data to evaluate the strengths and weaknesses of a mobile application. Iterations of the prototype included an interactive guide, video components, remote connection to the vehicle, and ultimately a solution that could reside on the vehicle’s infotainment system. This paper details the process and evaluation outcomes and serves as a model for user-centered design of tutorials for Advanced Driver Assistance Systems (ADAS).

We investigated the effect of varying the level of cooperation in a smart charging agent (SCA) on user perception and behavior. Our study involved manipulating the SCA’s cooperativeness by varying its degree of automation and the amount of information sharing with the user and measuring effects on changes in user behavior, perceived goal alignment, the user’s awareness of the SCA’s information processing, and perceived cooperativeness. Our hypothesis that a lower degree of automation of the SCA would increase human-agent cooperation was not supported by our results. Instead, participants in the high-automation condition chose a later charging endpoint more often, implying greater cooperation. Our hypothesis that a higher amount of information shared by the SCA would increase human-agent cooperation was only partially confirmed. Cooperation led to a more positive user experience, but the correlation was only moderate to strong. The study shows the limitations of using the degree of automation as a sole measure of human-machine cooperation and highlights the need to explore other operationalizations of human-machine cooperation. Further research is needed to explore other scenarios and variations in the information provided to the user to better understand human-machine cooperation in the context of smart charging.

Intelligent agents (IAs) are increasingly used in vehicles and associated services (e.g. navigation, entertainment) to enhance user experience, as IAs were applied to the car and turned the vehicle into a service platform under the rapid development of the intellectualized and connected vehicle. However, various IAs may be employed by other services and devices. In the case of in-vehicle cross-device interaction, when users interact simultaneously with multiple services or devices, the actions and decisions of one IA may conflict with those of others. This paper presents a role-based relationship framework to resolve potential conflicts between different IAs in the driving scenarios. The article discusses four types of IA relationships: Partnership, Representative, Subordinate, and Co-embodiment. To examine people's perceptions and attitudes towards different types of relationships, we apply an evaluation system and conduct user studies (N = 30). In two scenarios (Navigation Plan & Music Switching), Participants are required to engage in conversations with IAs based on various types of relationships. Data analysis and user interviews show that Partnership is gaining popularity in leisure and entertainment settings. Moreover, Representative is more effective in efficiency-oriented use cases. In addition, the research on driver's attention behavior suggests that Representatives can convince the driver to focus on the road more efficiently in navigation scenarios than in music settings. After evaluating the different role-based relationships of IAs, design recommendations for user interactions with multiple IAs in driving scenarios are offered.

Dangerous driver behavior can arise from different factors: distraction, sleepiness, and emotional states like anger, anxiety, boredom, or happiness. The Driver Monitoring Systems (DMS) collect data on driver behavior and emotional states, which can help design safer driving systems. Human-machine interfaces (HMIs) can leverage the detection of altered states and foster a safe driving style. To this end, we presents two visual HMI prototypes designed to assist drivers in countering distraction conditions and emotional states of too high or too low activation. The HMI prototypes combine voice assistance, ambient lighting, and visual displays. The HMI visual strategies are designed to indicate the dangerous conditions to the driver and to provide the driver with additional information about the type of dangerous state detected. This work provides details on the design and of the methodology applied to evaluate the two HMI prototypes and presents the results of a user assessment with 26 participants, showing insights into user attitudes and helping to identify future design directions.

With the outburst of the intelligent vehicle market, vehicle Virtual Personal Assistant (VPA), as an important interactive interface of drivers and smart vehicles, will be more and more common in our daily life. Since VPA is the carrier of Voice User Interaction, previous VPA research topics mainly focus on the field of voice interaction and personification, such as personification, emotionalization, gender cognition preference, and role cognition preference. However, there is a growing demand to comprehensively evaluate vehicle VPA experience, concentrating on the vehicle application field. In this study, we constructed a vehicle VPA experience evaluation model and verified its validity and reliability.

