In-vehicle Infotainment Systems Research Articles

Sonically-enhanced in-vehicle air gesture interactions: evaluation of different spearcon compression rates

AbstractDriver distraction is a major contributor to road vehicle crashes, and visual distraction caused by using in-vehicle infotainment systems (IVIS) degrades driving performance and increases crash risk. Air gesture interfaces have been developed to mitigate driver distraction, and using auditory displays showed a decrease in off-road glances and an improved perceived workload. However, the potential of auditory display was not fully investigated. The present paper presents directional research in the design of auditory displays for air-gesture IVIS through a dual-task experiment of driving a simulator and air-gesture menu navigation. Twenty-four participants utilized the in-vehicle air gesture interfaces while driving with four auditory display conditions (text-to-speech, 70% compressed spearcons, 40% compressed spearcson, and no sound). The results showed that 70% spearcon reduced visual distraction and increased menu navigation accuracy but with increased navigation time. 70% spearcon was most preferred by the participants. Driving performance or workload did not show any difference among the conditions. Implications are discussed with the design guidelines for future implementations.

RFDrive: Tagged Human-Vehicle Interaction for All

Human–vehicle interaction is an important factor for safe driving. The driver needs to interact with the in-vehicle steering wheel and infotainment system properly during driving. Specifically, driving guidelines require the driver to hold the steering wheel at the 3 o’clock and 9 o’clock positions. Moreover, the in-vehicle infotainment system should be more adaptive for the driver and front-seat passenger during driving (i.e., the in-vehicle infotainment system should be part and even fully disabled for the driver, whereas the front-seat passenger should be able to enjoy the full in-vehicle infotainment system). However, affordable vehicles are usually designed to achieve basic driving functions without considering safe human–vehicle interactions, which require an add-on, affordable, and ready-to-use human–vehicle interaction monitoring system. In this article, we present RFDrive, a system that can simultaneously locate the driver’s hand positions on the steering wheel and automate in-vehicle infotainment system touch discrimination for safe driving using commodity passive RFID tags. Since these commodity passive RFID tags are low cost (i.e., around 5 cents per tag), battery free, and are small, like a sticker, our design will enable not only safe driving but is also low cost, which can lead to sustainable solutions. To do so, we attach RFID tags on the steering wheel for the driver’s hand position location and attach RFID tags on the roof of the vehicle’s interior for in-vehicle infotainment system touch discrimination (i.e., differentiating the driver’s infotainment system touch and front-seat passenger’s infotainment system touch). However, the wheel steering will distort the wireless channel-based driver’s hand position location on the steering wheel. Thus, we propose a novel tag ID-based algorithm to locate the driver’s hand position on the steering wheel by harnessing the human body as part of the RFID tag’s antenna. Since the in-vehicle infotainment system touch from the driver or front-seat passenger will affect different RFID tags attached to the roof of the vehicle’s interior, we propose to use the differential amplitude of backscattered signals from all the tags to discriminate in-vehicle infotainment system touch sources. Our experiments show that RFDrive can achieve the average accuracy of 0.98 and 0.98 for in-vehicle touch source discrimination and driver’s hand position location, respectively.

A vehicle firmware security vulnerability: an IVI exploitation

AbstractIn the last years, the increasing vehicular technology has led to a surge in cybersecurity attacks, particularly regarding connected vehicles and their vulnerable infotainment systems. This paper explores the vulnerabilities within an In-Vehicle Infotainment (IVI) system firmware, focusing on the Gen5W_L multimedia device utilized in Hyundai, Kia, and Genesis vehicles. Leveraging reverse engineering techniques, the study uncovers several security issues within the firmware, allowing for the creation and installation of custom firmware. The paper introduces Chimaera, a reverse engineering attack targeting the IVI system firmware, which exploits a vulnerability introduced by statically compiling the mbedtls library. After a reverse engineering analysis and injecting malicious assembly code directly in the IVI firmware, the attack enables the extraction of sensitive information from the firmware files like the cryptographic keys to install a customized firmware. The research shows that exploiting these vulnerabilities facilitates the installation of insecure firmware, granting attackers unauthorized access to vehicle functionalities. This includes the possibility to inject CAN bus messages, potentially compromising critical vehicle systems such as radio controls and safety features. The findings underscore the need for robust cybersecurity measures within automotive systems and highlight the significance of vulnerability assessment to mitigate security risks in connected vehicles.

