A personalized route guidance approach for urban travelling and parking to a shopping mall

When a driver travels from home to a shopping mall in China, a common issue is that though the chosen parking lot has enough parking spaces prior to departure, they are likely to be occupied when the driver arrives. For it, a two-stage route guidance approach is proposed in view of the driver's personal demand for parking. It utilizes the multinomial logit model to calculate the personalized utility of every available parking lot. In the first stage, an optimal path is planned from origin to an intersection close to the shopping mall. In the second stage, the optimal paths from the intersection to multiple available parking lots will be planned, and then one path is selected according to the personalized utility. Space can be considered as 'a buffer' for drivers in which the utilities are calculated. The paper emphatically describes the buffer and proposes an algorithm to solve it. The advantages of the proposed approach are demonstrated by the experiments implemented with real traffic data. The results verify the effectiveness and applicability of the proposed approach.