In-vehicle Technology Research Articles

Strategies for accelerating the implementation of non-intrusive alcohol detection systems in the vehicle fleet

Introduction Crashes involving drinking drivers represent as much as one-third of all fatal crashes around the world. Progress has been made in reducing this toll through a series of interventions that attempt to discourage driving while intoxicated (DWI) and reoffending among drivers who have been convicted of DWI. However, these approaches cannot eliminate the problem. In-vehicle technologies are being developed, such as the Driver Alcohol Detection System for Safety—commonly referred to as DADSS—that have the potential to prevent alcohol-impaired drivers from driving their vehicles. DADSS in-vehicle sensors are designed to quickly detect whether drivers have been drinking and accurately and precisely measure blood or breath alcohol concentration. If the driver’s alcohol concentration measures at or above a set limit, the vehicle will be prevented from moving. Method The DADSS technology is expected to be ready for real-world applications in the next few years. The implementation of this technology in vehicles promises to prevent thousands of deaths and injuries every year. This paper investigates approaches that have been used in various countries to accelerate the deployment of innovative vehicle safety technologies beginning with its initial implementation in vehicles through to its more widespread use. Results Various approaches were identified that can smooth and accelerate the deployment of in-vehicle alcohol detection devices. Recommendations are made regarding the most promising approaches to use initially and over time, as the body of evidence regarding their effectiveness grows. Conclusions This paper provides guidelines for how best to stimulate the widespread adoption of in-vehicle alcohol-detection technology as a preventive measure so that its life-saving potential can be realized both in the United States and in other countries that may be open to the implementation of DADSS.

Cosine similarity based anomaly detection methodology for the CAN bus

In recent years, vehicular technology has rapidly evolved in terms of the driver’s convenience and safety, along with the convergence of vehicle communication and the expansion of external interfaces. However, the connectivity of the vehicle to the external environment poses a considerable driving risk because of the pre-existing vulnerabilities in the vehicle. Furthermore, most of the in-vehicle networks, such as controller area network (CAN), local interconnect network (LIN), and FlexRay network, are not ready to cope with malicious attacks from the outside. For that reason, various studies have addressed the security issues of the automobiles, as protecting the life and safety of the drivers and passengers is one of the core values of the in-vehicle technology. In the present study, in order to address these critical security issues, we propose an anomaly detection method based on cosine similarity for in-vehicle network through the analysis of self-similarity of the CAN bus. Our main goal is to detect three types of injection attacks without having additional information about the attacks. To this end, we evaluated the performance of the proposed method by measuring the accuracy and detection time using a dataset extracted from two real vehicles in driving and stationary conditions. More specifically, we designed a light-weight feature vector that can accomplish real-time detection and then analyzed the performance in terms of accuracy, recall, and detection time by the time window. In the performance evaluation, we achieved high detection accuracy–namely, 98.93% and 99.18% for KIA Soul in the driving condition and in the stationary condition, respectively, 99.43% and 99.49% for the HYUNDAI YF Sonata in the driving condition and in the stationary condition, respectively. Finally, we also showed that the cosine similarity in the CAN bus is a meaningful feature to identify and classify the types of attacks on target CAN IDs.

Intelligent Group Prediction Algorithm of GPS Trajectory Based on Vehicle Communication

With the rapid development of in-vehicle communication technology and the integration of big data intelligent technology, intelligent algorithms for vehicle communication used to predict traffic flow and location information have been widely used. Aiming at the problem that the gravitational algorithm is difficult to minimize the complex function and easily fall into the local optimum, this paper proposes an improved IGSA algorithm. First, a gridding algorithm is introduced to initialize the population, and under the premise of ensuring the randomness of the initial individuals, improving the ergodicity of the population is conducive to improving the quality of the solution; then, an adaptive location-based update strategy of decreasing inertia weights is proposed. this strategy inherits the advantages of linearly decreasing weights, and adaptively adjusts the weights according to the fitness value to further improve the optimization performance. The optimization simulation of 8 classic test functions shows that the IGSA algorithm is an effective algorithm for solving complex optimization problems. Finally, the IGSA algorithm is used to predict the geographic location problem in the vehicle GPS data. The IGSA algorithm is used to optimize the extreme learning method to optimize the hyperparameters and establish a vehicle GPS data prediction model. Simulation results verify the feasibility of the method.

