As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Cycling, as one of the oldest forms of mobility, is currently experiencing a renaissance. It supports active mobility and can have a positive influence on public health, the environment, climate and the traffic situation. Pedelecs (bicycles with an electric motor supporting the user up to a speed of 25 kmph) represent a new form of active mobility and are currently enjoying great popularity as they have the same benefits compared to conventional bicycles and, in addition, make cycling accessible to new user groups. With the growing number of pedelecs, however, potential for conflict also increases. Unfortunately, the majority of accidents cannot yet be analysed accordingly, as pedelec-specifiic characteristics are missing from the accident data. This fact in itself has already been proven as a barrier. Most accident studies focusing on pedelecs are based on police data from standardised accident forms [e.g. 1, 2, 3, 4]. Their findings can be summarised in the following key statements: Accidents with pedelecs are less frequent but more severe than those with conventional bicycles. For both, accidents on urban roads dominate, but pedelec accidents occur significantly more often on rural roads than conventional bicycle accidents. And: injured pedelec users, especially those fatally injured, are on average significantly older than injured users of conventional bicycles. But, standardised accident forms were initially designed for accidents with double-track motor vehicles, in particular passenger cars. Accidents with bicycles (especially pedelecs), are difficult to categorise with this systematic as important information is missing. For example, 'falling on ground' is not an accident category as cars normally won't do so, but for pedelec accidents, this information is fundamental. This acts as a barrier as bicycle-specific causes of accidents cannot be analysed. However, accident statistics are the most important basis for evidence-based measures in road safety work. The aim of this paper is therefore to identify and categorise pedelec-specific accident characteristics and to evaluate pedelec accidents on the basis of these characteristics to identify frequent and severe accident constellations. [From: Introduction]

Šiame magistro darbe išanalizuota Lietuvos eismo įvykių apskaitos sistema, sudaryta iš duomenų rinkimo, įvedimo ir teikimo proceso, kurį atlieka policijos įstaigų darbuotojai. Darbe išsamiai išnagrinėti Lietuvos norminiai dokumentai, reglamentuojantys eismo įvykių apskaitos procesą. Analizės rezultatams apibendrinti yra skurti pirminių veiksmų, duomenų pasiskirstymo ir teikimo bei ikiteisminio tyrimo medžiagos panaudojimo grafiniai modeliai. Taip pat išsamiai išnagrinėtas Europos Sąjungoje atliekamas eismo įvykių apskaitos procesas. Darbe pateiktas eismo įvykių duomenų apskaitos programinės sistemos detalus vertinimas su rekomendacijomis, kaip patobulinti sistemą siekiant užtikrinti išsamesnius, tikslesnius oficialios statistikos eismo įvykių duomenis. Baigiamojo darbo apimtis – 81 psl. teksto be priedų, 19 lentelių ir 13 paveikslų. / In this Master Thesis analysis of Lithuanian road accident management system, which consists data collecting, adding and provision process have been done. Lithuanian normative documents which governs road accident management process are purely explored in this Master Thesis. To generalize analysis results have been created primary respond, data distribution and provision, data usage of pre-trial process graphical models. Also a part of the work reveals detailed analysis of accident data management of European Union countries. In this paper is provided detailed evaluation of road accident data management software system and recommendations to ensure more detailed road accidents data of official statistics by improving system. Master Thesis consists of 81 pages pure text without appendixes, 19 tables and 13 pictures.

In Europe, the deployment characteristics of frontal crash restraints are generally optimised to best protect an average young male, since a 50th percentile male dummy is used in a stylised frontal impact scenario. These single point restraint systems may not provide similar levels of effectiveness when the crash scenarios vary with respect to the regulatory and consumer crash test procedures. Previous research has demonstrated that varying restraint deployment characteristics according to occupant and crash variation can provide further injury reduction in frontal impacts. This thesis reports the investigation conducted to assess the potential real world injury reduction benefit of smart restraint systems in frontal impacts. The intelligent capability of the restraint was achieved by varying the seat belt load limiter (SBL) threshold, according to the frontal crash scenario. Real world accident data (CCIS) were analysed to identify the target population of vehicle occupants and frontal impact scenarios where employing smart load limiters could be most beneficial, particularly in reducing chest injury risk. From the accident sample, the chest was the most frequently injured body region at an AIS 2+ level in frontal impacts (7% of front seat occupants). The proportion of older vehicle front seat occupants (>64 years old) with AIS 2+ injury was also greater than the proportion of younger occupants. Additionally, older occupants were more likely to sustain seat belt induced serious chest injury in low and moderate speed frontal crashes. Numerical simulations using MADYMO software were conducted to examine the effect of varying the load limiter thresholds on occupant kinematics and injury outcome in frontal impacts. Generic baseline driver and front passenger numerical models were developed using a 50th percentile dummy and were adapted to accommodate a 5th and 95th percentile dummy. Simulations were performed where the load limiter threshold was varied in five frontal impact scenarios which were selected to cover as wide a range of real frontal crash conditions as possible. From the simulation results, it was found that for both the 50th and 95th percentile dummy in front seating positions (driver and passenger), the low SBL provided the best chest injury protection, without increasing the risk to other body regions. In severe impacts, the low SBL allowed the dummy to move further towards the front facia, thus increasing the chance of occupant hard contact with the vehicle interiors. The Smart load limiters predicted no injury risk reduction for the 5th percentile drivers, who are shorter and tend to sit closer to the steering wheel. The potential injury reduction of the smart load limiters was quantified by applying the estimated injury risk reduction from the simulation to the real world accident data sample. Thoracic injury predictions from the simulations were converted into injury probability values using AIS 2+ age dependent thoracic risk curves which were developed and validated based on a methodology proposed by Laituri et al. (2005). Real world benefit was quantified using the predicted relative AIS 2+ risk reduction and assuming an appropriate adaptive system was fitted to all the cars in the real world sample. When applying the AIS 2+ risk reduction findings to the weighted accident data sample, the risk of sustaining an AIS 2+ seat belt injury reduced from 1.3% to 0.9% for younger front seat occupants, 7.6% to 5.0% for middle aged front seat occupants and 13.1% to 8.6% for the older front seat occupants. The research findings clearly demonstrate a chest injury reduction benefit across all age groups when the load limiter characteristics are varied. It suggests that employing a smart load limiter in a vehicle would not only benefit older occupants but also middle aged and young occupants. The benefit does appear to be most pronounced for older occupants, since the older population is more vulnerable to chest injury. As the older population of car users is rapidly rising, the benefits of smarter systems can only increase in the future.