Dynamic Traffic Flow Entropy Calculation Based on Vehicle Spacing

In information theory, entropy is a measure of uncertainty. The higher the degree of chaos in a system, the higher its entropy. The concept of entropy has also been applied to the evaluation of transportation systems. Because of the limitation of the existing traffic information collection technology, an entropy-based evaluation method has not been widely applied. With the development of on-board sensors and the Internet of vehicles, vehicle spacing information will be easier to acquire and transmit in real time; furthermore, traffic flow entropy will be calculated in real time. Based on the vehicle spacing on the road, the proportion of the distance between the vehicles was taken as the input data of the entropy calculation, and the summation result was normalised and corrected to obtain the calculation corresponding to the entropy and the degree of disorder. On this basis, the entropy values at different moments were repeatedly calculated, and the dynamic traffic flow entropy on the road segment was summarised. We constructed a one-lane road segment model in the simulation software, recorded the vehicle information, and calculated the dynamic traffic flow entropy. A comparison of the difference in the traffic flow entropy between different proportions of heavy goods vehicles revealed that a large proportion of the heavy goods vehicles corresponded to a large traffic flow entropy, indicating a large degree of disorder. The simulation results showed that the proposed method has good scientific value and is practical.