In-vehicle Systems Research Articles

A quantitative study of Cooperative Awareness Messages in production VANETs

In Vehicular Ad-hoc Networks (VANETs), vehicles gather Cooperative Awareness Messages (CAMs) sent from other vehicles via wireless broadcast. Each received message has to be processed by an in-vehicle system. In series implementations, such an in-vehicle system needs to cope with limited resources whose capacity is not yet defined. Therefore, information about the received CAM rate is a crucial input for the development of series VANET products. CAMs from distant vehicles are less likely to be received than those of nearby vehicles. Designers of applications leveraging CAM information are interested in the frequency of received CAMs originating from vehicles depending on their distance. In this paper, we study future CAM rates depending on various parameters. We set up a road traffic simulation for selected highway scenarios. We estimate the rates of generated CAMs and introduce the notion of relative channel load. We present a new approximative channel model to determine a vehicle’s message reception probability. That model is used to simulate the rates of received CAMs for each vehicle. Moreover, we investigate the origin of received CAMs and times between consecutive CAMs received from the same sender (inter-reception times) depending on distance. Most results depend on the penetration rate of VANET technology that will increase in the near future. We derive approximative formulae and use them to validate our simulation results. They are quite accurate, and so they may also serve for simple forecasts. The results from our analysis show that the rates of generated and received CAMs lead to several challenges for the design of an efficient and robust VANET implementation.

Evaluation of the driver’s mental workload: a necessity in a perspective of in-vehicle system design for road safety improvement

Human factors research and debate related to mental workload have been going on for decades since the 60's (McKenzie et al. 1966) and is still happening (Finomore et al. 2013). The raised issues are: is it useful (do we need the concept of mental workload or do we have to banish it for good? Leplat 2002), is it scientifically credible (Dekker et al. 2010), and, in case of a positive answer, how to measure it (Jex 1988). In the context of the driving task, human factors research is abundant and diversified, aiming at a better understanding of driver behavior and functional capacities in terms of perception, cognition, and motor processes in order to improve road safety (Lee 2008), drivers' mental workload being an important issue to consider in this framework (Dick de Waard 1996). This problematic is even more crucial since the deployment of onboard Intelligent Transport System in the vehicles (Carsten and Nilsson 2001), as human factors have the responsibility to evaluate whether these innovative systems really support the driving task or, on the contrary, lead to distraction and increase mental workload, with potential dramatic consequences in terms of road safety. So, since the beginning of research in this area, the objectives have been to establish methods of assessing fluctuations in mental workload that are sensitive to the various aspects of attentional processing requirements in relation to both external environmental conditions, such as traffic density as well as in-vehicle conditions, such as competing visual and auditory displays (Pauzie´ and Amditis 2010). Workload can be defined as a hypothetical construct that represents the cost incurred by a human operator to achieve a particular level of performance (Hart 1986). Driving performance and the driver's mental workload are both relevant and complementary parameters to consider, knowing that they can vary independently (Yeh and Wickens 1988). Indeed, if the complexity of the task increases, the driver is able to maintain a stable performance to a certain degree, by increasing effort. Keywords: Driver distraction; Language: en

Effect of type of lead vehicle on following headway behaviour in mixed traffic

Purpose – There is gap in literature on understanding of the issues of following headway behaviour of the driver and a lack of sufficient data in different traffic conditions. The purpose of this paper is to find the effects of type of lead vehicle on following headway in mixed traffic condition in India on different category of roads and flow. Design/methodology/approach – Real-world headway data were collected through video and extracted. Data were analysed using tools and statically approach was adopted to present the results in detail. Findings – Results shows the impact of type of lead vehicle on driver following time headway behaviour under different level of traffic and types of road characteristics. It was found that driver following behaviour is affected by the type of lead vehicle. It also shows that drivers are inconsistent in their choice of headway. Research limitations/implications – This research has special strategic study area of India in typical two cities Silchar and Shillong of northeast region of India. The traffic characteristic and composition is quite different as compared to other cities of India. Therefore the study results cannot be generalized for whole India. Practical implications – The result of the study has focused on impact of type of lead vehicle on following behaviour. This can be useful to safety reduction and changing the driver behaviour through education and display of information. However, the real application of this result is to be implemented by local transport and road managing authority to reduce accidents and increase safety of drivers. Originality/value – In mixed traffic conditions, the impact of type of lead vehicle on following behaviour affects the safety of drivers and the accounting for such behaviour is never been explored in mixed traffic condition. If the study is implemented, it can be useful to simulation modeller and intelligent transport systems (ITS) to design and operate many in-vehicle systems for smooth traffic processes.

