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Robust road-boundary extraction/tracking is one of the main problems in autonomous roadway navigation. Although the road boundary can be defined by various means including lane markings, curbs, and borders of vegetation, this paper focuses on road-boundary tracking using curbs. A vehicle-mounted (downward tilted) 2-D laser-measurement system is utilized to detect the curbs. The tracking problem is difficult because both the vehicle is moving and the target is disappearing, reappearing, and maneuvering in clutter. The interacting-multiple-model probabilistic-data-association filter (IMMPDAF) is proposed to solve the problems after detailed analysis. Track initiation, confirmation, and deletion are performed using the sequential-probability-ratio test. Extensive simulations followed by experiments in a campus environment show that the road-boundary tracking utilizing curbs is possible and robust through IMMPDAF. [ABSTRACT FROM AUTHOR]

Although widely accepted, traffic controls are an unnecessary evil, imposed on a road network by governments with no commercial incentive to ensure the free flow of traffic. Far from making our roads safer and less congested, traffic lights make matters worse. They take our eyes off the road, obstruct our progress and cause needless delay. In the process they damage our health, the economy and the environment. There is another way: remove controls and restore the common law principle of first-come, first-served – or ‘filter-in-turn’, as it's known in the Channel Islands. The optimum form of traffic control is self-control. The onus should be on government to prove otherwise. [ABSTRACT FROM AUTHOR]