RESUMO
This study examines the differences in service level and coverage of public transit (PT) and private vehicles (PV) with multi-source data in Shanghai. To construct computable networks and address visual results, the constrained shortest path algorithm and a spatial grid accessibility model are employed to seek the optimal path for travelers to city key points. Travel time ratio of PV and PT is applied to reflect the competitiveness of the two modes over different areas of Shanghai. Results show that for PV, although the average travel time meets the needs of car travel, 51 % of the population cannot get to graded city centers within 45 min. In addition, the PV accessibility gradually weakens from the central city to the outside, highways and expressways may be feasible solutions. For PT, half of the population can't reach any city key points within two transfers, and almost all of these people live in the suburbs. Less than 30 % of the population can reach the city key points within 1 h, of which rail transit contributes more than conventional buses. Furthermore, the travel accessibility of PV is much better than that of PT. The average travel time ratio in all comparable grids is 2.04 for hubs, and 2.10 for graded city centers. For travels to graded city centers, the travel time ratio of suburbs is 35 % higher than that of central city, indicating that the inequity distribution of public transportation resources is worse in the suburbs than in the central city. This study also measures equity performance of groups based on spatial location and income level, and we find out that more core locations and higher income lead to higher accessibility. The gap among groups is significant, with a Gini coefficient over 0.5.
