Study On The Public Parking Location Based On Low-carbon Travel

With the growth of+ the GDP in china,the urban traffic has also entered into a rapid development.The rapid increase of vehicle ownership has lead to "urban traffic pollution" and "parking difficult" problem.Based on the structure of residents' travel in our country,this paper established the optimization model of traffic structure with low carbon as the goal.By optimizing the traffic travel structure,the motor vehicle travel has reduced.At the same time,the basic parking demand is fundamentally compressed and then we made a further study of the urban public parking lot site construction.The main contents of the thesis include the following aspects:First.The parking characteristics affect the city public parking lot location,there are some differences of characteristics between the parking lot.This paper summarizes the supply and demand of different types of parking lots based on the actual survey data.It is found that the berth turnover and peak parking index of residential and large hospital parking lots are high,the parking characteristic index of P+R parking lot are related with its use nature and management policy,while the utilization of some commercial parking lot is relatively low.Based on this,this paper analyzed the main factors that affect the location of urban public parking lot.Second.Urban motor vehicle ownership is the main factor for parking demand and the optimization of urban passenger traffic structure based on low carbon can significantly reduce the motor vehicle ownership.Taking that the rapid growth of motor vehicle ownership is the most direct cause of parking demand can't be met into account,this paper established a low carbon target urban passenger transport structure optimization model.And taking Beijing as an example,this paper,combining with low carbon target traffic structure optimization,explored the low carbon traffic travel patterns and the basic scenarios of travel mode carbon emissions.The results show that the CO2 emissions in the low carbon transport model will be 19.2%lower than the basic scenario in 2020,the proportion of car travel will be reduced by 5%,and the proportion of public transport will increase by 8%.Third.Parking demand has the relationship with the way residents travel,and the traditional parking demand forecasting method didn't take the residents' travel structure into account.This paper puts forward the forecasting method of parking demand based on residents' travel.Based on the principle of urban public parking lot selection,the urban public parking lot location model is established,and the algorithm of unbalanced transportation is calculated and solved by MTATLAB.Through the concrete case analysis,the results show that the urban traffic travel structure under the low carbon scenario can significantly reduce the parking demand and construction cost,while the parking lot gap in the basic scenario is about 3.7 times of the low carbon mode,which means to improve the urban traffic travel structure is an important way to improve traffic pollution and parking problems.