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Many pavement distress (PD) indexes are defined only from the perspective of the PD physical structure, which cannot describe the change of traffic efficiency. Some PD indexes are defined considering the influence of traffic efficiency, but it is unpractical to calculate them out due to their complex processes. We quantify the impact of the cohesive whole of PD points on the traffic flow and also define the corresponding PD index which is easy to compute. Firstly, the lane cell based on the idea of road discretization is introduced. Secondly, the PD degree for the lane cell is defined by the reduction of the average vehicle speed given the same flow condition. The cell whose PD degree is larger than 0 is defined as the PD cell. Then, considering (1) the ratio of PD cells, (2) PD cell distribution, and (3) the influence of the vehicle lane changing, we define the holistic road-damage degree (HRDD) as the PD index. At last, the relationship among HRDD, flow speed, and flow volume is analyzed through the simulated experiments. The results show that (1) the average speed is inversely proportional to HRDD, and the reduction of vehicle speed is more significant with the increase of the traffic flow input; (2) the inverse relation between road capacity and HRDD can be seen on the whole HRDD range. In another word, the proposed HRDD describes the change of traffic efficiency indeed.

Sharing economy uses the Internet platform, speeds up the flow of resources, improves resource utilization also conforms to the concept of modern development. Located in the Yangtze river delta economic belt, Changzhou is facing the transformation and upgrading stage of three traditional industries. Through the concept of sharing economy, it encourages the sharing of collaborative innovation, strengthens the cooperative technology development of manufacturing industry, and stimulates the transformation and upgrading of consumption. Using big data to mine demands, effectively manage and eliminate backward production capacity to achieve. Based on green development concept, build a new economic growth point.

The reduction of carbon emissions has become a heated background topic in the context of climate change. This paper estimates the potential for carbon reduction from the use of public bikes, on the basis of a travel mode choice model and a carbon emission calculation model. A probability model for the travel mode choice is built to predict travel demands of different modes, and is based on the Logit-based stochastic user equilibrium model. According to this, the generalized travel cost of choosing to walk increases with distance, but the cost of choosing a taxi decreases with distance. When the trip distance is 1.4 km, the walk cost equals to that of the taxi, while if the trip distance is smaller than 1.4 km, the probability of the walk is larger than of a taxi, and vice versa. The case of Ningbo is analyzed. Based on the monthly travel data, the travel characteristics of the public bikes are first analyzed; these indicate that the medium travel distance is 1.44 km, and that the number of trips less than 1.6 km accounts for 70% of all trips. This reveals that the public bike trips are mainly short-distance and in workday rush hour. The related carbon emission reductions of Ningbo on average are 1.97 kg/person and 1.98 kg/km2, and the reductions are positively linearly related to the average hourly total turnover rate, which means the turnover rate is a great parameter to reflect the capability of carbon emission reductions.