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To improve road safety the public sector is actively supporting this effort with investment in required infrastructure, enforcement in the road safety rules, and improved deployment of Intelligent Transportation Systems (ITS). With the development of more powerful processors, communication and sensor technologies, tools are now available to enable the industry players to meet the aforementioned challenges. The paper will describe work undertaken within the European MEDEA+ framework in the project SAPECS (Secured Architecture & Protocols for Enhanced Car Safety). The consortium of companies that worked within SAPECS broke down the requirements emerging from these complex automotive architectures into component specifications, and partitioning of software/hardware to optimise costs.

The Controller Area Network (CAN) has seen enormous success in automotive body and powertrain control systems, and in industrial automation systems using higher layer protocols such as DeviceNet and CANopen. Now, the CAN standard ISO11898 are being extended to Time Triggered CAN (TTCAN) to address the safety critical needs of first generation drive-by-wire systems. However, their successful development depends upon the availability of silicon and software support, and appropriate development & analysis tools. This paper outlines the current status of TTCAN technology and describes the implementation of Level 1 TTCAN on the Atmel 89c51cc01/cc02/cc03/cc04 microcontrollers. The descriptions contained show how to implement for different bus speeds, along with suggestion for a user to tailor the drivers for their own application. Level 2 TTCAN is also described for comparison purposes.

The Controller Area Network (CAN) has seen enormous success in automotive body and powertrain control systems, as well as industrial automation systems using higher layer protocols such as CANopen and DeviceNet. Now, the CAN standard ISO11898 is being extended to Time Triggered CAN (TTCAN) to address the safety critical needs of first generation drive-by-wire systems. However, their successful development depends upon the availability of silicon and software support, and appropriate development & analysis tools. Warwick Control Technologies and the University of Warwick are tasked with prototyping a TTCAN analyser within the European Union Media+ project Silicon Systems for Automotive Electronics (SSAE) consortium, and with funding from the British Department of Trade and Industry (DTI). This paper briefly outlines the current status of both CAN & TTCAN technology and describes the requirements of a TTCAN analyser over that of a traditional CAN analyser.

An on line method for verification of chassis dynamometer operation uses a neural network. During the testing of a vehicle, it is assumed that after a warm up period the parasitic losses remain stable. There is normally no provision for verification of correct dynamometer operation while the test is running. This technique will detect if a component wears or fails during the testing of a vehicle and thus avoid testing under erroneous conditions. A Learning Vector Quantization (LVQ) neural network is trained to recognise poor dynamometer operation in order to signal a fault condition to the operator.