Driving Distraction Evaluation Model of In-Vehicle Infotainment Systems Based on Driving Performance and Visual Characteristics

With the rapid development of automotive electronic technology, increasingly car enterprises choose to carry touchscreen in-vehicle infotainment systems (IVISs) in smart cars. The integration of navigation, music, telephone, and other functions into touchscreen IVISs has greatly enriched the driving experience. However, the design of touchscreen IVISs, which lacks consideration of driver human–computer interaction leads to increased driving distraction. The current discussion is limited to evaluating the overall distractions of the secondary task, and there is a lack of research on classifying and summarizing the types of driving distractions. Therefore, this paper proposes a new method to evaluate the degree of driving distraction during the interaction with touchscreen IVISs based on driving performance and visual characteristics. A driving simulation environment was built to conduct psychological experiments on three types of driving distraction, namely visual, manual, and cognitive distraction, respectively, to obtain the impact of different types of driving distraction by using touchscreen IVISs. Combining the criteria importance through intercriteria correlation method with fuzzy comprehensive evaluation to establish a driving distraction evaluation method, we quantify the driving distraction caused by the touch screen IVIS. The results of this study indicate that the proposed driving distraction evaluation model by using driving performance and visual characteristics can effectively evaluate the degree of driving distraction caused by the touchscreen IVIS and provide reference and specification for IVIS safety design from a human–computer interaction perspective.

How Dose Aesthetic Design Affect Continuance Intention in In-Vehicle Infotainment Systems? An Exploratory Study

With the digitalization of automobile cabins, in-vehicle infotainment systems play an increasingly pivotal role in vehicles. This study aims to understand how the interface aesthetics of the in-vehicle infotainment system affect users’ continuance intention in in-vehicle infotainment systems. Based on a literature review, a theoretical model was constructed, encompassing seven latent variables: simplicity, colorfulness, diversity, craftsmanship, functional value, emotional value, and continuance intention. Analysis of 243 valid questionnaires revealed that both functional and emotional values serve as crucial mediators in encouraging users to continue using the in-vehicle infotainment system, with functional quality being the core element. Moreover, simplicity, diversity, and craftsmanship indirectly affect continuance intention by influencing both functional and emotional values. These findings underscore the need for future designers of in-vehicle infotainment systems to focus on interface functionality and emotional needs, and to ensure that content is concise, engaging, user-friendly, and visually polished, thereby enhancing the user experience and fostering the intention to continue usage.

SP-E: Security Evaluation Framework of In-vehicle Infotainment System based on Threat Analyses and Penetration Tests

With the increasing requirement of people, the functions of in-vehicle infotainment systems are becoming more and more abundant, and their security also affects the safety of vehicles. Therefore, it is more and more important to evaluate the security of the IVI system. This paper proposes a security evaluation framework for in-vehicle infotainment systems based on threat analyses and penetration tests. By constructing the data flow diagram of application scenarios, analyzing threats, combing the attack link diagram, combining white-box audit and black-box test, we use the characteristics of high efficiency of automatic tools and high accuracy of manual methods to set factor sets, and then the whole IVI system is evaluated by Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation.

Empowering Driver-Passenger Collaboration: Designing In-Car Systems with a Focus on Social Connectedness, Fairness, and Team Performance

Driving a car can be difficult when it comes to distractions caused by operating the in-vehicle infotainment system (IVIS). In-car passengers often help with performing IVIS-related tasks. However, an IVIS is often not designed with a focus on task collaboration. In this article, we focus on how to design in-car systems with the goal to support collaboration between a driver and a front-seat passenger. Based on infotainment-oriented tasks, we initially explore five key collaborative control concepts by means of an IVIS which differ from each other in terms of the number of available IVIS screens (one or two), access to menus (restricted and unrestricted), and the nature of performing tasks in parallel or one after the other. Results from a simulator study with N = 16 pairs show significant effects of the concepts on social collaboration in terms of perceived social connectedness (measured with sub-dimensions connectedness, affiliation, belongingness, companionship), team performance (coordination effectiveness and team cohesion), and fairness. We found that especially a dedicated passenger IVIS screen empowers front-seat passengers, reduces power dynamics, supports fairness, and minimizes driver distraction (caused by interacting passengers). We discuss the implications of these findings and posit recommendations to design future IVIS in passenger cars with improved driver-passenger collaboration by explicitly designing for balanced power roles, situational awareness, active communication, and a balance between drivers’ privacy and trust toward the passenger. Additionally, we outline a systematic overview of future work to explore the research field of driver-passenger collaboration in more breadth and depth.

