Multiple-Criteria Decision Analysis of Urban Planning Methods towards Resilient Open Urban Spaces

Cities are dynamic systems that need to plan for development with resilience, while facing an increasing set of multidimensional challenges and emerging operating trends (e.g. Smart Cities) (Schmitt, 2015). In the framework of new Urban Strategies (Digital Europe Program, 2021-2027; Green Deal, 2019), local authorities play a key role in making the right decisions for covering current and future needs. Public/outdoor urban spaces are vital parts of cities as they define citizens’ quality of life and the ability of cities to respond to urban challenges. In this context, this research aims to support the decision-making process for shaping, designing and managing public/outdoor urban spaces by using measurable and multicriteria indicators to evaluate alternative climate-sensitive design and regeneration plans of urban areas within risk and uncertainty. Emphasis is placed on both supply and demand for outdoor urban areas. Demand is studied by disaggregate analysis for identifying citizens’ needs through questionnaire survey. Supply side is placed at the center of the research by developing a multiple-criteria assessment methodology of urban planning methods. The main evaluation criteria involve the bioclimatic impact of the studied methods, the air pollution detected in microclimate as well as financial cost for their implementation and operation. In particular, questionnaires’ results revealed that citizens prefer open spaces as they provide a feeling of freedom and the chance to be closer to nature. Based on these, citizens visit open spaces with green areas, incoorporating nature based solutions, as well as places that support walkability and green mobility. In addition, simulation and cost assessment results regarding the studied methods showed the planning solutions involving medium size plants and greenery are low cost interventions, creating favorable microclimate conditions and leading to medium CO2 concentration. The benefit of the current research is in the innovative, interdisciplinary and holistic approach of a complex real-word problem combining different research areas, such as environmental science, bioclimatic urban planning and decision-making process. The multiple-criteria analysis of urban plans leads to a model of the decision-making process on open urban spaces to enhance citizens’ quality of life and to ensure urban resilience as well as cities’ operational and sustainable future

Enabling Sustainable Freight Air Transport in the Adriatic Region through Development of ICT Platform

Freight transport in the Adriatic area suffers from persistent organizational, operational and service barriers and the negative impacts of road transport. Multimodal interventions could reduce CO2 emissions and other impacts, including air and noise pollution, and road congestion. Integrated sustainable solutions can act to improve traffic flow and logistics, and management of goods and tourism supply. Multimodal optimization of road-sea combined transport can be augmented to include air modal share on existing and new routes for sensitive freight with emphasis on yearlong operations. This paper adresses the need to improve and extend the availability of passenger routes to allow the potential for mixed cargo in the Adriatic with a case study in Italy-Greece transport. Such plans are hampered by the overlong (up to 15 hours) duration of air trips, which could reduce product quality within a few hours after harvest. Fast shipment and delivery of affordable fresh products, such as mozzarella and strawberries is essential, and would benefit from nonused passenger cargo. Fresh products could use available hold space, guaranteeing lower-than-conventional shipping time at affordable price. The new service would establish new shipping options for fresh products, empowering Italian and Greek local producers. The service will be enabled through an integrated ICT platform that was developed to offer user access (e.g. to information on departure time, load space availability, goods allowed for transportation), and facilitate creation of new market opportunities for fresh producers. The platform supports the identification of demand and supply (by creating accounts as seller or buyer) and the booking of transport. The platform end user (seller or buyer) can find the proper passenger carrier for shipping fresh products to the airport of origin. Platform design includes Operational (OR) and NonOperational (NOR) requirements. For assuring traceability and location information, static and dynamic RFID tags and portable RFID readers, as well as GPS devices and/or tracking smartphones and supporting infrastructure were included

Development and application of incident detection techniques to improve incident management in freeway corridors

Responding to the need for effective and reliable detection of freeway incidents, an essential element for improved traffic management and control in freeway corridors (Stephanedes and Chang, 1991), the authors initiated this research to investigate the performance limitations of conventional automatic incident detection systems and define the specifications for a new algorithmic logic that can lead to improved detection performance. The research initially focused on assessing the ultimate detection performance that can be accomplished with existing and new incident detection systems that use traffic data from presence detectors. A new algorithm was developed and tested against the major existing ones with promising results towards the development of a more-sophisticated detection structure. All tests employed a unified system of performance assessment (Stephanedes and Chassiakos, 1991), suitable for direct algorithm evaluation. The major accomplishments of this project are: * Review of current incident detection algorithms. * Testing major existing algorithm in the Twin Cities Freeway system. * Development of data preprocessing techniques to enhance the incident signal. * Development and testing of incident detection algorithms based on the data preprocessing.Center for Transportation Studie

