_applied_  
_sciences_  
_Article_  
Sustainable Transport in a Smart City: Prediction of Short-Term Parking Space through Improvement of LSTM Algorithm  
[PERSON] 1, [PERSON] 2 and [PERSON] 2,*(c)  
Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))  
Footnote 2: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
Footnote 3: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
Footnote 4: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
Footnote 5: [[https://www.md](https://www.md)]([https://www.md](https://www.md))  
of the number of vehicles, resulting in serious parking problems and frequent urban traffic congestion. According to the data of the China White Paper on Parking Industry Development (2020) [7], there is a huge gap between the number of vehicles and parking spaces in China. This problem has led to a long-term failure to solve the parking problem in many big cities, especially in crowded commercial areas. The problem of parking difficulty in large cities must be controlled from three perspectives: city governors should continue to optimize urban roads and parking space [8; 9], solve the problem of high carbon emissions caused by the usage of fossil fuels by vehicles, and reduce the carbon emissions generated by unnecessary driving activities, such as car owners looking for parking spaces. From the perspective of enterprises, advanced information technology should be applied to improve service quality and operation efficiency. The innovative and practical parking guidance system [10] should also be developed to provide car owners with prediction information of both short-term and long-term parking spaces, in order to reduce carbon emissions, protect the environment, and relieve urban traffic pressure. Car owners would be able to improve their urban traffic awareness and quickly find parking lots and parking positions with such a system. Therefore, it is very necessary to develop a parking guidance information system with prediction algorithms in order to let car owners can find parking spaces purposefully, which would not only improve the efficiency of parking but also save time. In this way, carbon dioxide emissions and air pollution can be reduced, and the goals of smart city construction, carbon peak, and carbon neutralization can be better achieved. It is challenging to use the actual parking availability data in intelligent transportation systems and parking guidance systems because parking availability is a random process. With the change of time and location, the occupation information of parking spaces will also change. Therefore, improving the accuracy of parking guidance systems and providing accurate parking availability prediction services for car owners is the key to effectively solving the problem of \"parking difficulty\". The main purpose of this paper is to design, construct, and evaluate a prediction framework of parking space availability. The main contents are presented through the following contributions:  
1. In order to ensure the validity of the commercial block data about a big city, the data of eight commercial blocks with high vehicle access density, shortage of parking spaces, and urgent need for parking spaces are selected for analysis and evaluation. Figure 1: The statistics of private vehicle and passenger service vehicle from 2010 to 2021. 2. The improved LSTM, simple LSTM, MLR, and SVR algorithms are compared with MAE and RMSE, and the short-term prediction model is obtained to facilitate the more accurate real-time parking occupancy prediction for large-scale parking data.