Economical and Environmentally Friendly Geocast Routing in Vehicular Networks

The volatile world economy has greatly affected fuel prices, while pollution and gas emissions are increasing to negatively impact global warming. Rising fuel costs have made drivers more concerned about how much of their monthly budgets are allocated for gasoline. In terms of the air pollution problem, greenhouse gas (GHG) emissions from vehicles are considered to be one of the main contributing sources. Carbon dioxide (CO₂) is the largest component of GHG emissions. As a result, it is important to develop and implement effective strategies to reduce fuel expenditure and prevent the expected increase of CO₂ emission from vehicles. Vehicular networks offer a promising approach that can be applied in transportation systems to reduce fuel consumption and emissions. One of the major applications of vehicular networks is intelligent transportation systems (ITS). To exchange and distribute messages, geocast routing protocols have been proposed for ITS applications. Most of these protocols focus on improving network-centric performance measures (e.g., message delay, packet delivery ratio, etc.) instead of focusing on improving the performance measures that are meaningful to both the scientific community and the general public (e.g., fuel consumption and CO₂ emission). Stop-and-go conditions, high acceleration, and unnecessary speed are uneconomical and environmentally unfriendly (UEU) actions that increase the amount of vehicle fuel consumed and the CO₂ emission. These actions can happen frequently for vehicles approaching a traffic light signal (TLS). This thesis proposes a new protocol named Economical and Environmentally Friendly Geocast (EEFG), which focuses on minimizing CO₂ emission and fuel consumption from vehicles approaching a TLS. The goal of this protocol is to deliver useful information to approaching vehicles inside the regions of interest (ROIs). Based on the information sent, the vehicle receiving the message adapts its speed to a recommended speed (Sʀ), which helps the vehicle reduce its UEU actions. To determine the value of Sʀ, a comprehensive optimization model that is applicable in both vehicle-to-vehicle (V2V) communication and traffic light signal-to-vehicle (TLS2V) communication is developed. The objective function is to minimize fuel consumption by and emissions from vehicles. The speed that can achieve this goal is the optimum Sʀ (Sʀ*). The thesis also proposes efficient heuristic expressions to compute the optimum or near-optimum value of Sʀ. An extensive performance study of the EEFG protocol is performed. It shows the impact of using EEFG in a modeled real-world network for urban and suburban areas in the city of Waterloo, Ontario, Canada. Four case studies have been considered: (1) a suburban environment at the maximum traffic volume hour of the day; (2) a suburban environment at the minimum traffic volume hour of the day; (3) an urban environment at the maximum traffic volume hour of the day; (4) an urban environment at the minimum traffic volume hour of the day. The results show that EEFG saves fuel and CO₂ emission in all four cases. In addition, the thesis studies the effect of communication parameters (e.g., transmission range, packet delay, and packet dropping rate) on vehicle fuel consumption and CO₂ emission. Having high transmission range, low packet delay, and low packet dropping rate, can save more fuel and CO₂ emission

Impact of Stoplight Policies on Urban Traffic System Emissions

With increasing urban populations (Boyd 2015), also comes higher land resource demands and more concentrated pollution levels. Increasing the efficiency of transportation systems is key to fostering sustainable urban development because it can decrease urban pollution levels, better meet the social demands of its residents, and decrease vehicle fuel consumption – encompassing the three pillars of sustainability: social, environment, and economic. This study aims to better understand the environmental impact of traffic light coordination and their timing policies in a randomly generated traffic network on an urban area. We focus on the effect of three different stoplight policies on emission and congestion. Transportation is a basic human need and an area of sustainable development with great potential. The United Nations states that achieving sustainable transportation is a key component in the development of sustainable cities across the world (United Nations 2016). The number of vehicles on the roads are increasing, as are their emission levels (Environmental Protection Agency 2017). In the United States alone, over 263 million vehicles were registered by 2015 (Bureau Of Transportation Statistics 2015). The coordination of stoplight timing has the potential to mitigate not only traffic-related congestion, but also traffic-related emissions. An acceleration following either a deceleration or a complete stop due to a red light that has turned green is responsible for significantly more carbon dioxide (CO2) emissions than cruising at a constant speed when approaching a green light (Ericsson 2001). Congestion decreases the fuel efficiency of all vehicle types on the road (Bigazzi, Clifton and Gregor 2014). With decreased fuel efficiency comes increased CO2 emissions (Barth et al. 2007). Stoplights are responsible for much of vehicles’ halts and changes in acceleration. Depending on the sequences of the traffic lights and the flow of traffic, the lights can both cause and relieve congestion, especially in large cities because of the high concentration of intersections with traffic lights. Just in New York City there were 12,460 recorded intersections that were stoplight-regulated (NYC DOT 2012), and out of the 3,360 intersections found in the Manhattan borough (Howe 2010), 2,820 of them are operated by traffic lights (NYC DOT 2012). In this study, three stoplight timing policies are assessed for their effect on vehicle emissions for random traffic scenarios on a given downtown area. Without loss of generality, vehicle emissions are assumed to be primarily caused by acceleration and deceleration. Traffic is modeled using a variation of a cell transition model to capture traffic as density-dependent flows (Daganzo 1995). To block any secondary effects in the system, all vehicles are assumed to have identical characteristics. This study assumes 100% penetration of vehicle autonomy, or in other words driver-less vehicles. It also assumes vehicle-to-infrastructure (V2X) technology, which includes vehicle-to-vehicle (V2V) communication of the vehicles’ locations and speeds as well as communication with other network infrastructure such as traffic lights. These vehicle assumptions aid in the simplicity and accuracy of the cell transmission model application. V2X is also known for its potential to improve traffic safety and decrease idling time (Abboud, Omar and Zhuang 2016). We compare the performance, as captured on the total emission levels of traffic controlled by three stoplight timing policies: a conventionally timed traffic light system, a system with traffic flow-dependent lights, and a light-less system

Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time

Cooperative ITS is enabling vehicles to communicate with the infrastructure to provide improvements in traffic control. A promising approach consists in anticipating the road profile and the upcoming dynamic events like traffic lights. This topic has been addressed in the French public project Co-Drive through functions developed by Valeo named Green Light Optimal Speed Advisor (GLOSA). The system advises the optimal speed to pass the next traffic light without stopping. This paper presents results of its performance in different scenarios through simulations and real driving measurements. A scaling is done in an urban area, with different penetration rates in vehicle and infrastructure equipment for vehicular communication. Our simulation results indicate that GLOSA can reduce CO2 emissions, waiting time and travel time, both in experimental conditions and in real traffic conditions.Comment: in 22nd ITS World Congress, Oct 2015, Bordeaux, France. 201

Lead as a tracer for automotive particulates: projecting the sulfate air quality impact of oxidation catalyst-equipped cars in Los Angeles

An analysis of the fate of lead in the Los Angeles Basin is used to evaluate an emissions to air quality model for automotive exhaust particulates. The dispersion model is then applied to projecting the annual average sulfate air quality impact of direct sulfuric acid mist emissions from oxidation catalyst-equipped cars of the 1975 model type. Estimates are given of the incremental sulfate contributions from three model years of oxidation catalyst-equipped cars burning a relatively low sulfur gasoline, and from roughly ten model years of 1975-type autos burning gasoline of sulfur content equal to that of the entire 1974 Southern California gasoline pool. In the latter case, sulfate concentrations in portions of downtown Los Angeles in 1985 could be elevated by roughly two thirds above present average sulfate values

International Fuel Tax Assessment: An Application to Chile

Most developed and developing country governments levy taxes on gasoline and diesel fuel used by motor vehicles. However, outside of the United States and Europe, automobile and heavy truck externalities have not been quantified, so policymakers have little guidance on whether prevailing tax rates are anywhere close to their corrective levels. This paper develops a general approach for roughly gauging the magnitude of motor vehicle externalities, and hence the corrective tax on gasoline and diesel, for individual countries, based on pooling local data sources with extrapolations from U.S. data. The analysis is illustrated for the case of Chile, though it could be readily applied to other countries with appropriate data collection.gasoline tax, diesel tax, externalities, optimal tax, welfare gains, Chile

Ecodriving and Carbon Footprinting: Understanding How Public Education Can Reduce Greenhouse Gas Emissions and Fuel Use

Ecodriving is a collection of changes to driving behavior and vehicle maintenance designed to impact fuel consumption and greenhouse gas (GHG) emissions in existing vehicles. Because of its promise to improve fuel economy within the existing fleet, ecodriving has gained increased attention in North America. One strategy to improve ecodriving is through public education with information on how to ecodrive. This report provides a review and study of ecodriving from several angles. The report offers a literature review of previous work and programs in ecodriving across the world. In addition, researchers completed interviews with experts in the field of public relations and public message campaigns to ascertain best practices for public campaigns. Further, the study also completed a set of focus groups evaluating consumer response to a series of websites that displayed ecodriving information. Finally, researchers conducted a set of surveys, including a controlled stated-response study conducted with approximately 100 University of California, Berkeley faculty, staff, and students, assessing the effectiveness of static ecodriving web-based information as well as an intercept clipboard survey in the San Francisco Bay Area. The stated-response study consisted of a comparison of the experimental and control groups. It found that exposure to ecodriving information influenced people’s driving behavior and some maintenance practices. The experimental group’s distributional shift was statistically significant, particularly for key practices including: lower highway cruising speed, driving behavior adjustment, and proper tire inflation. Within the experimental group (N = 51), fewer respondents significantly changed their maintenance practices (16%) than the majority that altered some driving practices (71%). This suggests intentionally altering driving behavior is easier than planning better maintenance practices. While it was evident that not everyone modifies their behavior as a result of reviewing the ecodriving website, even small shifts in behavior due to inexpensive information dissemination could be deemed cost effective in reducing fuel consumption and emissions