Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design and achieve solutions for optimal design features before implementation. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since vehicle movements are not as flexible as pedestrian movements, velocity angle constraints are included for vehicles. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs

Adaptive driver modelling in ADAS to improve user acceptance: A study using naturalistic data

Accurate understanding of driver behaviour is crucial for future Advanced Driver Assistance Systems (ADAS) and autonomous driving. For user acceptance it is important that ADAS respect individual driving styles and adapt accordingly. Using data collected during a naturalistic driving study carried out at the University of Southampton, we assess existing models of driver acceleration and speed choice during car following and when cornering. We observe that existing models of driver behaviour that specify a preferred inter-vehicle spacing in car-following situations appear to be too prescriptive, with a wide range of acceptable spacings visible in the naturalistic data. Bounds on lateral acceleration during cornering from the literature are visible in the data, but appear to be influenced by the minimum cornering radii specified in design codes for UK roadway geometry. This analysis of existing driver models is used to suggest a small set of parameters that are sufficient to characterise driver behaviour in car-following and curve driving, which may be estimated in real-time by an ADAS to adapt to changing driver behaviour. Finally, we discuss applications to adaptive ADAS with the objectives of improving road safety and promoting eco-driving, and suggest directions for future researc

Drivers’ behaviour modelling for virtual worlds

In this paper we present a study that looks at modelling drivers’ behaviour with a view to contribute to the problem of road rage. The approach we adopt is based on agent technology, particularly multi-agent systems. Each driver is represented by a software agent. A virtual environment is used to simulate drivers’ behaviour, thus enabling us to observe the conditions leading to road rage. The simulated model is then used to suggest possible ways of alleviating this societal problem. Our agents are equipped with an emotional module which will make their behaviours more human-like. For this, we propose a computational emotion model based on the OCC model and probabilistic cognitive maps. The key influencing factors that are included in the model are personality, emotions and some social/personal attributes

Driving offences

Copyright @ 2010, Taylor & Francis Group. This material is posted on this site with the permission of the publishers.This chapter on driving offences will largely follow the template of earlier chapters except that owing to their vast number, a limited selection only will be examined based on their high volume, seriousness and public concern. The first section will define what driving offences are, how they developed alongside the emerging car culture, and it will consider the contemporary landscape. The second section will give a general overview of patterns and trends, those most likely to engage in road traffic offending, and kinds of explanations voiced by drivers and theoretical approaches used. The next three sections will follow a similar pattern and focus on speeding, bad driving – mostly dangerous and careless offences, and impaired driving – mostly drink-driving but mentioning drug-driving and fatigued driving. In addition, contemporary debates and key issues concerning each will be considered, along with official responses to each offence category comprising court-based penalties and other measures. The final section will draw the key threads and themes together, noting the danger of work-related driving. Given that up to a third of all road traffic collisions involve somebody at work at the time accounting for up to 20 fatalities and 250 serious injuries every week (DfT and HSE, 2003), the importance of reducing traffic offending is clear

Factors influencing learner driver experiences [Road Safety Grant Report 2009-003]

When compared with more experienced drivers, new drivers have a higher crash risk. This study examined the experiences of learner drivers in Queensland and New South Wales in order to develop an understanding of the factors that influenced them while learning to drive. This will enable the development of more effective licensing systems. The research was informed by a number of heoretical perspectives, particularly social learning theory. Participants were recruited from driver licensing centres as soon as they passed their practical driving test to attain a provisional licence. Of those approached, 392 new drivers from capital cities and regional locations in Queensland and New South Wales completed a 35 minute telephone interview that collected information on a range of personal, social, environmental and socio-demographic factors. Participants were obtaining their licence before several changes to the licensing systems in both Queensland and New South Wales were made in 2007. Several implications for countermeasure development resulted from this research. These included ensuring licensing authorities carefully consider mandating a minimum number of hour of practice as it may inadvertently suppress the amount of practice that some learners obtain. Licensing authorities should consider the use of logbooks for learner drivers, even if there is no minimum amount of supervised practice required as it may assist learners and their supervisors structure their practice more effectively. This research also found that the confidence of learner drivers increases between when they first obtain their learner licence and when they obtain their provisional licence. This is an important issue requiring further attention by licensing authorities

