Problem of freight vehicle parking: towards dynamic management of delivery areas.
The subject of my thesis involves addressing the problems caused by freight vehicle parking. The various negative impacts this has (including blocking streets, noise, unsafe roads, atmospheric pollution and additional costs) are compounded by such poor practices as double parking. Moreover, a static network of delivery areas, however great its reach, is not the ultimate solution to all of these problems since they are seldom documented in any objective manner.
On the basis of these observations, we aim to define an urban parking system where the status (delivery area vs parking space) of all of the parking spaces it manages can switch in real-time and autonomously. The system must therefore be able to predict the use made of its spaces and to assign them to the carriers requesting them. This is how we came up with a tool comprising two modules.
The first considers, by way of input data, the destination zone, day and exact time of delivery. By way of output data, it provides the number of available spaces, their coordinates and the likelihood of them remaining free. With that in mind, we are developing a supervised machine learning approach. We are looking to capitalise on several different models for better generalisation of results.
The second module assigns a delivery area to each carrier with account taken of space availability, vehicle size and walking distance. To decide between two drivers heading to the same destination, the amount of freight is a decisive factor. This means that the delivery address, vehicle used and the freight amount form the input data, along with the output of the first module. To solve the problem of the suitability of the parking space for the size of the vehicle, it is possible to combine two consecutive available spaces. Two different approaches are proposed for that: one based on mathematical programming techniques and the other on fuzzy logic.
Hanae Errousso was born in 1994 in Tangier, Morocco. She passed her experimental sciences high school diploma, with physical sciences as her elective subject, when she was 18. She graduated from the Faculty of Sciences and Technologies in 2014 with a Diploma of Higher Education (DEUST) with Maths, IT, Physics and Chemistry (MIPC) as her elective major. Three years later she was awarded the state engineering degree in industrial engineering, with industrial organisation and management as her elective major, by the same institution. In December 2018, she enrolled in the National Graduate School for Electricity and Mechanical Engineering (ENSEM) as a PhD student in the Engineering Research Laboratory. She is writing her PhD thesis on urban logistics at the Foundation for Research, Development and Innovation in Science and Engineering. She has undertaken a range of scientific contributions under the supervision of EIGSI faculty. Her main research activities are devoted to private vehicle parking, urban freight delivery, smart transport systems and urban land use.