Optimal Scheduling Algorithm in Vehicular Real Time System

In this paper, we mainly discuss the optimal scheduling algorithms in Low-end ECU and In-vehicle information system. For Low-end ECU, we propose an optimal scheduling algorithm. This algorithm can guarantee schedulability of mandatory parts in periodic tasks, guarantee aperiodic tasks and minimize the average scheduling error of optional parts in periodic tasks. In-vehicle information system is a multi-constraint real-time and non-real-time application coexisted application system. To meet the system scheduling requirements, a feedback algorithm based on the Constant Bandwidth Server is designed to control the fraction of CPU bandwidth allocation and a precise mathematical model is provided. Finally, the experimental results prove the effectiveness of our framework and algorithm.

Augmented Affective-Cognition for Usability Study of In-Vehicle System User Interface

Usability of in-vehicle systems has become increasingly important for ease of operations and safety of driving. The user interface (UI) of in-vehicle systems is a critical focus of usability study. This paper studies how to use advanced computational, physiology- and behavior-based tools and methodologies to determine affective/emotional states and behavior of an individual in real time and in turn how to adapt the human-vehicle interaction to meet users' cognitive needs based on the real-time assessment. Specifically, we set up a set of physiological sensors that are capable of collecting EEG, facial EMG, skin conductance response, and respiration data and a set of motion sensing and tracking equipment that is capable of capturing eye ball movement and objects which the user is interacting with. All hardware components and software are integrated into an augmented sensor platform that can perform as “one coherent system” to enable multimodal data processing and information inference for context-aware analysis of emotional states and cognitive behavior based on the rough set inference engine. Meanwhile subjective data are also recorded for comparison. A usability study of in-vehicle system UI is shown to demonstrate the potential of the proposed methodology.

Reliability of an in‐vehicle warning system for railway level crossings – a user‐oriented analysis

This study analyses the reliability of an in-vehicle warning system developed in Finland during 2008–2010. The system is based on the positioning of trains using GPS, calculation of the states of level crossings on a server and in-vehicle equipment that retrieves information about the states of level crossings from the server. Information about the reliability of the system is very relevant for accurate estimation of the impacts of the system and for estimating the potential for improvements to it. The study starts with a description of the system under analysis, continues by defining the concept of reliability and provides an estimate for the reliability of the system from the user point of view. To achieve this objective, the study defines the relevant concepts and describes a methodology for analysis of the reliability of the system. The main input to the analysis of reliability includes a brief overview of existing concepts related to the reliability of in-vehicle ITS systems and empirical data obtained in a field test carried out in southern Finland. The analysis shows that the expected functionality has been achieved, but the reliability level of the pilot system needs improvement, especially reduction in the share of missed alarms.

On-Road Driver Monitoring System Based on a Solar-Powered In-Vehicle Embedded Platform

This study presents an on-road driver monitoring system, which is implemented on a stand-alone in-vehicle embedded system and driven by effective solar cells. The driver monitoring function is performed by an efficient eye detection technique. Through the driver’s eye movements captured from the camera, the attention states of the driver can be determined and any fatigue states can be avoided. This driver monitoring technique is implemented on a low-power embedded in-vehicle platform. Besides, this study also proposed monitoring machinery that can detect the brightness around the car to effectively determine whether this in-vehicle system is driven by the solar cells or by the vehicle battery. On sunny days, the in-vehicle system can be powered by solar cell in places without the vehicle battery. While in the evenings or on rainy days, the ambient solar brightness is insufficient, and the system is powered by the vehicle battery. The proposed system was tested under the conditions that the solar irradiance is 10 to 113 W/m2and solar energy and brightness at 10 to 170. From the testing results, when the outside solar radiation is high, the brightness of the inside of the car is increased, and the eye detection accuracy can also increase as well. Therefore, this solar powered driver monitoring system can be efficiently applied to electric cars to save energy consumption and promote the driving safety.

