Multicriteria Decision Making for Carbon Dioxide (CO2) Emission Reduction

The fast industrial revolution all over the world has increased emission of carbon dioxide (CO2), which has badly affected the atmosphere. Main sources of CO2 emission include vehicles and factories, which use oil, gas, and coal. Similarly, due to the increased mobility of automobiles, CO2 emission increases day-by-day. Roughly, 40% of the world’s total CO2 emission is due to the use of personal cars on busy and congested roads, which burn more fuel. In addition to this, the unavailability of parking in all parts of the cities and the use of conventional methods for searching parking areas have added more to this problem. To solve the problem of reducing CO2 emission, a novel cloud-based smart parking methodology is proposed. This methodology enables drivers to automatically search for nearest parking(s) and recommend the most preferred ones that have empty lots. For determining preferences, the methodology uses the analytical hierarchy process (AHP) of multicriteria decision-making methods. For aggregating the decisions, the weighted sum model (WSM) is adopted. The methods of sorting, multilevel multifeatures filtering, exploratory data analysis (EDA), and weighted sum model (WSM) are used for ranking parking areas and recommending top-k parking to the drivers for parking their cars. To implement the methodology, a scenario comprising cars, smart parkings are considered. To use EDA, a freely available dataset “2020testcar-2020-03-03” is used for the estimation of CO2 emitted by cars. For evaluation purpose, the results obtained are compared with the results of traditional approach. The comparison results show that the proposed methodology outperforms the traditional approach

iValet – A smart parking reservation system

In the current time with the continuously increasing population in the world generally and in big cities like Dubai particularly, many problems arise related to traffic and transportation. Due to covid-19 virus spread pandemic, WHO is submitting different regulations and recommendation for the need of social distancing along with avoiding any activities that might increase the possibility of the virus spread and minimize the number of infected people to save more lives. The need for decreasing the usage of the public transportation in Dubai have created parking issues in the city, streets, and buildings. One of the preferred solutions by people to overcome the long searching time for a parking lot and to reduce the fuel usage is to use the valet parking service in different city buildings, but many of them now are scared to allow strangers to use their car in the valet service. In this regard, the idea has emerged of having a smart parking reservation system that is connected with the RTA and the traffic police. The system consists of a hardware part implemented in the parking lot, and a software part where the user can search for a vacant parking spot and reserve it with in-advance payment using his/her smart phone

Greenhouse Gas Reduction Opportunities for Local Governments: A Quantification and Prioritization Framework

Local governments have steadily increased their initiative to address global climate change, and many present their proposed strategies through climate action plans (CAPs). This study conducts a literature review on current local approaches to greenhouse gas (GHG) reduction strategies by assessing CAPs in California and presents common strategies in the transportation sector along with useful tools. One identified limitation of many CAPs is the omission of quantitative economic cost and emissions data for decision-making on the basis of cost-effectiveness. Therefore, this study proposes a framework for comparing strategies based on their life cycle emissions mitigation potential and costs. The results data can be presented in a marginal abatement cost curve (MACC) to allow for side-by-side comparison of considered strategies. Researchers partnered with Yolo and Unincorporated Los Angeles Counties to analyze 7 strategies in the transportation and energy sectors (five and two, respectively). A MACC was subsequently developed for each county. Applying the life cycle approach revealed strategies that had net cost savings over their life cycle, indicating there are opportunities for reducing emissions and costs. The MACC also revealed that some emissions reduction strategies in fact increased emissions on a life cycle basis. Applying the MACC framework to two case study jurisdictions illustrated both the feasibility and challenges of including quantitative analysis in their decision-making process. An additional barrier to using the MACC framework in the context of CAPs, is the mismatch between a life cycle and annual accounting basis for GHG emissions. Future work could explore more efficient data collection, alternative scopes of emissions for reporting, and environmental justice concerns.View the NCST Project Webpag

Urban Freight Last Mile Logistics-Challenges and Opportunities to Improve Sustainability: A Literature Review

Last mile logistics (LML) is the least efficient and complex part of supply chain. The main objective of this study was to identify major challenges of urban freight LML and opportunities for intervention. For this, 42 peer-reviewed full papers published after 2010 and three additional references were used. The findings indicated that urban freight flow has a trend of steady growth. The main driving forces behind this steady growth are population growth, urbanization, densification, globalization, online and omni-channel (OC) retailing, and urban economic development. Using typology analysis, three main potential freight LML configurations were mapped and discussed. Freight LML configurations that involve light cargo vehicles and cargo bike-based delivery schemes could be more attractive freight LML models if the delivery failure is minimized. The LML challenges were categorized as technological, infrastructural, LML system and management, and logistic cost related challenges, and discussed broadly. Similarly, the potential opportunities were discussed from environmental, economic, and social sustainability aspects. Finally, this report has pinpointed future potential research agendas related to LML. The study could be a knowledge base useful for academicians and practitioners, logistics and technical service providers, policy makers, and customers