Age-Related Differences in the Cognitive, Visual, and Temporal Demands of In-Vehicle Information Systems.

In-vehicle information systems (IVIS) refer to a collection of features in vehicles that allow motorists to complete tasks (often unrelated to driving) while operating the vehicle. These systems may interfere, to a greater extent, with older drivers’ ability to attend to the visual and cognitive demands of the driving environment. The current study sought to examine age-related differences in the visual, cognitive and temporal demands associated with IVIS interactions. Older and younger drivers completed a set of common tasks using the IVIS of a representative sample of six different vehicles while they drove along a low-density residential street. Evaluation measures included a Detection Response Task (DRT), to assess both cognitive and visual attention, and subjective measures following each condition using the NASA Task Load Index (TLX). Two age cohorts were evaluated: younger drivers between 21 and 36 years of age, and older drivers between 55 and 75 years of age. Participants completed experimental tasks involving interactions with the IVIS to achieve a specific goal (i.e., using the touch screen to tune the radio to a station; using voice commands to find a specified navigation destination, etc.). Performance of tasks varied according to different modes of interaction available in the vehicles. Older drivers took longer to complete tasks, were slower to react to stimuli, and reported higher task demand when interacting with IVIS. Older drivers stand to benefit the most from advancements in-vehicle technology, but ironically may struggle the most to use them. The results document significant age-related costs in the potential for distraction from IVIS interactions on the road.

Effect of age and secondary task engagement on motor vehicle crashes in a naturalistic setting

ProblemAutomobile crashes are one of the leading causes of death in the United States, especially for younger and older drivers. Additionally, distracted driving is another leading factor in the likelihood of crashes. However, there is little understanding about the interaction between age and secondary task engagement and how that impacts crash likelihood and maneuver safety. MethodData from the Naturalistic Driving Study (NDS), which was part of the Second Strategic Highway Research Program (SHRP2), were used to investigate this issue. ResultsIt was found that the distribution of crashes per one million km driven during the NDS was similar to previous research, but with fewer crashes from older drivers. Additionally, it was found that older and middle-aged drivers engaged in distracted driving more frequently than was expected, and that crashes were significantly more likely if drivers of those age groups were engaged in secondary tasks. However, secondary task engagement did not predict judgment of safe/unsafe vehicle maneuvers. Practical ApplicationsMore research is needed to better understand the interaction of age and distraction on crash likelihood. However, this research could aid future researchers in understanding the likelihood of future use of new in-vehicle technologies for different age groups, as well as provide insight to the engagement patterns of distraction for different age groups.

The Relationship between in-Vehicle Technologies and Self-Regulation among Older Drivers.

The study sought to understand the relationship between in-vehicle technologies (IVTs) and self-regulatory behaviors among older drivers. In a large multi-site study of 2990 older drivers, self-reported data on the presence of IVTs and avoidance of various driving behaviors (talking on a mobile phone while driving, driving at night, driving in bad weather, and making left turns when there is no left turn arrow) were recorded. Self-reports were used to identify whether avoidance was due to self-regulation. Hierarchical logistic regressions were used to determine whether the presence of a particular IVT predicted the likelihood of a given self-regulatory behavior after controlling for other factors. Results suggest that the presence of Integrated Bluetooth/Voice Control systems are related to a reduced likelihood of avoiding talking on a mobile phone while driving due to self-regulation (OR = 0.37, 95% CI = 0.29–0.47). The presence of a Navigation Assistance system was related to a reduced likelihood of avoiding talking on a mobile phone while driving (OR= 0.65, 95% CI = 0.50–0.84) and avoiding driving at night due to self-regulation (OR = 0.80, 95% CI = 0.64–1.00). Present findings suggest in-vehicle technologies may differently influence the self-regulatory behaviors of older drivers.

Effects of Mobile Computer Terminal Configuration and Level of Driving Control on Police Officers' Performance and Workload.