There are 3 phases included in this study: (a) First of all, through interviews with 20 real users, we extracted users' perception elements of vehicle VPA, summarized the factors affecting the experience of vehicle VPA, and converted them into the initial dimensions of the evaluation model, included Sensory Comfort, Depth Assistance, Natural Interaction, Pleasant Emotions 4 modules. (b)Secondly, we invited 10 vehicle VPA designers to discuss and adjust the model based on professionals suggestions. (c) Thirdly, to verify the adjusted model, 364 vehicle VPA users (including NIO(ET/ES/EC), XPENG(P5/P7), Li One, Lynk&Co 09) were invited to participate in an online questionnaire. Reliability analysis, validity analysis, and factor analysis are carried out to confirm the quality of the questionnaire and to complete the structural adjustment of the model. The final output of the vehicle VPA evaluation model included 5 first-level indicators, 7 s-level indicators, and 45 third-level indicators. First-level indicators include Sensory, Resource, Interaction, Emotion, Design modules. Among third-level indicators, high influence (weight) ones are Voice of VPA coverage span, Comprehension Accuracy, Recognition Accuracy, Sense of Trust, and Satisfaction of Resource Content.

Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle’s software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.

With the advancement of science and technology, the cabin of a car is becoming increasingly intelligent. The design of audible, intelligible, conductive and useful sounds in the audio-visual design of various interfaces in the cabin of a car, to enable driving safety and experience, has become a new design issue in the context of future smart mobility. Through literature research and analysis, this paper summarises the human factors parameters and design methods for the design of vehicle guidance sound. This study is based on the lane departure warning scenario of the car’s intelligent cockpit and investigates the sound design in this scenario. We conducted a case study of the warning cues of four mainstream car brands in this scenario and explored the design method of the cueing sound in the lane departure warning scenario.

This research obtains the functional requirements by mining the needs of the group of intelligent car owners, analyzing the relationship between user needs and functional requirements, and based on the innovation diffusion theory, using the online and offline diffusion channels, designs a service system that not only meets the needs of the modified car owners, but also has good usability. The innovation diffusion model was used as a research method for the availability of customized intelligent vehicle modification services. Collect the user needs of refitters through research, and analyze the user demand elements and their importance of refitting APP by using the diffusion group division method; Analyze and dissect the user needs to obtain the corresponding functional requirements, take the functional requirements as the design basis, combine the needs of the strong diffusion group, and design the information architecture, interaction prototype and visual interface of the modified service APP to optimize the contacts in the service system, and use the O2O business model to enhance the diffusion efficiency. It provides a solution for the optimization service system of China's intelligent vehicle modification industry.

Despite the rapidly expanding research on in-car intelligent voice assistants, relatively little attention has been paid to the study of their personality traits and how to improve the user’s emotional experience by cutting through from this perspective. In this study, first, an exploratory interview-based study is conducted to identify key traits that elicit driver emotions and five personality traits that can be used in in-car intelligent voice assistants: emotional enrichment, emotional expressiveness, persona congruence, empathic expressiveness, and user impressions. Second, an online survey-based study is conducted to investigate how the above five performance dimensions that focus on the degree of personification of intelligent assistants can be incorporated into smart car voice interaction systems in different scenarios. Finally, the ideal use cases for each personality trait are investigated, as well as how in-car intelligent voice assistants can apply the corresponding trait dimensions according to the current real-time driving situation. This study explores how the five personality trait dimensions can enhance driving users’ emotional experience and emotional connection with intelligent voice assistants by adding a pleasant attitude, a sense of pleasure, and can accurately grasp users’ emotional state and provide proactive services conducive to emotional appeasement and safe driving in navigation.

