Signal detection theory in applied tasks: The case of hazard perception in driving

Fuzzy signal detection analysis can be a useful complementary technique to traditional signal detection theory analysis methods, particularly in applied settings. For example, traffic situations are better conceived as being on a continuum from no potential for hazard to high potential, rather than either having potential or not having potential. This study examined the relative contribution of sensitivity and response bias to explaining differences in the hazard perception performance of novices and experienced drivers, and the effect of a training manipulation. Novice drivers and experienced drivers were compared (N = 64). Half the novices received training, while the experienced drivers and half the novices remained untrained. Participants completed a hazard perception test and rated potential for hazard in occluded scenes. The response latency of participants to the hazard perception test replicated previous findings of experienced/novice differences and trained/untrained differences. Fuzzy signal detection analysis of both the hazard perception task and the occluded rating task suggested that response bias may be more central to hazard perception test performance than sensitivity, with trained and experienced drivers responding faster and with a more liberal bias than untrained novices. Implications for driver training and the hazard perception test are discussed.

Multisensorial obstacles detection and classification for ADAS and autonomous driving

A reliable perception of the real world is a key-feature for an autonomous vehicle and the Advanced Driver Assistance Systems (ADAS). Obstacles detection (OD) is one of the main components for the correct reconstruction of the dynamic world. Historical approaches based on stereo vision and other 3D perception technologies (e.g. LIDAR) have been adapted to the ADAS first and autonomous ground vehicles, after, providing excellent results. The obstacles detection is a very broad field and this domain counts a lot of works in the last years. In academic research, it has been clearly established the essential role of these systems to realize active safety systems for accident prevention, reflecting also the innovative systems introduced by industry. These systems need to accurately assess situational criticalities and simultaneously assess awareness of these criticalities by the driver; it requires that the obstacles detection algorithms must be reliable and accurate, providing: a real-time output, a stable and robust representation of the environment and an estimation independent from lighting and weather conditions. Initial systems relied on only one exteroceptive sensor (e.g. radar or laser for ACC and camera for LDW) in addition to proprioceptive sensors such as wheel speed and yaw rate sensors. But, current systems, such as ACC operating at the entire speed range or autonomous braking for collision avoidance, require the use of multiple sensors since individually they can not meet these requirements. It has led the community to move towards the use of a combination of them in order to exploit the benefits of each one. Pedestrians and vehicles detection are ones of the major thrusts in situational criticalities assessment, still remaining an active area of research. ADASs are the most prominent use case of pedestrians and vehicles detection. Vehicles should be equipped with sensing capabilities able to detect and act on objects in dangerous situations, where the driver would not be able to avoid a collision. A full ADAS or autonomous vehicle, with regard to pedestrians and vehicles, would not only include detection but also tracking, orientation, intent analysis, and collision prediction. The system detects obstacles using a probabilistic occupancy grid built from a multi-resolution disparity map. Obstacles classification is based on an AdaBoost SoftCascade trained on Aggregate Channel Features. A final stage of tracking and fusion guarantees stability and robustness to the result.

Organizations driving positive social change:a review and an integrative framework of change processes

Academic and practitioner interest in how market-based organizations can drive positive social change (PSC) is steadily growing. This paper helps to recast how organizations relate to society. It integrates research on projects stimulating PSC – the transformational processes to advance societal well-being – which is fragmented across different streams of research in management and related disciplines. Focusing on the mechanisms at play in how organizations and their projects affect change in targets outside of organizational boundaries, we 1) clarify the nature of PSC as a process, 2) develop an integrative framework that specifies two distinct PSC strategies, 3) take stock of and offer a categorization scheme for change mechanisms and enabling organizational practices, and 4) outline opportunities for future research. Our conceptual framework differentiates between surface- and deep-level PSC strategies understood as distinct combinations of change mechanisms and enabling organizational practices. These strategies differ in the nature and speed of transformation experienced by the targets of change projects and the resulting quality (pervasiveness and durability), timing, and reach of social impact. Our findings provide a solid base for integrating and advancing knowledge across the largely disparate streams of management research on Corporate Social Responsibility, Social Entrepreneurship, and Base of the Pyramid, and open up important new avenues for future research on organizing for PSC and on unpacking PSC processes.

The influence of high contrast acuity and normalised low contrast acuity upon self-reported situation avoidance and driving crashes

The aim of this study was to determine the cues used to signal avoidance of difficult driving situations and to test the hypothesis that drivers with relatively poor high contrast visual acuity (HCVA) have fewer crashes than drivers with relatively poor normalised low contrast visual acuity (NLCVA). This is because those with poorer HCVA are well aware of their difficulties and avoid dangerous driving situations while those poorer NLCVA are often unaware of the extent of their problem. Age, self-reported situation avoidance and HCVA were collected during a practice based study of 690 drivers. Screening was also carried out on 7254 drivers at various venues, mainly motorway sites, throughout the UK. Age, self-reported situation avoidance and prior crash involvement were recorded and Titmus vision screeners were used to measure HCVA and NLCVA. Situation avoidance increased in reduced visibility conditions and was influenced by age and HCVA. Only half of the drivers used visual cues to signal situation avoidance and most of these drivers used high rather than low contrast cues. A statistical model designed to remove confounding interrelationships between variables showed, for drivers that did not report situation avoidance, that crash involvement decreased for drivers with below average HCVA and increased for those with below average NLCVA. These relationships accounted for less than 1% of the crash variance, so the hypothesis was not strongly supported. © 2002 The College of Optometrists.

Understanding mobile phone usage while driving:mini-bus and taxi drivers' experiences in Istanbul

In emerging markets, the amount of mobile communication and the number of occasions mobile phones are used are increasing. More and more settings appropriate or not for mobile phone usage are being exposed. Although prohibited by many governments, there is evidence that use of new mobile devices while driving are somehow becoming current everyday practice, hence legitimatizing usage for many users. Dominant dangerous behavior in the absence of enforced legal framework is being deployed and has become routine for many m-users. This chapter adopts a qualitative case study approach (20 cases) to examine the public transport drivers' motives, logic and legitimacy processes. The question which these issues raise in the light of advancing m-technologies is: How do, in the context of emerging market, undesired emerging routines enactment get to be reflected upon and voluntarily disregarded to maximize the benefits of m-technologies while minimizing their drawbacks? Findings point out at multiple motives for usage including external social pressure through the ubiquitous 24/7 usage of mtechnology, lack of alternative communication protocol, real time need for action and from an internal perspectives boredoms, lack of danger awareness, blurring of the boundaries between personal and business life and lack of job fulfillment are uncovered as key factors. As secondary dynamic factors such as education, drivers work' histories, impunity, lack of strong consumer opposition appear central in shaping the development of the routines. © 2011, IGI Global.