The objective of this study was to assess police officers' performance and workload in using two mobile computer terminal (MCT) configurations under operational and tactical driving conditions. Crash reports have identified in-vehicle distraction to be a major cause of law enforcement vehicle crashes. The MCT has been found to be the most frequently used in-vehicle technology and the main source of police in-vehicle distraction. Twenty police officers participated in a driving simulator-based assessment of driving behavior, task completion time, and perceived workload with two MCT configurations under operational and tactical levels of driving. The findings revealed that using the MCT configuration with speech-based data entry and head-up display location while driving improved driving performance, decreased task completion time, and reduced police officers' workload as compared to the current MCT configuration used by police departments. Officers had better driving but worse secondary task performance under the operational driving as compared to the tactical driving condition. This study provided an empirical support for use of an enhanced MCT configuration in police vehicles to improve police officers' safety and performance. In addition, the findings emphasize the need for more training to improve officers' tactical driving skills and multitasking behavior. The findings provide guidelines for vehicle manufacturers, MCT developers, and police agencies to improve the design and implementation of MCTs in police vehicles considering input modality and display eccentricity, which are expected to increase officer and civilian safety.

Barriers to widespread adoption of plug-in electric vehicles in emerging Asian markets: An analysis of consumer behavioral attitudes and perceptions

Electric vehicles (EVs) are one of the near-term practical solutions in-vehicle technology, which can reduce emissions leading to the greenhouse effect and dependence on fossil fuels that are correlated with conventional vehiclesconventional vehicles (CVs). Several interferences are yet to be overcome for widespread adoption of EVs, despite many benefits provided to the consumers. The tendencies of customers to resist new technology is one of the major barriers in EV adoption. Hence, the policy-related decisions that showing grim concerns of EV have a greater level of success. This research aims to identify potential environmental and socio-technical barriers to purchase of EVs and it determines if governmental policies and awareness of individuals affect the customer decisions purchasing an EV. This research tries to convey valuable insights into perceptions and preferences of technology enthusiasts, individuals who are greatly connected to latest technology developments, and those who are well equipped to sort out the numerous differences between CVs and EVs. These results can provide direction to EV engineer’s decision in including customer preference into EV engineering design. It can also help policymakers in developing transportation and energy policies. A survey-based study was conducted with a sample of 1230 people from urban cities of emerging Asian markets, i.e. India and Srilanka. The data collected were analyzed, which found perception of economic benefits, functional characteristics of EVs, awareness, knowledge, and familiarity of EVs as significant parameters, which directly have an impact on the purchase behavior of fully EVs.

Mitigating Teen Driver Distraction: In-Vehicle Feedback Based on Peer Social Norms.

To investigate the efficacy of in-vehicle feedback based on peer social norms in mitigating teen driver distraction. Distraction is a significant problem among teen drivers. Research into the use of in-vehicle technologies to mitigate this issue has been limited. In particular, there is a need to study whether social norms interventions provided through in-vehicle feedback can be effective. Peers are important social referents for teens; thus, normative intervention based on this group is promising. Socially proximal referents have a greater influence on behavior; thus, tailoring peer norm feedback based on gender may provide additional benefits. In this study, 57 teens completed a driving simulator experiment while performing a secondary task in three between-subject conditions: (a) postdrive feedback incorporating same-gender peer norms, (b) postdrive feedback incorporating opposite-gender peer norms, and (c) no feedback. Feedback involved information based on descriptive norms (what others do). Teens' self-reported frequency of distraction engagement was positively correlated with their perceptions of their peers' engagement in and approval of distractions. Feedback based on peer norms was effective in reducing distraction engagement and improving driving performance, with no difference between same- and opposite-gender feedback. Feedback based on peer norms can help mitigate driver distraction among teens. Tailoring social norms feedback to teen gender appears to not provide any additional benefits. Longer-term effectiveness in real-world settings should be investigated.

Safer vehicles and technology for older adults

Objective: The objective of this study was to address the uptake of safer vehicles and in-vehicle technologies among older adults through a better understanding of extent and use of safer vehicles and awareness/acceptance of new vehicle technologies.Methods: Data were collected from a sample of 501 active older drivers (those who drove at least once a week) through telephone surveys.Results: The sample included experienced and active drivers aged between 65 and 92 years (median 73 years). Though two-thirds indicated that safety was a priority in their vehicle choice, other factors such as reliability and vehicle make were more important. There was low awareness of driver assist safety features, particularly among the oldest drivers. Only one-quarter of drivers were receptive to paying extra for safety features, and there was no interest in paying more for driverless vehicles.Conclusions: The findings showed an overall low awareness and acceptance of in-vehicle safety features; however, where there was some awareness, there was greater interest in purchasing vehicles with safety features. More effort should be undertaken to develop and prioritize a set of recommendations to increase use of safe vehicles by older drivers.

