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Road traffic crashes (RTCs) are globally acknowledged as increasing threat to society, because they can affect many lives when they result in severe injury or fatality. In the State of Qatar RTCs are getting more awareness and attention, aiming to improve the traffic safety in the country. This study is an exploratory research providing different analyses of the crash data for seven consecutive years, ranging from 2010 to 2016, which is obtained from the Traffic Department in the Ministry of Interior for the State of Qatar. The objectives aim to evaluate the trend of RTC rate over time and create understanding of the influencing factors related to RTC frequency. Time series analyses show an increasing trend of RTCs leading to severe injury and a slight decreasing trend for fatal RTCs. Secondly, different RTC severity levels are related to diverse RTC causes. Furthermore, the results revealed that crashes with severe injuries or fatality for drivers as well as pedestrians are found to be significantly affected by seasonal weather variations, with the highest vulnerability in winter and autumn season. This study therefore suggests the implementation of strategies to prioritize the traffic safety of road users during the crash-prone winter and autumn seasons. ARTICLE HISTORY

Innovations for today's vehicle functions are mainly driven by software. They realize comfort systems like automated parking but also safety systems where sensors are continuously monitoring the vehicle's surroundings to brake autonomously for avoiding collisions with cars, pedestrians, or bicyclists. In simulation environments, various traffic situations with alternative sensor setups are imitated before testing them on prototypical cars. In this paper, we are presenting an MDE approach for managing different sensor setups in a cyber-physical system development environment to leverage automated model verification, support system testing, and enable code generation. For example, the models are used as the single point of truth to configure and generate sensor setups for system validations in a 3D simulation environment. After their validation, a considered sensor configuration is transformed into a constraint-satisfaction model to be solved by the logical programming language Prolog. Based on this transformation, the conformance to the embedded system specification is formally verified and possible pin assignments, for how to connect the required sensors are calculated. The approach was validated during the development of a self-driving miniature vehicle using an STM32F4-based embedded system running the real-time operating system ChibiOS as the software/hardware interface to the sensors and actors.

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