Road Traffic Regulations (Straßenverkehrsordnung; StVO) define legal road use on public streets. In particular, they describe the meaning and appropriation of traffic signs by means of which road use restrictions can be adopted. Traffic regulation orders become legally binding when they are announced by according traffic signs. This may lead to inconsistencies with existing regulations. In order to invalidate outdated, contradictory regulations, respective traffic signs need to be removed. Currently, road and traffic management officials in Vienna and Lower Austria are supported by a web application that allows editing and visualizing traffic regulations on a digital street map. However, tools are lacking that help to ensure the compliance of such restrictions with the Road traffic Regulations and with supplementary criteria. The goal of this thesis is to develop such tools based on intuitively readable, flexibly extendable formal specifications. To this end, we first analyze the kind of information, which is expressed by traffic signs and traffic measures in a domain analysis. We develop a formal model which allows an examination of high-level relations between measures and signs and their compliance with a formal specification, without neither being bound to specific street maps, traffic signs, regulations, nor to data models of existing implementations. We identify practically relevant tasks related to the correctness of traffic regulations and develop methods to solve them. First, we show how to evaluate a given scenario based on rules that declare the meaning of traffic signs and traffic measures. In case of an error, we can recognize which conflicts exist and where they occur. We provide diagnoses which determine the causes of conflicts. Furthermore, we show how corrections for inconsistent scenarios can be obtained by the specification itself. In addition to ensuring the correctness of measures and signs with respect to the rules, these repairs guarantee that the restrictions as announced by traffic signs correspond with the intended restrictions as expressed by traffic measures. We define these use cases in form of reasoning tasks and analyze the computational complexity of associated decision problems. Finally, we present in detail a prototypical solution of the defined problems with Answer Set Programming (ASP), which is a rule- based programming paradigm. By exploiting the purely declarative semantics of ASP, we obtain a modular, highly flexible and maintainable implementation, which is crucial to this intrinsically complex domain.