Deep Learning-Based Business Recommendation System in Intelligent Vehicles

The advancements in intelligent vehicle technologies are facilitating the growth of information technology (IT) platforms, unlike conventional automobiles. In-vehicle-infotainment (IVI) is becoming an appealing element in intelligent vehicles as it offers various experiences to users; however, it requires personalized services to provide even more sophisticated user experiences. It is supposed that passengers search for businesses that provide products or services they found interesting in videos played via IVIs while the vehicle is driving autonomously. In that case, it could be more effective to use images that can express the user’s preference as a query for the search than to utilize texts such as product names. Accordingly, this study proposes a recommendation system that informs users of businesses near an intelligent vehicle when a passenger inputs an image of a product or service into an IVI system. The proposed recommendation system involves training deep learning-based image classification models with the user’s interest images to classify the category, measure the similarity with the business category using Word2vec, and finally provide the locations of the businesses with a high degree of similarity via IVI, using a smartphone. The experimental results indicated that the user’s interest image exhibited 85% accuracy for category classification via the EfficientNet B0 model, while the similarity between the image and business categories using Word2vec was particularly high in the business category similar to the actual image category.

On the relationship between occlusion times and in-car glance durations in simulated driving

Drivers have spare visual capacity in driving, and often this capacity is used for engaging in secondary in-car tasks. Previous research has suggested that the spare visual capacity could be estimated with the occlusion method. However, the relationship between drivers’ occlusion times and in-car glance duration preferences has not been sufficiently investigated for granting occlusion times the role of an estimate of spare visual capacity. We conducted a driving simulator experiment (N = 30) and investigated if there is an association between drivers’ occlusion times and in-car glance durations in a given driving scenario. Furthermore, we explored which factors and variables could explain the strength of the association. The findings suggest an association between occlusion time preferences and in-car glance durations in visually and cognitively low demanding unstructured tasks but that this association is lost if the in-car task is more demanding. The findings might be explained by the inability to utilize peripheral vision for lane-keeping when conducting in-car tasks and/or by in-car task structures that override drivers’ preferences for the in-car glance durations. It seems that the occlusion technique could be utilized as an estimate of drivers’ spare visual capacity in research – but with caution. It is strongly recommended to use occlusion times in combination with driving performance metrics. There is less spare visual capacity if this capacity is used for secondary tasks that interfere with the driver’s ability to utilize peripheral vision for driving or preferences for the in-car glance durations. However, we suggest that the occlusion method can be a valid method to control for inter-individual differences in in-car glance duration preferences when investigating the visual distraction potential of, for instance, in-vehicle infotainment systems.

Impact of Temporary Browsing Restrictions on Drivers’ Situation Awareness When Interacting with In-Vehicle Infotainment Systems

Looking away from the road during a task degrades situation awareness of potential hazards. Long glances back to the road rebuild this awareness and are thought to be critical for maintaining good vehicle control and recognizing conflicts. To further investigate the importance of rebuilding situation awareness, a controlled test-track study was performed that evaluated drivers’ hazard awareness and response performance to a surprise event after completing a task that involved pausing partway through it to look back at the road. Thirty-two drivers completed a visual-manual infotainment system secondary task. Half of the drivers were instructed to pause their browsing mid-task, while the others were not. While the task was being performed, a lead vehicle activated its hazard lights. It then unexpectedly dropped a fake muffler once drivers completed the task. Drivers’ visual attention to the road and their ability to respond to the muffler were measured. The drivers that paused their browsing were more aware of the lead vehicle’s hazard lights, showed less surprise to the dropped muffler, and executed more measured avoidance maneuvers compared to the drivers that did not pause their browsing. These findings suggest that drivers’ situation awareness can be better maintained when task interactions are paced, allowing for longer monitoring of the environment. Mechanisms that encourage drivers to take restorative on-road glances during extended browsing may be a key aspect of an overall approach to mitigating driver distraction.