Driven to comment: Learning from older drivers impressions of in-vehicle technologies

Many challenges associated with aging faced by older drivers may be attenuated by advancements of in-vehicle technologies. One class in particular, In Vehicle Information Systems (IVIS), refers to a collection of features and functions that allow motorists to complete tasks in addition to operating the vehicle. Little is known about how interactions with IVIS may impact older drivers. This study explored comments provided by drivers while completing goal-oriented IVIS tasks in six vehicles; collected via survey, and in an open-ended prompt. Two age cohorts were evaluated: younger drivers between 21-36 years of age, and older drivers between 55-75 years of age. Analyses of comments investigated differences in the thematic content and emotional valence present in comments. Results indicated that older and younger drivers were surprisingly symmetrical in their responses pertaining to valence and themes, and older drivers were more willing to take time to become familiar with IVIS.

On-Road and In-Vehicle Delivery of Service Signs: Effects of Information Source and Age

In-vehicle technologies for communicating information to drivers have realized increasing use in recent years. While most attention has been paid to in-vehicle displays for presenting safety-related information, such as warnings, few studies have explored communication of non-safety-related information with in-vehicle displays. This simulated driving study examined driver performance in vehicle control and sign identification, when processing service logo information from on-road signs or an in-vehicle display. Findings suggest that in-vehicle displays, on-road signage, or both allowed drivers to identify service logos with a high accuracy and a relatively low level of workload. The use of in-vehicle displays either alone or simultaneously with on-road signage produced lower speed deviations therefore better vehicle control. Age differences were observed in vehicle control as well, suggesting the need for personalization of sign messages according to individual characteristics. This study is an initial step to examine the use of in-vehicle displays for messaging service logos as an example of non-safety-related information. The study is ongoing, and findings could provide a basis for in-vehicle display and on-road sign design for non-safety-related information.

An Application of Machine Learning for Police Mobile Computer Terminal Usability Evaluation

Police in-vehicle technologies especially mobile computer terminals (MCTs) are the major cause of motor vehicle crashes for law enforcement officers. Previous studies have found several usability issues with the design of MCT interfaces. The objective of this study was to develop an algorithm for classification of MCT interface usability based on a combination of officer performance, visual attention allocation, and subjective measures. It was found that speed deviation, secondary task completion time, off-road fixation frequency and glance duration are informative features that associate with MCT usability. The developed algorithm has the potential to be used in MCT design and development process to ensure efficient interaction in multi-tasking situations of driving and using the MCT.

Road Accidents Detection, Data Collection and Data Analysis Using V2X Communication and Edge/Cloud Computing

With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment; principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data; however, this feature is not yet commercially available in the OBU of the vehicle; therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data.

RAMT

Recently a class of new in-vehicle technologies based on off-the-shelf mobile devices have been developed to improve driving safety and experience. For instance, wearables like the smartwatches are utilized to monitor the action of the driver and detect possible secondary tasks. Moreover, wearables can allow a driver to use gesture for in-vehicle controls, reducing distractions to driving. The accuracy of these systems can be significantly improved by tracking the real-time attitude of mobile devices. This paper proposes a novel system called Real-time Attitude and Motion Tracking (RAMT) that can enable a mobile device to accurately learn the coordinate system of a moving vehicle, and hence track its attitude and motion in real time. RAMT consists of a series of lightweight algorithms to sense the vehicle's movement and calculate the device's attitude. It provides a solution for trajectory-based gesture recognition. We have implemented RAMT on a smartphone and a smartwatch and evaluated the performance in 10 real driving trips. Our results show that the overall error of the coordinate system alignment is around 5° for the smartphone and 10° for the smartwatch, and over 84% of customized hand gestures can be accurately recognized with the result of RAMT. A video demo of RAMT is available at https://youtu.be/9rZp7HxyRts.

