Abstract

It is essential that China follows a low carbon pathway, in which technology plays a key role in the future economy and social development. Based on the Integrated Policy Assessment Model for China, this paper analyzes a technology development roadmap for China to achieve a low carbon scenario. The results show that there are plenty of potential and opportunities for China to move towards a low carbon society when given enhanced and accelerated applications and expansions of key low carbon technologies. Strong policy and measure supports from all sectors in China are needed to achieve this goal. Liu, Q., K. Jiang, and X. Hu, 2011: Low carbon technology development roadmap for China. Adv. Clim. Change Res., 2 (2), doi: 10.3724/SP.J.1248.2011.00067.

Abstract

Nowadays, driver assistance systems involve an ever increasing degree of automatization. Costly effort is put into testing the individual components to ensure proper functioning by the vehicle manufacturers. However, problems can also arise on a macroscopic scale, as vehicles and infrastructure are recently equipped with short range radio communication (“Car2X”). These problems caused by interaction are of even greater concern than “normal” bugs, as the final product might already have been deployed when the issues first become apparent. Multi-Agent System (MAS) research refers to such issues as “emergent misbehavior”. The said field also brought up an approach to automatically discover the worst consequences of the malfunctions. Hence, a given system under test can already be revised during development, saving a tremendous amount of resources. The approach from MAS is adapted to the domain of testing driver assistance systems in traffic simulations. A green-light optimal-speed advisory (GLOSA) algorithm is used as an example in which conceptual problems are discovered by the testing system after simpler issues are eliminated.