Digital Forensic Case Studies for In-Vehicle Infotainment Systems Using Android Auto and Apple CarPlay.

Vehicle systems have been one of the fastest-growing fields in recent years. Vehicles are extremely helpful for understanding driver behaviors and have received significant attention from a forensic perspective. Extensive forensic research was previously conducted on on-board vehicle systems, such as an event data recorders, located in the electronic control unit or manufacturer-based infotainment systems. However, unlike previous vehicles that used only manufacturer-based infotainment systems, most vehicles today are equipped with infotainment systems such as Android Auto and Apple CarPlay. These in-vehicle infotainment (IVI) systems connect to mobile devices such as smartphones and tablets. The vehicle can periodically communicate with a smartphone and thus a network outside the vehicle. Drivers can use more services in their vehicles than ever before. Accordingly, an increasing number of diverse data are being stored in vehicles, with mobile devices connected to both the vehicle and the cloud. Such data include information that can be of significant help to investigators in solving problems during forensic investigations. Therefore, forensics of IVI systems such as Android Auto and Apple CarPlay are becoming increasingly important. We analyzed various forensic studies conducted on Android Auto and Apple CarPlay. Most of the research was mainly focused on mobile devices connected through a wired USB connection. The use of wireless-based IVI systems has recently been increasing. However, the analysis of Android Auto and Apple CarPlay from this point of view is insufficient. Therefore, we proposed a forensic methodology that fully considers such limitations. A forensic analysis was conducted on various IVI systems. We also developed an IVI system forensics tool that works based on the proposed methodology.

GOLIATH: A Decentralized Framework for Data Collection in Intelligent Transportation Systems

Intelligent Transportation Systems (ITSs) technology has advanced during the past years, and it is now used for several applications that require vehicles to exchange real-time data, such as in traffic information management. Traditionally, road traffic information has been collected using on-site sensors. However, crowd-sourcing traffic information from onboard sensors or smartphones has become a viable alternative. State-of-the-art solutions currently follow a centralized model where only the service provider has complete access to the collected traffic data and represent a single point of failure and trust. In this paper, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GOLIATH</i> , a blockchain-based decentralized framework that runs on the In-Vehicle Infotainment (IVI) system to collect real-time information exchanged between the network’s participants. Our approach mitigates the limitations of existing crowd-sourcing centralized solutions by guaranteeing trusted information collection and exchange, fully exploiting the intrinsic distributed nature of vehicles. We demonstrate its feasibility in the context of vehicle positioning and traffic information management. Each vehicle participating in the decentralized network shares its position and neighbors’ ones in the form of a transaction recorded on the ledger, which uses a novel consensus mechanism to validate it. We design the consensus mechanism resilient against a realistic set of adversaries that aim to tamper or disable the communication. We evaluate the proposed framework in a simulated (but realistic) environment, which considers different threats and allows showing its robustness and safety properties.

User Interface Design Patterns for Infotainment Systems Based on Driver Distraction: A Colombian Case Study

In this paper, we present a set of nine user interface design patterns for in-vehicle infotainment systems centered on the content, interaction mode, style, shortcuts, and notifications of the system, which are built based on both theoretical support and an empirical pattern finding process. This empirical process consists in an exploratory test made with 10 users from an age range from 18 to 29 and with a minimum of 2 years of driving experience, who were asked to perform a set of 13 secondary tasks in the vehicle to identify recurrent problems, behavioral patterns, and best practices. The output of this exploratory test was used as the main data source for the design patterns consolidation. It is worth mentioning that the proposal of these patterns arose as an initiative to begin to consider factors that can affect the driver’s experience in the Latin American context. The set of design patterns has been validated via a content validation (as an exploratory study) by a panel of Latin American experts in the area of HCI and UX through the development of a prototype using the patterns as a tool for the redesign proposal of the infotainment systems tested during the empirical finding process.