A study is presented focusing on the set of variables associated with the link between cognitive aspects, usability and fatigue in the context of the safe operation of heavy vehicles in a surface coal mine, in order to understand how driving performance is affected and the reduction of perceptual activity capacity in the detection of tasks associated with driving. Method: A multi-method approach was used where human activity recognition (HAR) was incorporated to analyze data from different sensor sources to identify activity-related features of a person. The study was developed in a surface mine with the participation of 37 drivers with a mean age of 37.4 years (STDV. 9.6), the study covered a shift design of 12 h duration and in sequence 3Day, 4 Night by three recovery shifts. Systematic observation sessions and data recording were carried out. Results: The various data recorded show that the usability possibilities of the cabins in terms of driver performance is closely related to the influence of aspects of geometry and composition of the cabs on the one hand and on the other hand with the cumulative effects of working time, i.e. it is not only to understand the impact of the 12-h shift and its effects on the modification of metabolic aspects and sleep hygiene of drivers, to explain the problem of driving performance, it must also consider an aspect that influences performance such as sleep debt.

The present study investigated the potential of using gestures to guide and control unmanned automated heavy vehicles in underground mine contexts, as well as the effects of adding external human-machine interfaces (eHMIs) to provide feedback during the gesture interaction. A study with 12 professional operators was conducted in a simulated mine environment, utilizing a Wizard of Oz methodology. The subjects used gestures to guide and control a heavy vehicle in three different scenarios in the mine, and different aspects of the user experience (UX) were assessed. The results support the notion that there is high potential in using gestures when operators stand in close proximity to the vehicles. Moreover, the results suggest that eHMI solutions can enhance the operator’s acceptance and feelings of safety. The selected gestures seemed appropriate for the investigated scenarios, which should be valuable insights for practitioners intending to develop and implement gesture interaction for similar applications.

Insufficient operator engagement poses danger to public safety. Identifying and validating the factors that influence Control Room Operator (CRO) engagement and choosing suitable research methods for collecting interview data is a crucial element of informing user experience design (UXD) interventions for enhancing engagement. However, this knowledge has been largely neglected. With the goal of filling this gap, a total of 18 CROs in two motorway control rooms were recruited. They were asked to participate in a two-stage interview to capture the influential factors of operator engagement. The findings corroborate that the factors influencing engagement in non-safety-critical domains still apply in the more safety critical control room context. This helps build a solid theoretical foundation for designing UXD interventions for enhancing operator engagement. In addition, this paper describes some inherent obstacles in using interview-based techniques for collecting the operator working experience -- especially engagement --, and makes suggestions for alleviating these obstacles.

As a counter to the continuous increase in size of passenger cars and the share of sport utility vehicles in traffic, we focus in this paper on the segment of fine means of transport that can be classified below the classic passenger car/small car. We have called mobility with these fine means of transport “fine mobility”. The broad spectrum of means of transport of fine mobility has not yet been perceived as a coherent segment and cannot be captured by any existing vehicle categorization. Therefore, a new classification was developed to define fine mobility, which classifies all road-based means of individual transport according to their (urban) spatial effects into the seven classes XXS to XXL. The classification makes it possible to clearly distinguish fine mobility means of transport - from micro mobiles to mobility aids, bicycles of all kinds to light electric vehicles - from coarse means of transport - from mid-range cars to off-road vehicles - on the basis of the characteristics of the spatial dimension (cuboid around the external dimensions of vehicles) and the turning circle. In this context, the classification builds on various use cases that may condition the promotion of fine mobility through its preference in moving and stationary traffic. The diversity of fine mobility means of transport in terms of their possible uses and transport capacities illustrates the shift potential of many urban as well as city-regional car trips to finer alternatives.

Urban air mobility (UAM) has gained increased attention as a promising new solution to tackle issues such as traffic congestion. This study aims to assess users’ perception and usage intentions and identify and weigh success-critical acceptance factors against each other. Further, user-related differences in the underlying decision patterns are analyzed. A mixed-methods approach was employed, including a prior interview study with laypeople and experts (N = 16), calculations of feasible prices via agent-based símulations, and the main survey study (N = 135) – a Choice-Based Conjoint (CBC) with the attributes: environmental impact, costs, placement of take-off and landing stations (vertiports), automation level, and onboard benefits. Results indicated that environmental impact, costs, and vertiport placement were the top three factors influencing user acceptance. The relative importance of these attributes differed, however, depending on the user group. Based on the results, three user segments were identified: automation-skeptical users, environmentally-conscious users, and cost-conscious users. The findings provide valuable insights for UAM providers and policymakers to understand the attitudes and needs of potential users and to design effective strategies for promoting the adoption of UAM.