Car drivers’ preferences for ISA policy measures

Intelligent Speed Adaptation (ISA), an in-vehicle system that can either warn the driver or directly limit the vehicle’s speed when the speed limit is reached, is generally believed to have a large potential to increase road safety. However, policy makers hesitate to take policy measures that may increase ISA use. Public acceptance of ISA or policy makers’ perception of it is regarded to play an important role in this. This paper aims to increase this insight by reporting car drivers’ preferences for ISA policy measures based on stated choice experiment conducted in the Netherlands. Respondents made choices between various implementation strategies (mandatory ISA and voluntary ISA with financial incentives) given a chosen policy measure. The policy measure describes which drivers group (speed offenders, professional drivers or all drivers) is targeted and which ISA type (warning or limiting) is stimulated. The results point out that car drivers especially prefer that policy makers would impose ISA on speed offenders and to a lesser extent also on professional drivers, while they prefer a voluntary ISA for themselves. Use of voluntary ISA can be stimulated by offering financial incentives, of which purchase subsidy is preferred above annual tax cuts. Furthermore, car drivers prefer warning ISA for themselves and also for professional drivers, while they prefer limiting ISA for speed offenders. In addition, the results indicate that females and the older age group prefer ISA policy measures more than males and young drivers, but overall car drivers’ preferences seem to be rather homogeneous.

Improvements and Implementation of Integrated In-Vehicle Monitoring System

An In-Vehicle Monitoring System (IVMS) monitors the location and status of the remote vehicle status. In this paper, we introduce an integrated IMVS suit for various vehicles types. Based on the state of art IMVS, this system realized some improvements on it. These improvements include report interval, fuel consumption, spotting the target, administrative boundary electronic fence, and big data. These improvements amplify the practicability, expand the use scope and improve the efficiency of IVMS.

Eco-driving Versus Green Wave Speed Guidance for Signalized Highway Traffic: A Multi-vehicle Driving Simulator Study

New in-vehicle systems provide the driver with speed advises through the variable message signs and the use of an in-car display. In this paper, two dynamic speed guidance strategies (green wave speed guidance strategy (GWSGS) and eco-driving speed guidance strategy (EDSGS)) through in-car display were tested. A new multi-vehicle driving simulator platform taking into account drivers interactions was built, and the two strategies for highway system were programmed through the script language provided by Virtools software. To evaluate the effectiveness of the overall strategies, 15 typical drivers were recruited to take part in the speed guidance experiments. It was found that the number of stops is both significantly reduced for the vehicles with the GWSGS and EDSGS. Compared with the vehicles without speed guidance, the fuel consumption and CO2 emissions can be reduced by 25% and 13% under the EDSGS and GWSGS respectively. The eco-driving vehicle's velocity trajectory is smoother than that of the green wave vehicle, and the average compliance rate of EDSGS is higher than GWSGS. The EDSGS showed more benefits than the GWSGS.

A Saliency-Based Search Model

Driver distraction is a leading cause of motor vehicle crashes. As more in-vehicle systems are developed, they represent increasing potential for distraction. Designers of these systems require a quantitative way to assess their distraction potential that does not involve time-consuming test track or simulator testing. A critical contribution to driver distraction concerns the search time for items in an in-vehicle system display. This study tests the saliency map’s ability to predict search time, and proposes a potential application of the saliency map in assessing driver distraction. Empirical data for search tasks were collected and used to test a modified driver model based on the saliency map. The results show that the modified saliency map can predict search time, and suggest that the driver model could be used to understand how design features influence the bottom-up visual search process. More broadly, such a model can complement guidelines and user testing to help designers to incorporate human factors considerations earlier in the design process.

