Generating Believable Mixed Traffic Animation

Abstract

We present an agent based approach to animate microscopic mixed traffic involving cars and motorcycles in complex scenarios, including signalized and nonsignalized road intersections, and traffic jams due to blockage. Based on our new car-following and lateral-movement models, our method can reproduce lane-based and non-lane-based traffic behaviors that are commonly seen in urban scenes. Our dynamic routing and intersection procedures enable a user to interactively control the movement of a car and our system generates the microscopic behaviors of the influenced vehicles accordingly. Experimental results show that our approach can animate appealing microscopic mixed traffic with various behaviors. Our approach will benefit applications in virtual cities, computer games and driving simulators.

Publication

Wen-Chieh Lin, Sai-Keung Wong, Cheng-Hsing Li, and Richard Tseng, "Generating Believable Mixed Traffic Animation", To appear in IEEE Transactions on Intelligent Transportation Systems.

Result
Please click the image to watch the video.

Main Video :


Impact of space-oriented lane changing
Fig. 12


Additional result, Traffic light turns red at 0th and 55th second


Influence of Phi_j weighting--
MTS: weight only the first term of Eq 5;
MTSa: weight all terms of Eq 5.
MTSa produces smaller spacing between leaders and followers.


Experiment 1
Comparison of car following models: IDM, CAH, MTS, MTSa;
Initial speed of the yellow car = 100 km/hr