Jonas Jansson

Brief paper: A framework and automotive application of collision avoidance decision making

Collision avoidance (CA) systems are applicable for most transportation systems ranging from autonomous robots and vehicles to aircraft, cars and ships. A probabilistic framework is presented for designing and analyzing existing CA algorithms proposed in literature, enabling on-line computation of the risk for faulty intervention and consequence of different actions. The approach is based on Monte Carlo techniques, where sampling-resampling methods are used to convert sensor readings with stochastic errors to a Bayesian risk. The concepts are evaluated using a real-time implementation of an automotive collision mitigation system, and results from one demonstrator vehicle are presented.

Dimensions of cooperative driving, its and automation

Wireless technology supporting vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communication, allow vehicles and infrastructures to exchange information, and cooperate. Cooperation among the actors in an intelligent transport system (ITS) can introduce several benefits, for instance, increase safety, comfort, efficiency. Automation has also evolved in vehicle control and active safety functions. Combining cooperation and automation would enable more advanced functions such as automated highway merge and negotiating right-of-way in a cooperative intersection. However, the combination have influences on the structure of the overall transport systems as well as on its behaviour. In order to provide a common understanding of such systems, this paper presents an analysis of cooperative ITS (C-ITS) with regard to dimensions of cooperation. It also presents possible influence on driving behaviour and challenges in deployment and automation of C-ITS.

Handling of buses on slippery roads during the influence of side wind—a study of the effects of different tyres

Accident statistics assembled by the Swedish National Road and Transport Research Institute (VTI) have shown that buses are overrepresented when it comes to accidents on icy and snowy roads. For a better understanding of the problem, the performance of modern summer and winter tyres on winter road conditions had to be assessed. The objective of this work has been to go beyond standard road grip studies, and instead investigate how the drivers possibility to deal with one challenging situation depends on the tyres and tyre configuration. This paper describes a novel methodology where measurements with different tyres on ice in VTIs tyre test facility, enabled a simulator study for evaluating the impact of different tyre characteristics when driving in conditions with strong side wind on a slippery road. The main results of the study are: to deal with strong side wind, good front wheel grip is most important, and while non-studded winter tyres provided little or no improvement over summer tyres, studded winter tyres significantly reduced the risk to run off the road. Furthermore, it is very difficult for the drivers to judge, beforehand, whether a vehicle with a particular tyre configuration will perform good or bad.

Extended Driving Simulator for Evaluation of Cooperative Intelligent Transport Systems

Vehicles in cooperative intelligent transport systems (C-ITS) often need to interact with each other in order to achieve their goals, safe and efficient transport services. Since human drivers are still expected to be involved in C-ITS, driving simulators are appropriate tools for evaluation of the C-ITS functions. However, driving simulators often simplify the interactions or influences from the ego vehicle on the traffic. Moreover, they normally do not support vehicle-to-vehicle and vehicle-to-infrastructure (V2X) communication, which is the main enabler for C-ITS. Therefore, to increase the C-ITS evaluation capability, a solution on how to extend a driving simulator with traffic and network simulators to handle cooperative systems is presented as a result of this paper. Evaluation of the result using two use cases is presented. And, the observed limitations and challenges of the solution are reported and discussed.