The SINERGI project brings together private and public stakeholders who will conduct pilot initiatives in five major cities in Europe and Asia. What use cases will be developed and tested in these pilots?
Amsterdam, the Netherlands
Amsterdam, with a population of about 825,000, is renowned for its innovative approaches to sustainable mobility and transport. The modal share includes 25% for public transport, 8% for private vehicles, 43% for bicycles, and 24% for walking. The city is increasingly confronted with challenges related to the impacts of climate change and the livability of a growing urban center.
Especially in the years following Covid-19, Amsterdam witnessed a surge in demand for home delivery services, particularly in the realm of food delivery. These services heavily rely on micro-delivery methods, such as e-bikes and e-scooters, contributing to elevated traffic and accidents in bike lanes.
SINERGI prioritizes the safety and convenience of both riders and citizens while ensuring the efficiency of micro-deliveries in Amsterdam. Decisions related to rebalancing, dispatching, and routing now consider the well-being of riders, aiming to reduce their work pressure and ensure a fair distribution of tasks across the network.
Copenhagen, Denmark
The City of Copenhagen enjoys a global reputation as a bike-friendly city with high traffic, attributed to both mobility and delivery purposes. The prevalence of bike traffic contributes to a significant number of accidents.
SINERGI is developing a data-driven and AI-based optimization framework that utilizes real-time bike lane traffic data to identify hazardous bike lanes at various times of the day and in different parts of the city. The real-time recommended routes for delivery riders incorporate processed information, aiming to reduce the anticipated number of accidents in Copenhagen.
Singapore
In Singapore, a city-state with a population of over 5.7 million, the on-demand food delivery (OFD) market has experienced significant growth, driven by advancements in mobile and wireless communication technologies. The city’s high population density and diverse culinary scene present unique logistical challenges for efficient food delivery. To address these, a novel initiative has been developed focusing on optimizing the customer service area and driver dispatch area for each restaurant. This involves dynamically balancing supply and demand by adjusting the areas within which customers can order and drivers can deliver, respectively.
The approach combines discrete choice models, machine learning, and mathematical programming, leveraging real datasets from a local OFD platform. This data-driven framework aims to maximize the total number of orders while maintaining service level requirements for delivery times. A unique ‘model tree’ prediction model is integrated into this system, leading to an efficient solution through a Mixed Integer Quadratically Constrained Program. This innovative methodology has shown significant improvements in operational efficiency and customer satisfaction in empirical tests, positioning Singapore as a model for urban logistics optimization in the food delivery sector.
Shanghai, China
Shanghai has a population of over 24 million people, making it one of the most populous cities in the world. In terms of area, Shanghai covers approximately 6,340 square kilometers. Shanghai has a well-developed instant delivery ecosystem, providing quick and convenient solutions for a wide range of products and services. The major players include Meituan, Ele.me, JD.com, Dingdong, employing a vast network of couriers and leveraging technology for seamless operations. Customers can order a variety of goods, from food and groceries to electronics and even household items, and expect swift delivery often within the hour. The infrastructure in Shanghai, including its extensive transportation system and dense urban layout, contributes to the efficiency of these services. The prevalence of mobile payment methods also facilitates quick and hassle-free transactions.
The surge in demand of instant fresh product delivery especially after Covid-19 calls for sophisticated plans on where to locate mini hubs (consolidation centers) to use the available space while improving the service level. SINERGI focuses on the mapping of such mini-hubs in a two-echelon urban instant delivery system. On top of that, efficient algorithms for dispatching, routing, and fleet management strategies will be developed while explicitly taking riders and consumers behavior into account, with the aim to make the instant delivery experience in Shanghai both reliable and sustainable.
Beijing, China
In the bustling city of Beijing, a capital city with over 20 million residents, online food delivery services have become integral to the urban fabric. Beijing’s diverse cuisine offerings, ranging from traditional delicacies to global flavors, have found a convenient way to reach its customers, allowing residents to savor a multitude of dishes at their fingertips.
The SINERGI team aims at addressing several pivotal challenges faced by online food delivery platforms, namely, determining the restaurants displayed, their delivery fees, and the corresponding placement on the users’ phone screen. These decisions hinge on a delicate balance between user preferences, restaurant partnerships, and platform profitability. The SINERGI team will design algorithms that consider user history, cuisine popularity, geographic proximity, review rating, and so on. The goal is to improve the operational efficiency of the platforms and better serve the customers.