Driver Training Using an Advanced Driver-Assistance System (ADAS)

A driver-training assistant that accesses features of an Advanced Driver-Assistance System (ADAS) to train drivers is described. The driver-training assistant uses detection capabilities of the ADAS to determine a performance of the driver and indicate a correction to the driver. Such an indication may be provided to the driver through a visual, audible, or haptic aide

Conceptual Model for an Intelligent Persuasive Driver Assistant

Traffic congestion is a serious issue for large cities.  This is especially critical for cities that has insufficient mass transit system like Bangkok.  Although transportation infrastructure projects and rail mass transit lines are being implemented, these efforts require major financial investment and take a long time to complete.  This work proposes to help reduce traffic problems through influencing a change in driver behavior.  In this initial stage, a model for an intelligent persuasive driver assistant is conceptualized as a voice-interactive smart assistant on a smartphone.  The system uses information about the driver, his physical state, vehicle performance information, and geolocation information to form persuasive strategies to influence driver behavior and to adapt user interfaces and interactions to reduce driver distraction.  Integrating these components together is expected to provide improved assistance in driving tasks and affect driving behavior changes. Keywords: intelligent driver assistant, navigation, smart assistant, persuasive technolog

Providing over-the-horizon awareness to driver support systems

Vehicle-to-vehicle communications is a promising technique for driver support systems to increase traffic safety and efficiency. A proposed system is the Congestion Assistant [1], which aims at supporting drivers when approaching and driving in a traffic jam. Studies have shown great potential for the Congestion Assistant to reduce the impact of congestion, even at low penetration. However, these studies assumed complete and instantaneous availability of information regarding position and velocity of vehicles ahead. In this paper, we introduce a system where vehicles collaboratively build a so-called TrafficMap, providing over-the-horizon awareness. The idea is that this TrafficMap provides highly compressed information that is both essential and sufficient for the Congestion Assistant to operate. Moreover, this TrafficMap can be built in a distributed way, where only a limited subset of the vehicles have to alter it and/or forward it in the upstream direction. Initial simulation experiments show that our proposed system provides vehicles with a highly compressed view of the traffic ahead with only limited communication

Prototype of a Child Safety Driver Assistant System

Farming machinery accidents frequently cause the injury and death of children on farms. These accidents are caused by vehicle blind spots, attached machinery, inadequate security measures, carelessness, and insufficient childcare availability. It is often difficult to separate working and living areas on family farms, making additional security and preventative measures necessary. Farmers are interested in using devices that increase the safety of children in the mechanized working environment. The system developed to tackle this problem combines two technologies, a wireless radio network sensor and an electrical near field sensor. Detection occurs indirectly, meaning that each child wears a slumbering transponder. Upon entering a risk zone, the transponder begins to communicate with a stationary sensor and alarm unit device mounted on the vehicle. Initial tests have verified the suitability of these technologies for this universal problem. To improve usability, it is necessary to miniaturize the transponder, identify detection gaps, and synchronize parallel vehicle use. Danger zones must also be defined in order to create a phased warning system to avoid false alarms, reduce alarm desensitization, and moderate stress for the vehicle operator. A user-friendly design and high service quality would increase the motivation and acceptance of wearing a transponder

Automatically Detecting and Assisting a Drowsy Driver

This disclosure describes a virtual assistant that provides suitable interventions and/or suggestions to drivers to mitigate risks from drowsy driving. With user permission and express consent, the virtual assistant receives inputs from multiple sensors, devices, and systems that provide driving context information. For example, the virtual assistant can be provided via a wearable device, a mobile device, vehicle infotainment system etc. Inputs are received from various user-permitted sensors on one or more of these devices and are utilized to calculate a drowsiness score for the driver. Based on the drowsiness score, suitable interventions and suggestions are provided via audio, visual, or another interface. With user permission, tools to enhance driver alertness such as live conversation, jokes, games, etc. are provided

Over-the-Horizon Awareness for Advanced Driver Assistance Systems: the TrafficFilter and microSlotted 1-Persistence Flooding

Vehicle-to-vehicle communications (V2V) is a promising technique for Advanced Driver Assistance Systems to increase traffic safety and efficiency. A proposed system is the Congestion Assistant, which supports drivers when approaching and driving in traffic congestion. Studies have shown great potential for such systems to reduce the impact of congestion, even at low penetration. However, these studies assumed complete and instantaneous knowledge regarding position and velocity of vehicles ahead. This paper refines and analyses the TrafficFilter, designed to supply the required information to the Congestion Assistant. Vehicles collaboratively build a so-called TrafficMap, providing over-the-horizon awareness. To this end, an improvement to the Slotted 1-Persistence Flooding called microSlotted 1-Persistence Flooding is proposed and evaluated. In a simulation study the TrafficFilter is found to be a viable system to build over-the-horizon awareness for future Advanced Driver Assistance Systems like the Congestion Assistant, without triggering the phenomenon known as Broadcast Storm

Destination Prediction with Decision Tree An Intelligent Driver Assistant for Volvo Cars: Destination Prediction, Traffic Notifying and Route Advising

In this thesis, a destination prediction method based on decision tree model will be presented. The method will be used to support the Volvo Car Intelligent Driver Assistant System. Accurate destination prediction method is useful in many cases, for instances, it helps to free driver's hand of manually inputting destination address, provide traffic jam report before running into traffic jam and recommend the optimal route with the supporting of third parties' services. The mean accuracy of the destination prediction introduced in this thesis can achieve about 75%. By collaborating with the INRIX Traffic API, WirelessCar API and Volvo On Call app, the Intelligent Driver Assistant System achieves the goal to notifying Volvo Car drivers with traffic information and providing possible routes to the predicted destination

SHPbench – a smart hybrid prototyping based environment for early testing, verification and (user based) validation of advanced driver assistant systems of cars

Statistical analysis show that more than 90 percent of all car accidents result from human mistakes. Advanced Driver Assistant Systems (ADAS) are intended to support and assist the car driver, and therefore contribute significantly to the reduction of accidents. ADAS become more and more complex and demanding regarding hard- and software fulfilling the requirements applied onto assistant systems nowadays and in the future. They have to be considered as multi-functional multi-domain mechatronic systems. Smart Hybrid Prototyping (SHP) is a by now proven approach for handling ADAS’ demands during and to the development process, specifically for early integrated component and system testing, its verification and validation with the focus on the interaction with the driver can only be reasonably and economically met by utilizing the SHP technology. For those mentioned purposes the SHPbench, an integrated development and validation environment, has been recently developed. The SHPbench's architecture and specification is presented and evaluated by applying a representative use case of an ADAS development process. This paper documents the use case setup, process steps and test results