This paper reports on research on responsible innovation for last-mile urban delivery. We designed, developed and tested a fleet of autonomous electric vehicles that operate in a new urban district developed as part of the federal horticulture exhibition 2019 in Heilbronn, Germany. Hereby not only the technical aspects play an important role but also the acceptance of the stakeholders. Thereby, the technical and technological innovation of the entire system is guided by the interactivity with the users. They are able to interact with the system by planning, modifying and monitoring their delivery requests in real time. All different usage scenarios together with the human machine interfaces were co-designed in a participatory way with users from the new neighborhood by an interdisciplinary team of engineers, logistics experts, behavioral scientists, designers, and developers. In this context, the research deals with both social and technical innovation. The ability to identify and describe processes that can be used as models for the implementation of such innovations and that can be reproduced in similar contexts is crucial to meet the challenges of digitalization and automation in mobility with regard to demographic change and the trend towards reurbanization.

Autonomous shuttles can extend the flexibility of micro-mobility to small groups, families, and persons with mobility limitations and impairments. When integrating autonomous shuttles into public transportation systems, the challenge is to shift the tasks of the driving personnel to the operators in the traffic control center. From there, the autonomous shuttles are centrally monitored and controlled. At the same time, the service quality for the passengers should be fully maintained. This leads to the research question, “Which new tasks arise for operators in the traffic control center in the dispositive control of autonomous shuttles?” A task analysis of the previous tasks of the driving personnel was conducted to answer the research question. The analysis consists of a method mix of inductive and deductive methods to compensate for the disadvantages of both. The result is a systematic of tasks that have to be shifted to the operators in the traffic control center. Furthermore, the technical potentials to support these tasks by assistive systems are described. The results mean a human-centered design of autonomous shuttles for passengers and a basis of task design for operators in the traffic control center for public transport companies.

Delivery robots can contribute to efficient transportation and handover of goods in urban areas. To realize the full potential of this technology, users need to accept these novel systems. One possibility to increase acceptance is adapting the design of robots. The design of delivery robots, which are meant to function as tools but also interact closely with humans during transportation and delivery, presents both challenges and opportunities for increasing user acceptance. Specifically, anthropomorphic framing, or ascribing human-like characteristics to the robot, may influence acceptance. In addition, the type of goods being transported by the robot may also affect user acceptance. We used a video-based online experiment, to investigate how anthropomorphic framing and product value affect the individual and general acceptance and intention to use robots for transporting goods. In addition, we operationalized the perceived value of the robot’s service through the willingness to pay for this delivery service. The data of 189 participants were retrieved in our between-subjects online study. The study revealed no differences in general acceptance, intention to use, and willingness to pay for the service robot. However, anthropomorphic framing and the prize of the transported goods mattered for the individual acceptance of the delivery robots. In particular, anthropomorphically framed robots and robots transporting inexpensive goods were accepted significantly more. As the services of transporting inexpensive products were accepted more, the successful implementation and actual usage could lead to an extension of the acceptance of more expensive goods transportation. This result could be the basis for a gradual market entry strategy that starts with low-cost product transportation like food delivery.

Purpose - With the increasing integration of car functions, as well as the increasing operation and information on the central control screen, we explored how to improve the user interface, in order to reduce cognitive load and improve reading efficiency. Methodology - This paper applied the neural network-based eye-tracking prediction model to analyze the eye-tracking data of mainstream smart electric vehicle center control screens. Through analyzing and discussing the attention map, clarity map, regions of interest, etc., we assess the usability of user interface and propose design guidelines. Conclusion - In a landscape central control screen, dock bar is more visually significant on the left side. The layout should avoid scattering, the shape of the function card should avoid using long stripes, and the information should not be too concentrated. Important information should be designed with high contrast and distinctive colors, and filled types icons should be used. Important text should be succinct, enlarged, bolded, and not be too dense. Concentrated text is more likely to attract users’ attention, but it will also cause higher cognitive load.

