Erik M Steinmetz

Processing of Eye/Head-Tracking Data in Large-Scale Naturalistic Driving Data Sets

Driver distraction and driver inattention are frequently recognized as leading causes of crashes and incidents. Despite this fact, there are few methods available for the automatic detection of driver distraction. Eye tracking has come forward as the most promising detection technology, but the technique suffers from quality issues when used in the field over an extended period of time. Eye-tracking data acquired in the field clearly differs from what is acquired in a laboratory setting or a driving simulator, and algorithms that have been developed in these settings are often unable to operate on noisy field data. The aim of this paper is to develop algorithms for quality handling and signal enhancement of naturalistic eye- and head-tracking data within the setting of visual driver distraction. In particular, practical issues are highlighted. Developed algorithms are evaluated on large-scale field operational test data acquired in the Sweden-Michigan Field Operational Test (SeMiFOT) project, including data from 44 unique drivers and more than 10 000 trips from 13 eye-tracker-equipped vehicles. Results indicate that, by applying advanced data-processing methods, sensitivity and specificity of eyes-off-road glance detection can be increased by about 10%. In conclusion, postenhancement and quality handling is critical when analyzing large databases with naturalistic eye-tracking data. The presented algorithms provide the first holistic approach to accomplish this task.

A Stochastic Geometry Model for Vehicular Communication near Intersections

Many traffic-related applications require the nodes in a vehicular ad-hoc network (VANET) to periodically broadcast their state information. As measurements campaigns or simulations to evaluate the reliability of packet transmission are slow and scenario-specific, we present an analytic performance assessment tool that accounts for the spatial statistics of the nodes on a road, in a scenario of crossing roads and fast fading. Based on stochastic geometry, our tool is able to capture a static two-dimensional road geometry and the effect of interference due to node clustering in the vicinity of an intersection. Numerical results reveal how packet transmission is affected as the receiver gets closer to the intersection.

WiP Abstract: Reception Probability Model for Vehicular Ad-Hoc Networks in the Vicinity of Intersections

In order to guide and validate the communication system design for vehicular ad-hoc networks (VANETs), and to obtain important insight about scalability and performance in these networks, analytical expressions of key performance metrics are necessary. In this study, we present an analytical model based on stochastic geometry to evaluate the reliability of packet transmission in VANETs in the vicinity of intersections.

Communication analysis for centralized intersection crossing coordination

Coordination of autonomous cooperative vehicles is an important challenge for future intelligent transportation systems. In particular, coordination to cross intersections captures the inherent and connected challenges among control and communication. While intersection coordination and vehicular wireless communication have both received extensive treatment in their respective communities, few works consider their interaction. We provide a communication system analysis for the specific problem of centralized intersection crossing coordination, leading to design guidelines for both uplink (whereby vehicles send intentions to the central controller) and downlink (where the controller prescribes vehicles of safe control actions).

Vehicle-to-Vehicle Communications with Urban Intersection Path Loss Models

Vehicle-to-vehicle (V2V) communication can improve road safety and traffic efficiency, particularly around critical areas such as intersections. We analytically derive V2V success probability near an urban intersection, based on empirically supported line-of-sight (LOS), weak-line-of-sight (WLOS), and non-line-of-sight (NLOS) channel models. The analysis can serve as a preliminary design tool for performance assessment over different system parameters and target performance requirements.

Assessment of GPS derived speed for verification of speed measuring devices

Speed information from GPS is increasingly used and provides an alternative to conventional methods such as wheel speed sensors. We investigate the possibility to use GPS derived speed as a reference when verifying laser and radar-based speed measuring devices used in traffic enforcement. We have set up a realistic test scenario where a GPS equipped vehicle was driven at three different speeds (40, 90 and 130 km/h) through a pre-defined measurement zone. An independent and traceable reference speed was calculated by accurately measuring the length of the measurement zone (approximately 15 metres), and the time it took to pass through it. The reference speed was compared to the average GPS speed for each passage. This comparisons show that the standard uncertainty of such GPS speed measurements is less than 0.05 km/h. Hence, GPS derived speed meets the accuracy requirements for verification of laser and radar based speed measuring devices.