Smart Loading Zone Applications for Urban Last Mile Delivery - Wahid, Robin (My University, 2020)
Last mile delivery has become increasingly difficult in urban areas; as population increases alongside the demand of the citizens, novel and smarter solutions are needed to cope with challenges of congestion and misuse of urban spaces, while at the same time sustainability goals need to be taken into consideration. The smart city concept has become the next step for the future transformation of our society. Smart cities strive towards creating better welfare for its citizens in an urban area to reach sustainable consumption of resources. This is done by leveraging technological tools such as IoT, Big Data analytics and ICT. Similarly, smart cities include smart parking which helps to facilitate the process of monitoring, controlling, and parking by the mentioned digital and technological tools. However, previous and current smart parking solutions have almost entirely been developed for passenger cars and not for commercial freight vehicles which park on so called loading zones (LZs), in order to perform loading/unloading activity for parcels and goods delivery. The purpose of this study is to investigate the concept of smart LZs, including the definition of a smart LZ, what factors inhibit the deployment and operations of LZ use and management and lastly, how smart LZs can be implemented in Sweden. This was done by using a qualitative research approach, by analyzing semi-structured interviews and a pre-recorded focus group of relevant stakeholders: truck manufacturer, smart parking provider, urban strategists from different municipalities and logistics providers. A smart LZ should, with the help of smart technological systems, improve overall operations of last mile delivery and loading/unloading activities for the operators. The findings showed that there is no clear definition of a smart LZ; the empirical data suggest that smart LZs should be digital, having cameras or sensors, and a widely spread system for operators to interact with, like a smartphones app. Furthermore, smart LZs should provide real-time data of occupancy to facilitate operations for logistics providers. Combining the empirical data and literature review, three components were derived of what a smart LZ requires; sensing technology to gather data, predictive data analytics tools to analyze data and lastly, a user interface which could be a smartphone app to display analyzed data for the operators. There are three holistic steps to implement optimal smart LZ solutions efficiently; the first step in developing a smart LZ is to gather data to understand the underlying problem of the LZs, this can be done via sensors placed at LZs. The next step is to involve all the relevant stakeholders including enforcement agencies, policy makers, smart parking developers, municipality/transport department and logistics providers. The last step is to do a pilot of the full system with no compromises before deploying the system on a large scale. However, the findings showed that there are several inhibiting factors for smart LZ deployment and operations in Sweden; counterproductive policy, regulation, legislation, lack of knowledge and data of LZ utilization, not being able to book LZs, not paying for LZs or having time limits which could potentially lead to a lack of enforcement, built-in incentives for the city to decrease the number of LZs and increase the number of parking spots for passenger cars due to monetary reasons and sustainability goals overshadowing smart LZ initiatives.