This paper proposes a novel visualization approach, which can depict the variations between different human motion data. This is achieved by representing the time dimension of each animation sequence with a sequential curve in a locality-preserving reference 2D space, called the motion track representation. The principal advantage of this representation over standard representations of motion capture data -generally either a keyframed timeline or a 2D motion map in its entirety -is that it maps the motion differences along the time dimension into parallel perceptible spatial dimensions but at the same time captures the primary content of the source data. Latent semantic differences that are difficult to be visually distinguished can be clearly displayed, favoring effective summary, clustering, comparison and analysis of motion database.

Emergency evacuation is to transfer people from dangerous places to safe areas, so as to reduce or even avoid the potential harm to people. It is inherently a comprehensive system composed of evacuation managers, evacuees, road networks, shelters, etc. Security is one of the important indicators of such system. Moreover, in order to ensure the normal and efficient operation of evacuation system, each component should cooperate well with each other, thus making stability another important index of the evacuation system. In order to optimize evacuation safety, some residential areas may be arranged to stay much longer which is hard to be accepted, namely, the stability of evacuation system is low. In this paper, a system-based evacuation CSO model at residential level is proposed which compromises the security and stability of evacuation systems. The CSO model is a bi-level network optimization model, the upper level aims at minimizing the total risk of evacuation subject to the residential tolerance level and the lower level conveys a cell transmission-based dynamic traffic assignment problem. Using our model, we also study the impact of the number of shelters, the organizational form of road intersections, the uncertainty of evacuation demand and risk distribution on evacuation system. INDEX TERMS Evacuation management, system theory, constrained system optimal, dynamic traffic assignment, cell transmission model.

The existing variants of the rapidly exploring random tree (RRT) cannot be effectively applied in local path planning of the autonomous vehicle and solve the coherence problem of paths between the front and back frames. Thus, an improved heuristic Bi-RRT algorithm is proposed, which is suitable for obstacle avoidance of the vehicle in an unknown dynamic environment. The vehicle constraint considering the driver’s driving habit and the obstacle-free direct connection mode of two random trees are introduced. Multi-sampling biased towards the target state reduces invalid searches, and parent node selection with the comprehensive measurement index accelerates the algorithm’s execution while making the initial path gentle. The adaptive greedy step size, introducing the target direction, expands the node more effectively. Moreover, path reorganization minimizes redundant path points and makes the path’s curvature continuous, and path coherence makes paths between the frames connect smoothly. Simulation analysis clarifies the efficient performance of the proposed algorithm, which can generate the smoothest path within the shortest time compared with the other four algorithms. Furthermore, the experiments on dynamic environments further show that the proposed algorithm can generate a differentiable coherence path, ensuring the ride comfort and stability of the vehicle.

The objective of this study was to investigate how route familiarity affected drivers' eye movement features (fixation and saccade) and driving speed when driving in the entrance zone of highway tunnels with different spatial visual conditions. On-road tests were conducted on the drivers' visual characteristics and the speed were recorded in real time using an eye tracker and onboard diagnostic system. The variations in the eye movement features and speed in the entrance zone of the tunnels were analyzed. Then, statistical methods were conducted to examine the influence of the route familiarity and spatial visual conditions of tunnels on the driver behavior. The results demonstrated that the variations in the drivers' eye movements and speed were much more significant in the entrance zone of a tunnel without spatial intervisibility than in a tunnel with spatial intervisibility. The impact of this environmental transition on unfamiliar drivers was greater than that on familiar drivers. Road familiarity reduced the drivers' period of adaptation to the tunnel entrance environment and increased the driving speed.

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