It is considered as an important and effective means to give priority to the development of public transit which can improve the efficiency of transportation resources utilization and alleviate traffic jams. Public transit signal priority belongs to the "time priority" among the right-of-way priorities. After reviewing the existing bus priority signal control strategies and the advances in related technologies at home and abroad, this article analyzed the breakthrough direction of the bus signal priority design technologies suitable for China's conditions, and then proposed the hardware and software systems and the modules for the bus priority signal control system. Finally, the hardware-in-the-loop simulation (HILS) was introduced to evaluate bus priority signal control programs in order to optimize the control strategies.
Based on an available parking space occupancy （APSO） survey conducted in Nanjing, China, an APSO forecasting model is proposed. The APSO survey results indicate that the time series of APSO with different time-sections are periodical and self-similar, and the fluctuation of the APSO increases with the decrease in time-sections. Taking the short-time change behavior into account, an APSO forecasting model combined wavelet analysis and a weighted Markov chain is presented. In this model, an original APSO time series is first decomposed by wavelet analysis, and the results include low frequency signals representing the basic trends of APSO and several high frequency signals representing disturbances of the APSO. Then different Markov models are used to forecast the changes of low and high frequency signals, respectively. Finally, integrating the predicted results induces the final forecasted APSO. A case study verifies the applicability of the proposed model. The comparisons between measured and forecasted results show that the model is a competent model and its accuracy relies on real-time update of the APSO database.