Contour Extraction Based on Improved Snake Model and its Application in Vehicle Identification

Contour curve is an important shape feature for vehicle recognition and it is a hard work to extraction it from complex dynamic traffic video for in-vehicle detection system. Snake Model is used to automatically extract the object contour curve proposed by Kass et al, but it is inability for traffic objects. Presented here is a novel approach for extracting vehicle contour curve by combining stereo vision with Snake Model. In this paper, Stereo vision is first used to segment vehicle from traffic background, then Snake Model is adopted to obtain complete contour curve. In view of classical Snake model is easily affected by noise, here we propose a improved Snake model by combining corner detection technology with Distance Potential Snake Model. Moreover, a vehicle identification method based on contour curve is presented. The method presented here was tested on complex traffic scenes and the corresponding results prove the efficiency of our proposed method.

Towards intelligent in-vehicle sensor database management systems

Due to the evolution of technologies for sensor and wireless communication, there has been increasing attention to research on an intelligent vehicle that supports safe driving by exploiting large traffic data gathered from traffic environments such as vehicles and road side units, as well as data gathered from sensors mounted on the vehicle. In this paper, we study an in-vehicle sensor database management system (DBMS). In the proposed approach, simply called in-vehicle DBMS approach, DBMS inside the ego-vehicle manages, gathers, and processes traffic and sensor data onboard such as signal data and multimedia data including map and image data. We classify the requirements of applications using the in-vehicle DBMS into data modeling and query processing. We also propose a system architecture for an in-vehicle DBMS which solves those issues and discuss database techniques offered by the system.

An Experimental Analysis of Drivers Attitudes towards In-Vehicle Warning System at Stop Sign Controlled Intersection

Most traffic accidents occur at unsignalized intersections, mainly due to inappropriate behavior of non-priority vehicles. The authors have developed an advanced Intelligent Speed Adaptation (ISA) system with GPS/GIS to provide warning to stop failure vehicles at unsignalized intersections. In this study, experiments related to driver attitudes toward stop sign warning were carried out. At a drivers training course, drivers attitudes were tested using a vehicle equipped with the warning system in order to ascertain appropriate timing of warnings when approaching intersections. The drivers evaluation and willingness-to-pay for the warning system were also analyzed using an interview survey answered by testers.

Design of CAN-FlexRay Gateway based on Node Mapping Methods for In-Vehicle Network System

The In-Vehicle Network System is a main channel to transmit electronic signals among each automotive node. In order to share the node information from both of chassis and body networks in automobiles, the gateway system is used to realize the communication between CAN and FlexRay systems. In this paper, a modified gateway system based on the node mapping method, the node slotting method, and the corresponding operation algorithm will be proposed. Through the modified gateway system, repeated remodifying problems are solved that is changes of information or ID during transmitting information between CAN and FlexRay systems. Additionally, improvements in the reliability and the amalgamation of the In-Vehicle Network System are shown in this paper.

FlexRay 네트워크 시스템을 위한 FIBEX 자동 생성 알고리즘에 관한 연구

As vehicles become more intelligent for safety and convenience of drivers, in-vehicle networking systems such as controller are network (CAN) have been widely used due to increasing number of electronic control unit (ECU). Recently, FlexRay was developed to replace CAN protocol in chassis networking systems, to remedy the shortage of transmission capacity and unsatisfactory real-time transmission delay of conventional CAN. However, it is difficult for vehicle network designers to calculate platform configuration registers (PCR) and determine a base cycle or slot length of FlexRay. To assist vehicle network designers for designing FlexRay cluster, this paper presents automatic field bus exchange format (FIBEX) generation algorithm from CANdb information, which is de-facto standard database format for CAN. To design this program, structures of FIBEX, CANdb and relationship among PCR variables are analyzed.