Evaluation of in-vehicle technologies to prevent unlicensed driving in Queensland and Victoria

Unlicensed driving is a serious problem in many Australian states, with unlicensed driving-related crashes (UDC) costing up to $304 million per year in Queensland, and $176 million in Victoria. In this paper, we present a Benefit-Cost Ratio (BCR) analysis of a set of Intelligent Transportation Systems technologies aimed at preventing unlicensed driving by verifying the driver’s identity through biometric technology, as well as the validity of their licence. Utilised together, the technology would essentially take the form of a licence interlock. The goal of this program of research (from which this paper stems) was to provide preliminary recommendations as to which technology is the most beneficial and should be implemented as part of a government-led program increasing the functionalities of electronic driving licences (EDL). The corresponding BCR analysis revealed that fingerprints and finger vascular patterns recognition technologies were found to systematically have the best BCRs. In regard to the most effective manner to implement the technology, a corresponding investigation with five scenarios revealed that the greatest benefits would be achieved with: (a) a mandatory system for all banned drivers (e.g., suspensions & disqualifications), and (b) a mandatory system for banned drivers under the age of 21 only. Scenario (b) performs extremely well, with returns of up to 16 times the investment with a simple fingerprint-based interlock. Although often more modest, all systems were found to have BCRs above 1 in all of the implementation scenarios except one. This paper further outlines the findings in regard to addressing the significant problem of unlicensed driving via emerging technologies.

Smart In-Vehicle Technologies and Older Drivers: A Scoping Review

In-vehicle technologies may decrease crash risk in drivers with age-related declines. Researchers determined the impact of in-vehicle information systems (IVIS) or advanced driving assistance systems (ADAS) on driving. Through a scoping review, the effect of IVIS or ADAS on older drivers' convenience (i.e., meets one's needs), comfort (i.e., physical or psychological ease), or safety (i.e., absence of errors or crashes) was examined. Researchers synopsized findings from 28 studies, including driving simulators and on-road environments. Findings indicated that IVIS or ADAS enhanced safety and mitigated age-related declines. Notably, IVIS may reduce cognitive workload, but may jeopardize safety if the systems are overly complicated. The ADAS enhanced safety and comfort by increasing speed control, lane maintenance, and braking responses. However, no studies addressed convenience. In-vehicle technologies may enhance safety and comfort while driving, if one's cognitive workload is not compromised. Naturalistic studies are needed to elucidate the risks and benefits of IVIS and ADAS for older drivers.

Consumer Information Potpourri: Instructional and Operational Variability Among Passenger Vehicle Automated Systems

Even owners of the most advanced vehicles often have little understanding of the available in-vehicle technology. Accessible safety-critical information and standard instructional and operational components are potential routes to increase drivers’ knowledge. This article presents a review of information obtained from automobile manufacturers’ websites and operator manuals aimed toward passenger vehicle automated system consumers. This review revealed target areas for researchers, manufacturers, and policy makers to consider. Systems offering comparable functionality varied greatly in their nomenclature, type of feedback provided to drivers, and the accessibility of information about the systems. Also, information pertaining to systems limits was difficult to obtain.

Improving Safe Mobility: An Assessment of Vehicles and Technologies among a Large Cohort of Older Drivers

Evidence suggests that older driver safety may be improved by good vehicle maintenance, in-vehicle advanced technologies, and proper vehicle adaptations. This study explored the prevalence of several measures of vehicle maintenance and damage among older drivers through inspection of their vehicles. We also investigated the prevalence of in-vehicle technologies and aftermarket adaptations. Vehicle inspections were conducted by trained research staff using an objective, standardized procedure. This procedure, developed by a multidisciplinary team of researchers, was based on a review of inspection checklists used by automobile dealerships and the project team's expertise. The study used baseline data from vehicles of 2988 participants in the multi-site Longitudinal Research on Aging Drivers (LongROAD) study. Among this cohort, vehicles were well maintained, had little damage, and contained a range of advanced technologies but few aftermarket adaptations. Implications of study findings for occupational therapy practice are discussed.

Mindfulness Predicts Driver Engagement in Distracting Activities

Distracted driving is a major public health concern because of its potential costs of injury, mortality, and property damage. Understanding the psychological factors that underlie drivers’ willingness to engage in distracting activities despite the clear safety risks can help to identify interventions to mitigate this dangerous behavior. This study examined if mindfulness, defined as one’s attention to and awareness of oneself and the present situation, predicts driver engagement in a wide range of distracting activities, including in-vehicle technology and non-technology-based distraction sources, daydreaming/mind wandering, and distractions external to the vehicle. A total of 312 drivers completed an online survey assessing levels of mindfulness and the frequency with which they engaged in a range of potentially distracting activities. The results showed that while engagement in distracting activities is common, mindfulness was negatively associated with the frequency of driver engagement in all distraction sources studied, apart from passenger interaction. Our results suggest that a single mindfulness intervention could potentially reduce driver engagement in multiple distracting activities at once, and therefore have significant utility as a distraction mitigation technique.