Solving Commuting Challenges with RTS Bus Rapid Transit (RTS-BRT) Rochester, NY

The public transport service in Rochester, NY, is inefficient in terms of reliability, safety, comfort, security, waiting, transfer, and longer commute hours. The public transportation system needs significant transformation to overcome this alleviating issue and relieve the burden on low-income residents, pedestrians, and non-motorized vehicle users. The research objective of this thesis is to advance and discover a connection pattern between transportation, urban sprawl, poverty, and unemployment in Rochester, NY. It targets the low-income resident’s detachment from diverse uses, residential settlement, locations of jobs, and transportation options. The research analyses how-: people commute to work, how long the commute takes, the rate of car ownership, and the financial burdens of owning a car. Furthermore, the research goes deeper into the energy demands and emission reduction caused by the transport sector. The data collection method used for the analysis is metanalysis, gathering data from local authority websites, organizations, research papers, and media. Sustainable transport can be a catalyst for urban development that prioritizes equity, accessibility, and time savings for the low-income commuter while reducing emissions and increasing traffic safety. Thus, all benefactors are a modal shift to lower-carbon transport systems such as walking, cycling, public transport, alternative fuel vehicles, modifying roads, and minimizing travel time. The scope of this study is to assess the environmental, social, and economic impacts caused by car dependency in Rochester, NY. As a result, the research probes the opportunities and challenges of leveraging Transit-Oriented Development (TOD) while introducing a Bus Rapid Transit (BRT) system

Optimizing energy consumption in smart cities’ mobility: electric vehicles, algorithms, and collaborative economy

Mobility and transportation activities in smart cities require an increasing amount of energy. With the frequent energy crises arising worldwide and the need for a more sustainable and environmental friendly economy, optimizing energy consumption in these growing activities becomes a must. This work reviews the latest works in this matter and discusses several challenges that emerge from the aforementioned social and industrial demands. The paper analyzes how collaborative concepts and the increasing use of electric vehicles can contribute to reduce energy consumption practices, as well as intelligent x-heuristic algorithms that can be employed to achieve this fundamental goal. In addition, the paper analyzes computational results from previous works on mobility and transportation in smart cities applying x-heuristics algorithms. Finally, a novel computational experiment, involving a ridesharing example, is carried out to illustrate the benefits that can be obtained by employing these algorithms.Peer ReviewedPostprint (published version

Big Data for Urban Sustainability: Integrating Personal Mobility Dynamics in Environmental Assessments.

To alleviate fossil fuel use, reduce air emissions, and mitigate climate change, “new mobility” systems start to emerge with technologies such as electric vehicles, multi-modal transportation enabled by information and communications technology, and car/ride sharing. Current literature on the environmental implications of these emerging systems is often limited by using aggregated travel pattern data to characterize personal mobility dynamics, neglecting the individual heterogeneity. Individual travel patterns affect several key factors that determine potential environmental impacts, including charging behaviors, connection needs between different transportation modes, and car/ride sharing potentials. Therefore, to better understand these systems and inform decision making, travel patterns at the individual level need to be considered. Using vehicle trajectory data of over 10,000 taxis in Beijing, this research demonstrates the benefits of integrating individual travel patterns into environmental assessments through three case studies (vehicle electrification, charging station siting, and ride sharing) focusing on two emerging systems: electric vehicles and ride sharing. Results from the vehicle electrification study indicate that individual travel patterns can impact the environmental performance of fleet electrification. When battery cost exceeds $200/kWh, vehicles with greater battery range cannot continuously improve travel electrification and can reduce electrification rate. At the current battery cost of$400/kWh, targeting subsidies to vehicles with battery range around 90 miles can achieve higher electrification rate. The public charging station siting case demonstrates that individual travel patterns can better estimate charging demand and guide charging infrastructure development. Charging stations sited according to individual travel patterns can increase electrification rate by 59% to 88% compared to existing sites. Lastly, the ride sharing case shows that trip details extracted from vehicle trajectory data enable dynamic ride sharing modeling. Shared taxi rides in Beijing can reduce total travel distance and air emissions by 33% with 10-minute travel time deviation tolerance. Only minimal tolerance to travel time change (4 minutes) is needed from the riders to enable significant ride sharing (sharing 60% of the trips and saving 20% of travel distance). In summary, vehicle trajectory data can be integrated into environmental assessments to capture individual travel patterns and improve our understanding of the emerging transportation systems.PhDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113510/1/caih_1.pd