In order to improve the protection of children transported in cars, within the CHILD programme (GR3D-CT2002-00791) real world road accidents are thoroughly analysed and then reconstructed in laboratory. Prior to comparing injury severities of real victims to physical parameter values measured on the dummies, the quality of the reconstructions is evaluated by experts who use their experience based on the investigation of numerous and various accidents. This paper presents a new tool aiming at better evaluating and validating accident reconstructions. It is based on statistical evaluation of vehicle deformations which gives weighing factors for every part of the car body structure finally leading to a specific Reconstruction Quality Score (RQS indicator). Furthermore, the reliability of this score, depending on the number of measured points, can be established. This tool includes a function aiming at adjusting the speed for a further reconstruction and at defining the launching speed and the pulse shape for complementary sled tests. Finally, the functions of the RQS software and database are presented.
Intelligent transportation systems have a high potential to optimise traffic flow, to increase road traffic safety and to reduce environmental pollution. Real Time Traffic Information (RTTI) systems help to achieve these targets. Beside verbal radio announcements the most used RTTI service is the Traffic Message Channel (TMC) as a part of the Radio Data System (RDS). TMC messages support drivers in their choice of efficient routes or prepare them to cope with situations on the route ahead. The main focus of the paper is on the quality of TMC messages in Germany. After a brief overview of RTTI stakeholders in Germany and their role in the German public traffic information chain the following literature analysis summarizes the state-of-the-art on traffic information quality. Then the paper gives an overview about methodology and first results of an ongoing project on traffic information quality that has been initiated by the Bundesanstalt für Straßenwesen (BASt, German Federal Highway Research Institute) in 2008. The paper describes a concept how to check all processing iterations of the traffic information chain and occurring failures. A cause-effect-analysis forms the basis of this concept to get an idea which reasons (= process) lead to which measurable effect (= quality indicator). The paper demonstrates the principle with the pre-process of the Location Code List (LCL), which is the major basis for message coding since the LCL describes all locations that can be named in a TMC message.
Causation patterns and data collection blind spots for fatal intersection accidents in Norway
(2010)
Norwegian fatal intersection accidents from the years 2005-2007 were analysed to identify any causation patterns among their underlying contributing factors, and also to evaluate whether the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to perform causation pattern analysis. A total of 28 fatal accidents were analysed. Details on crash contributing factors for each driver in each crash were first coded using the Driving Reliability and Error Analysis Method (DREAM), and then aggregated based on whether the driver was going straight or turning. Analysis results indicate that turning drivers to a large extent are faced with perception difficulties and unexpected behaviour from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers going straight on the other hand have less perception difficulties. Instead, their main problem is that they largely expect turning drivers to yield. When this assumption is violated, they are either slow to react or do not react at all. Contributing factors often pointed to in literature, e.g. high speed, drugs and/or alcohol and inadequate driver training, played a role in 12 of 28 accidents. While this confirms their prevalence, it also indicates that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, information on blunt end factors (those more distant in time/space, yet important for the development of events) was more limited than information on sharp end factors (those close in time/space to the crash). A possible explanation is that analysts may view some blunt end factors as event circumstances rather than contributing factors in themselves, and therefore do not report them. There was also an asymmetry in terms of reported obstructions to view due to signposts and vegetation. While frequently reported as contributing for turning drivers, they were rarely reported as contributing for their counterparts in the same accidents. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver legally held liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator mindset needs addressing to avoid future bias in crash investigation reports.
As the data for road weather stations is used for online traffic control within section control systems, it is very important for the efficiency of the traffic control systems to be based on reliable data of a high quality. Therefore, a Test Site for checking the quality of road weather stations was established near Munich in Germany in 2003 and has been operational since then. In close co-operation with all participants (sensor manufacturers, road authorities, German Federal Research Institute, research and consultancy bodies), the overall goal was to improve the sensors" quality as well as to establish methods to detect failures in measurements. Furthermore, several improvements were carried out within the scope of the Test Site using the expertise of all participants and the infrastructure of the Test Site. The developments, reports and results obtained are both significant and helpful for manufacturers, road authorities, practitioners, research and consultancy.