In our study, we aim to provide a sustainable route for tourism by considering the carbon emission by different transportation methods in an attempt to create a sustainable travel itinerary for each user. A model for route optimization between selected travel spots using an actual dataset of popular tourist spots in Tokyo, the road network, and available train connections is proposed. We try different vehicle routing algorithms such as Dijkstra’s algorithm and genetic algorithm. This is followed by creating clusters for close points and providing a walking/bicycle route option. We test our model by comparing it with Google Maps. The result of this paper shows the relationship between time and carbon emission, and the improvement in terms of carbon emission between different routes.

Mobility as a Service (MaaS) has been hailed as a new ecosystem that is transforming transportation systems and individual mobility behavior. However, due to new phenomena such as Covid-19, adoption in the mobility industry has stagnated, and not all ecosystems, i.e., novel partnership networks, could scale. The most important component of both ecosystems in general and MaaS is the platform that combines all other building blocks and enables exchanges between the supply and demand sides. This research therefore aims to design the platform of a minimum viable MaaS ecosystem using academic MaaS as an example, with a qualitative content analysis of supply-side interviews and demand-side focus group discussions and workshops. The focus lies on an academic offer, as MaaS is typically targeted at young individuals and persons with high education. The results show that the standardization of programming interfaces and the provision of user data for all participating institutions are key drivers.

With the continuous development of bike-sharing apps, the competition has become more and more fierce, and the products tend to be homogenized. The study also aims to build a framework of “demand-perceived-performance-function” in bike-sharing apps, and to point out the core dimensions of user experience design in bike-sharing apps. The study helps to improve the exploration of perceptual schematic theory in the field of information interaction and shared mobility, and provides a reference basis for the current mainstream user experience design of bike-sharing apps.

While shared e-scooters are still highly prevalent in many urban areas, we also see an increasing share of privately owned e-scooters on our roads. However, so far, not much is known about the users of such privately owned e-scooters. As there is reason to suspect that those who ride their own e-scooter differ considerably from occasional users of rental vehicles, the question is what the characteristics of those riders are and how their use of vehicles can be described. To address these questions, we analysed data from an online survey (99 usable data sets) and several focus group discussions (20 participants) with frequent users and owners of e-scooters. Results show that these frequent riders have a high degree of identification with the vehicle, and often use it as their main means of transport. The majority indicated that they used their e-scooter daily or almost daily, with commuting as their most frequent trip purpose. They are rather safety conscious, as is highlighted by their use of protective gear and the installation of additional safety equipment on their vehicles. The results indicate that a specific focus on frequent users is warranted, as they appear to be quite distinct from the user population that occasionally uses shared services. With the number (and share) of privately owned e-scooters continuously increasing, targeted approaches that facilitate their safe and efficient participation in traffic will be required.

Crash statistics and hospital data show that injured e-scooter riders arrive at hospitals often at night and on weekends. Subsequently, the crash risk at night is higher compared to the daytime. A possible explanation might be increased rule violations, safety-critical behaviors, and changes in the user group at night compared to daytime. Therefore, we aimed to conduct an observational study analyzing the interrelationships of risky behaviors, rule violations, and user characteristics of e-scooter riders in two German cities. A total of 732 observations were analyzed with Chi-Squared tests and Generalized Estimating Equations. The results show increased rates of tandem riding at night compared to the daytime and increased rule violations of adolescents compared to older e-scooter riders regardless of the time of day. Rates of helmet use, wrong-way riding, headphone use, smartphone use, and luggage transport were comparable for daytime and night observations. The results suggest that educational campaigns should focus on tandem riding, especially targeting the user group of teenage riders. This study brings e-scooter riding at night into the light and emphasizes riders' nightly behaviors for policymakers and traffic safety.