Comparative effects of eco-driving initiatives aimed at urban bus drivers – Results from a field trial

A field trial is used to investigate effects of two programmes aimed at encouraging bus drivers to develop and maintain ecological driving behaviour. Drivers on one bus line were divided into three groups, one received feedback from an in-vehicle system, the second received the same feedback coupled with personal training sessions, and the third acting as a control. A 6.8% fuel saving and large decreases in instances of harsh deceleration and speeding were found, but with no difference in the effect of the two eco-driving strategies. The drivers reported perceived gains in theoretical knowledge of eco-driving, but found it more difficult to put that knowledge into practice. Several contextual factors were found to limit drivers’ to eco-driving, most noticeably shaped by their work tasks, but also the commitment of the company where they were employed.

Assessment of risky driving caused by the amount of time focused on an in-vehicle display system

Korea is currently experiencing a rapidly increasing distribution rate of in-vehicle display devices, such as navigation or DMB displays, owing to remarkable advances in IT. At the same time, the number of traffic accidents and traffic violations is increasing due to the distraction of drivers’ attention by such devices. In particular, in-vehicle display devices such as navigation systems temporarily distract drivers’ visual or cognitive attention when they perform a unit task. Accordingly, it is necessary to prepare adequate standards to regulate in-vehicle display devices, especially in Korea. There are few empirical studies that have employed experiments to support such regulation. In this study, an experiment was conducted using a driving simulator to establish the proper standards regarding the maximum distraction time per unit task that can be allowed without causing any disturbance in safe driving. A total of 25 participants participated in the experiment. The distraction time was controlled by asking participants to perform the two tasks at once: while participants were driving as a primary task, they performed secondary task that count the number of intersections between the start point and the arrival point displayed on the screen. The results showed that the 2.0 second condition differed from the controlled condition in the deviation in the distance from the preceding vehicle, speed, and steering wheel movement, whereas there were no differences between the controlled condition and the 1.0 or 1.5 second condition. Finally, the limitations of the study and the implications of the findings with regard to future studies and application of the Korean version of guidelines for in-vehicle display devices are discussed.

Probabilistic Modeling of Erroneous Human Response to In-Vehicle Route Guidance Systems: A First Look

An integral component of (in-vehicle) navigation systems is the determination of optimal routes to the desired destination. An implicit assumption in the underlying algorithms is that people do not make mistakes when following the prescribed routes. This is, however, not always consistent with reality, especially when driving in unfamiliar environments. This article presents a first look at the possibility of mistakes when driving. This possibility is formalized in a Markov decision process. It is demonstrated that quite paradoxical situations can occur when accounting for mistakes. As the most interesting—but perhaps extreme—example, we have shown that under certain conditions, it is no longer optimal to recommend drivers to take the shortest route. Instead, a longer route (in certain cases even the longest!) becomes optimal. Numerical results are provided throughout the article to reveal the fundamental properties of this problem.

Comparisons of Discretionary Passenger Vehicle Idling Behavior by Season and Trip Stage with Global Positioning System and Onboard Diagnostic Devices

This study addresses the comparisons of discretionary passenger vehicle idling by using field data collected from 20 volunteers in Vermont. Each volunteer participated in two 2-week data collection periods, one in the summer and one in the winter. Overall, 15.6% of vehicle-operating time was spent idling, consistent with the limited existing data on this topic. In addition, the paper describes a processing method used with an in-vehicle Global Positioning System and onboard diagnostic data that allows discretionary idling at the start and end of trips to be separated from the in-travel idling related to traffic or traffic control. Discretionary idling accounted for more than 6.5% of vehicle operating time. Discretionary winter idling events were found to be longer than summer idling events and, for idling events greater than 60 s, trip-start idling was found to be longer than trip-end idling. Both of these results reaffirm previous findings suggesting that there are opportunities for behavioral changes to reduce idling. The method used to extract discretionary idling is promising for widespread use and large sample data collection efforts. This method will be critical for the many communities that lack robust idling data when considering the costs and benefits of idling behavior change initiatives.