Transportation and Economic Development

This report summarizes the results of a project undertaken by a University of Minnesota team for the Minnesota Department of Transportation (Minnesota DOT) to determine the existence and extent of relationships between transportation and economic development (in particular, employment) in Minnesota. The interdisciplinary team was directed by the Department of Civil & Mineral Engineering and included experts from Civil & Mineral Engineering, Geography, Economics (both Twin Cities and Duluth campuses), Applied & Agricultural Economics, Industrial Engineering & Operations Research, and Regional Economics.Stephanedes, Yorgos J.. (1988). Transportation and Economic Development. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/157102

Transit System Monitoring and Design

Statistical techniques were developed for extracting the most significant features (indicators) from a transit system data base, and classifying proposed and existing transit systems according to the selected features. The data base was constructed by using information from all previous years available by the Mn/DOT, the Census and other sources to be used in classifying transit systems. The data base emphasized the use of raw characteristics of the operating system and the area socioeconomics. The feature extraction was done so that the minimum number of features were extracted that can be used for classifying the transit systems with maximum accuracy. The classification method was designed around the data base and is flexible so that it can use future data to update the data base at minimum cost. The transit system patterns, resulting from the classification method, were identified according to need and performance, and the main characteristics were specified for each pattern. These characteristics and descriptions identifying each pattern determines whether it should be modified. A controlled experiment was required to test the classification method. A randomly selected part of the data was classified by the method, and then the unselected data was treated as a control group for the experiment. After the experiment a percent of misclassifications was calculated.Minnesota Department of TransportationStephanedes, Yorgos J.. (1990). Transit System Monitoring and Design. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/157095

Urban Congestion Reduction for Energy Conservation: Control Strategies for Urban Street Systems: A State of the Art: Final Report

The primary objective of this study is to acquire an understanding of the current state-of-the-art of traffic signal control strategies at urban street systems. Control of traffic signals is by far the most common type of control at heavily trafficked intersections in urban areas. Inefficient use of the transportation system results when traffic signals are set without the aim of optimizing them. The byproducts of such situations include greater fuel consumption, increased vehicle emissions, increased travel time, higher accident rate, and less reliable services.Hajjiri, Samir A.; Stephanedes, Yorgos J.. (1988). Urban Congestion Reduction for Energy Conservation: Control Strategies for Urban Street Systems: A State of the Art: Final Report. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/157103

Applications of Advanced Technologies in Transportation Engineering

Capr

Techniques for Detection of Incidents and Traffic Disturbances

The increasing contribution of incidents to freeway congestion has generated strong interest in the development of incident detection algorithms in the last two decades. According to Federal Highway Administration estimates (Lindley, 1986), incidents currently account for up to 60% of the vehicle-hours lost to freeway congestion; projection for the year 2005 indicates a 70% contribution of incidents to total delay. Fast and accurate detection of incidents can, therefore, substantially reduce the impact of incident congestion on freeway traffic. In particular, when an incident alarm is promptly signaled, traffic management plans can be adjusted in real time to produce the best control and guidance actions in freeway corridors. In addition, the incident management process (detection, response, and clearance) is initiated as emergency vehicles can be promptly dispatched to clear the incident. Existing techniques for the detection of freeway incidents do not provide the necessary reliability for freeway operations. Conventional automated techniques, based on computerized algorithms, are less effective than is desirable for operational use because they generate a high level of false alarms. Operator-assisted methods minimize the false alarm risk, but suffer from missed or delayed detections, are labor intensive, and restrict the potential benefits from advanced, integrated traffic management schemes. The initial phase of this research focused in assessing the performance limitations of conventional automatic incident detection systems. That research was directed towards two objectives, the performance evaluation of major existing algorithms and the development of an improved algorithm. This part of the research pointed out that the existing techniques for the automatic detection of freeway incidents are not reliable as they are seriously handicapped by excessive, operationally unacceptable false alarm rates. The new algorithm proposed by the authors was developed for identifying capacityreducing incidents in freeway traffic. That algorithm aims to minimize the number of false alarms that the existing algorithms generate when temporal random oscillations in the traffic measurements, frequently observed in congested flows, occur. The proposed structure involved preprocessing the traffic data with average, median, or exponential smoothers over data windows of approximately five minute length to eliminate or reduce the size of traffic fluctuations. Although the new algorithm showed an improved and satisfactory performance relative to the conventional algorithms, the initial stage of this research pointed out the need of more research in finding ways and methods for distinguishing between the incident and the non-incident alarms and highlighted the issues that had to be addressed by the second stage of this project.Center for Transportation StudiesStephanedes, Yorgos J.; Vasilakis, George. (1994). Techniques for Detection of Incidents and Traffic Disturbances. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/156691