Reversing Kia Motors Head Unit to discover and exploit software vulnerabilities

Modern vehicles resemble four-wheels computers connected to the Internet via their In-Vehicle Infotainment (IVI) systems. As with PCs in the past, cars, being connected to the Internet can be potentially vulnerable. The IVI system of a car is part of the intra-vehicle network and can be the entry-point of offensive cybersecurity attacks. The intra-vehicle network, based on the CAN protocol, is vulnerable by design: messages are exchanged in clear. Thus, the uncontrolled access to the CAN bus may have serious impact on the vehicle itself and its passengers. In this paper, we present a vulnerability assessment, through a reverse engineering process, of Kia vehicles IVI system. In particular, we focused on reverse engineer the Kia IVI system to discover vulnerabilities that may allow an attacker to compromise the IVI functionalities and inject CAN frames into the CAN bus to alter the behaviour of (part of) the vehicle. By reverse engineering the IVI, we identified four important vulnerabilities that affect all Kia vehicles that embed the studied IVI. Finally, we show how an attacker can easily control the IVI and inject CAN bus frames by means of a Metasploit module that we wrote.

Classification of Driver Cognitive Load: Exploring the Benefits of Fusing Eye-Tracking and Physiological Measures

In-vehicle infotainment systems can increase cognitive load and impair driving performance. These effects can be alleviated through interfaces that can assess cognitive load and adapt accordingly. Eye-tracking and physiological measures that are sensitive to cognitive load, such as pupil diameter, gaze dispersion, heart rate (HR), and galvanic skin response (GSR), can enable cognitive load estimation. The advancement in cost-effective and nonintrusive sensors in wearable devices provides an opportunity to enhance driver state detection by fusing eye-tracking and physiological measures. As a preliminary investigation of the added benefits of utilizing physiological data along with eye-tracking data in driver cognitive load detection, this paper explores the performance of several machine learning models in classifying three levels of cognitive load imposed on 33 drivers in a driving simulator study: no external load, lower difficulty 1-back task, and higher difficulty 2-back task. We built five machine learning models, including k-nearest neighbor, support vector machine, feedforward neural network, recurrent neural network, and random forest (RF) on (1) eye-tracking data only, (2) HR and GSR, (3) eye-tracking and HR, (4) eye-tracking and GSR, and (5) eye-tracking, HR, and GSR. Although physiological data provided 1%–15% lower classification accuracies compared with eye-tracking data, adding physiological data to eye-tracking data increased model accuracies, with an RF classifier achieving 97.8% accuracy. GSR led to a larger boost in accuracy (29.3%) over HR (17.9%), with the combination of the two factors boosting accuracy by 34.5%. Overall, utilizing both physiological and eye-tracking measures shows promise for driver state detection applications.

Effects of Animated Screen Transition in In-Vehicle Infotainment Systems: Perceived Duration, Delay Time, and Satisfaction

Enhancing the user experience of in-vehicle infotainment system (IVIS) GUIs has gained importance in the vehicle industry. However, there are no studies on the effects of animated transitions in an IVIS screen. We investigated the effects of animated transitions on the perceived duration, delay time, and satisfaction of IVISs. Forty participants divided into two groups (Slide and Fade) performed touch tasks to experience different transition effects and evaluate each condition. The transitions were manipulated considering transition type (NS, Split-R, Split-M), easing type (Ease-out, Ease-In), and interval time (0, 150, 300, 450, 600 ms). An analysis indicated that Split-R (fade-fade) in the Fade group and Split-M (fade-slide) in the Slide group best satisfied users. Post-interviews revealed that the interval time should not exceed 450 ms, while an appropriate interval (150 ms) is necessary to enhance the user’s visual perception and satisfaction. Our results may provide effective guidelines for designing animated transitions in IVIS.

Evaluation of a dynamic blocking concept to mitigate driver distraction: Three simulator studies

In recent years, the number and complexity of in-vehicle infotainment systems has been steadily increasing. While these systems certainly improve the driving experience, they also increase the risk for driver distraction. International standards and guidelines provide methods of measuring this distraction along with test criteria that help automakers decide whether an interface task is too distracting to be used while driving. Any specific function failing this test should therefore be locked out for use by the driver. This study implemented and tested a dynamic approach to this blocking by algorithmically reacting to driver inputs and the pace of the interaction in order to prevent drivers from having prolonged or too intense sequences of in-vehicle interactions not directly related to driving. Three simulated driving experiments in Germany and the United States were conducted to evaluate this dynamic function blocking concept and also cater for differences in the status quo of either no blocking or static blocking. The experiments consisted of a car following scenario with various secondary interface tasks and always included a baseline condition where no blocking occurred as well as an implementation of the dynamic function blocking. While Experiments 1 and 3 were aimed at collecting and analyzing gaze and driving data from more than 20 participants, Experiment 2 focused on the user experience evaluation of different visual feedback implementations from 13 participants. The user experience as rated by these participants increased throughout the course of all three studies and helped further improve both the concept and feedback design. In the experiments the total glance time towards the road was significantly higher in the dynamic function blocking condition compared to the baseline, already accounting for the increase in total task time inherent to the dynamic condition. Participants developed two strategies of interacting with the dynamic function blocking. They either operated at their normal baseline speed and incurred task blockings or operated slower to avoid the blockings. In the latter strategy, participants chunked their interactions into smaller steps with the present data suggesting that they used the pauses in between chunks to look back onto the road ahead. Theoretical and practical implications of this first evaluation of a dynamic function blocking concept are discussed.

