Autonomous intersection management has the potential to reduce road traffic congestion and energy consumption. To realize this potential, efficient algorithms are needed. However, most existing studies locally optimize one intersection at a time, and this can cause negative externalities on the traffic network as a whole. Here, we focus on coordinating multiple intersections, and formulate the problem as a distributed constraint optimisation problem (DCOP). We consider three utility design approaches that trade off efficiency and fairness. Our polynomial-time algorithm for coordinating multiple intersections reduces the traffic delay by about 41 percentage points compared to independent single intersection management approaches.

Ridesharing has great potential to improve transportation efficiency while reducing congestion and pollution. To realize this potential, mechanisms are needed that allocate vehicles optimally and provide the right incentives to riders. However, many existing approaches consider restricted settings (e.g., only one rider per vehicle or a common origin for all riders). Moreover, naive applications of standard approaches, such as the Vickrey-Clarke-Groves or greedy mechanisms, cannot achieve a polynomial-time, truthful, individually rational and budget balanced mechanism. To address this, we formulate a general ridesharing problem and apply mechanism design to develop a novel mechanism which satisfies all four properties and whose social cost is within 8.6% of the optimal on average.

Though a variety of indoor positioning systems have been proposed for a GPS-denied environment, most of them depend on dedicated devices which must be installed in a building. The preparation of this infrastructure usually entails considerable cost, which prevents the spread of indoor positioning technology. On the other hand, smartphones are already widespread and their low cost sensors are promising as rich data sources that can be used for indoor navigation. Several studies have demonstrated the possibility of smartphone-based infrastructure-free positioning. However, this navigation is not yet practical because of the accumulative error of inertial sensors and the communication range measurement error. We propose a solution to reduce the accumulative error of pedestrian dead reckoning carried out with only the low cost sensors and WiFi in smartphones by realizing cooperative positioning among multiple pedestrians. Our proposed method introduces linkage structures to simplify trajectories of pedestrians; these structures work as a constraint to reduce the number of variables to be estimated. Since this constraint makes positioning problems solvable with a small number of observations, our proposed method screened WiFi data by the signal strength and selected only strong signals for use in positioning. Our testing results showed that the positioning accuracy improved as the number of participants in the cooperative positioning operation increased. The positioning uncertainty was a few meters, comparable to GPS, when the density of participants is high enough.

On the basis of corpus analysis, we havemade directiongiving dialog system which adjust the pace of dialog without using speech recognition. And we evaluate the naturalness of the resulting conversations by experiments. Then the system showed good performance. And also the possibility of prosody to compensate for the weak points of speech recognition. 1