China's ongoing transition to a modern urban-centered economy is accompanied by ambitions of sustained economic growth as well as promises of environmentally sustainable futures for its cities. In this paper we critically assess how these two ideas are combined and translated into realities on the ground by examining three low-carbon development projects in Shanghai: Anting New Town, Dongtan Eco-City, and Hongqiao CBD's low-carbon transportation hub. By mobilizing insights from the academic field of Sustainability Transitions – specifically on expectations, experimentation and innovation journeys – we show how the original plans derailed and why until now there has been limited success in living up to the promises of sustainability. To realize the promises more fully in future projects we identify three broad lessons for the actors involved: they should nurture a set of parallel pathways, foster a more experimentalist mindset, and learn to embrace uncertainty.

In this paper, we consider active trailer steering control as a means to improve the maneuverability of (long) truck-trailer combinations during cornering. Hereto, we formulate the problem of reducing the so-called swept path width during cornering and that of eliminating unsafe tail swing of the trailer as a tracking control problem. We present a kinematic tractor-trailer model including off-axle hitching, on the basis of which we design nonlinear control strategies solving this tracking problem. The effectiveness of the proposed approach is evidenced experimentally on a robotic tractor-trailer platform.

Active trailer steering control can improve the manoeuvrability of (long) truck-trailer combinations during cornering. To assess the effectiveness of trailer steering control, we formulate the problem of reducing the so-called swept-path width during cornering, and that of eliminating unsafe tail swing of the trailer, as a tracking control problem. We present a kinematic tractor-trailer model including off-axle hitching, on the basis of which nonlinear control strategies solving this tracking problem are developed. The effectiveness of the proposed approach is evidenced by means of a benchmark simulation study.