Mounting a smartphone on a steering-wheel to facilitate ease of visibility of the navigation screen: A systematic product design approach.

Both professional and personal car drivers use smartphones as In-Vehicle Infotainment System (IVIS) and generally mount it wherever they feel convenient. Inappropriate or sub-optimal positioning of navigation devices increases off-road eye-glance duration and fixation frequency. The current research aimed to develop a smartphone holding device to facilitate the mobile-phone's easy mounting on the steering wheel's hub, ensuring the screen's visibility at a comfortable viewing angle in a vertical upright position irrespective of the steering wheel's rotation. A systematic product design methodology was adopted to develop the final product. The morphological chart was adopted for generating the different concepts of the smartphone mounting device. A Pugh chart was used for screening the various concepts generated in the previous step. Finally, a prototype of the selected best concept was made. User acceptance was assessed by taking feedback from users, and System Usability Scale (SUS) was used for usability evaluation. The developed innovative mounting device was light-weight and easy to use (SUS score 83.5). The final prototype was very effective in changing the angle of the smartphone to facilitate easy visibility at a comfortable viewing angle through the use of a ball and socket mechanism at the base. A ball bearing system was used in the mobile-phone holder for maintaining vertical stationary position during steering wheel rotation. As the device is useful for mounting the smartphone on the steering wheel's hub, it might reduce driver distraction.

Analysis of Relationship between Electroencephalograms and Subjective Measurements for In-Vehicle Information System: A Preliminary Study.

In this study, we explored the relationship between objective and subjective measures for usability evaluation in in-vehicle infotainment systems (IVISs). As a case study, four displays were evaluated based on cluster location and display orientation (that is, front–horizontal, front–vertical, right–horizontal, and right–vertical). Thirty-six participants performed tasks to manipulate the functions of the IVISs and data were collected through an electroencephalogram (EEG) sensor and questionnaire items. We analysed a model that estimated EEG-based objective indicators from subjective indicators. As a result, the objective indicators reflected the subjective indicators and were considered to explain the driver’s cognitive state. Although EEG data were collected from only four participants, this study proposed an experimental design that could be applied to the analysis of the relationship between the subject’s evaluation and EEG signals, as a preliminary study. We expect the experimental design and results of this study to be useful in analysing objective and subjective measures of usability evaluation.

Miniaturized Broadband-Multiband Planar Monopole Antenna in Autonomous Vehicles Communication System Device

The article mainly presents that a simple antenna structure with only two branches can provide the characteristics of dual-band and wide bandwidths. The recommended antenna design is composed of a clockwise spiral shape, and the design has a gradual impedance change. Thus, this antenna is ideal for applications also recommended in these wireless standards, including 5G, B5G, 4G, V2X, ISM band of WLAN, Bluetooth, WiFI 6 band, WiMAX, and Sirius/XM Radio for in-vehicle infotainment systems. The proposed antenna with a dimension of 10 × 5 mm is simple and easy to make and has a lot of copy production. The operating frequency is covered with a dual-band from 2000 to 2742 MHz and from 4062 to beyond 8000 MHz and, it is also demonstrated that the measured performance results of return loss, radiation, and gain are in good agreement with simulations. The radiation efficiency can reach 91% and 93% at the lower and higher bands. Moreover, the antenna gain can achieve 2.7 and 6.75 dBi at the lower and higher bands, respectively. This antenna design has a low profile, low cost, and small size features that may be implemented in autonomous vehicles and mobile IoT communication system devices.