Studying the effects of in-vehicle information systems on driver visual behaviour – implications for design

In-vehicle information systems (IVIS) are a common feature in modern vehicles. The interaction of drivers with IVIS when driving must be considered to minimise distraction whilst maintaining the benefits provided. This research investigates the glance behaviours of drivers, assessed from video data, when using two functions – a personal navigation device (study 1) and a green driving advisory device (study 2). The main focus was to establish the number of glances of 2 seconds or more to the IVIS and relate this to driver safety (as stipulated in new guidelines for use of IVIS proposed by NHTSA). In study 1, the percentage of eyes- off-road time for drivers was much greater in the experimental (with device) condition compared to the baseline condition (14.3% compared to 6.7%) but, whilst glances to the personal navigation device accounted for the majority of the increase, there were very few which exceeded 2 seconds. Drivers in study 2 spent on average 4.3% of their time looking at the system, at an average of 0.43 seconds per glance; no glances exceeded 2 seconds. The research showed that ordinary use of IVIS (excluding manual interaction) does not lead to driver visual distraction and therefore the impact on safety is minimal. The results of the study have important design implications for future in-vehicle information systems

Glance behaviours when using an in-vehicle smart driving aid : a real-world, on-road driving study

In-vehicle information systems (IVIS) are commonplace in modern vehicles, from the initial satellite navigation and in-car infotainment systems, to the more recent driving related Smartphone applications. Investigating how drivers interact with such systems when driving is key to understanding what factors need to be considered in order to minimise distraction and workload issues while maintaining the benefits they provide. This study investigates the glance behaviours of drivers, assessed from video data, when using a smart driving Smartphone application (providing both eco-driving and safety feedback in real-time) in an on-road study over an extended period of time. Findings presented in this paper show that using the in-vehicle smart driving aid during real-world driving resulted in the drivers spending an average of 4.3% of their time looking at the system, at an average of 0.43 s per glance, with no glances of greater than 2 s, and accounting for 11.3% of the total glances made. This allocation of visual resource could be considered to be taken from ‘spare’ glances, defined by this study as to the road, but off-centre. Importantly glances to the mirrors, driving equipment and to the centre of the road did not reduce with the introduction of the IVIS in comparison to a control condition. In conclusion an ergonomically designed in-vehicle smart driving system providing feedback to the driver via an integrated and adaptive interface does not lead to visual distraction, with the task being integrated into normal driving

Sustainability, transport and design: reviewing the prospects for safely encouraging eco-driving

Private vehicle use contributes a disproportionately large amount to the degradation of the environment we inhabit. Technological advancement is of course critical to the mitigation of climate change, however alone it will not suffice; we must also see behavioural change. This paper will argue for the application of Ergonomics to the design of private vehicles, particularly low-carbon vehicles (e.g. hybrid and electric), to encourage this behavioural change. A brief review of literature is offered concerning the effect of the design of a technological object on behaviour, the inter-related nature of goals and feedback in guiding performance, the effect on fuel economy of different driving styles, and the various challenges brought by hybrid and electric vehicles, including range anxiety, workload and distraction, complexity, and novelty. This is followed by a discussion on the potential applicability of a particular design framework, namely Ecological Interface Design, to the design of in-vehicle interfaces that encourage energy-conserving driving behaviours whilst minimising distraction and workload, thus ensuring safety

Motorcycle safety research project: Interim summary report 3: training and licensing interventions for risk taking and hazard perception for motorcyclists

Motorcycle trauma is a serious road safety issue in Queensland and throughout Australia. In 2009, Queensland Transport (later Transport and Main Roads or TMR) appointed CARRS-Q to provide a three-year program of Road Safety Research Services for Motorcycle Rider Safety. Funding for this research originated from the Motor Accident Insurance Commission. This program of research was undertaken to produce knowledge to assist TMR to improve motorcycle safety by further strengthening the licensing and training system to make learner riders safer by developing a pre-learner package (Deliverable 1), and by evaluating the QRide CAP program to ensure that it is maximally effective and contributes to the best possible training for new riders (Deliverable 2). The focus of this report is Deliverable 3 of the overall program of research. It identifies potential new licensing components that will reduce the incidence of risky riding and improve higher-order cognitive skills in new riders