A REVIEW OF SECURITY, PRIVACY AND INFORMATION LEAKAGE IN IOT BASED SMART CARPOOL SYSTEM

Internet of Things (IoT) age has now started and it'll very much change our way of life. The most important purpose for IoT is formation of smart environments using self-aware things like smart transport, smart city, etc. for novel and innovative applications. Internet of things allows us to control objects that we use distantly through the internet. Negative effects of IoT technology are defenseless against to attack. So, there is increase in possibility of privacy information leakage which is causing economical damage to individuals thus also causing social and political damage. To address this problem, many risk measurement methods for information Leakage in IoT have been proposed in the past years.This overview paper highlights possible application of the concept of IoT within smart city traffic surroundings that supported instance of carpooling system with utilization of a personal vehicle. It also discusses IoT security and privacy threats which cause information leakage. This paper presented and analyzed the IoT Security, Safety, and Privacy risks that provide a complete view of current issues due to the implementation of this technology

Offsetting the Impact of CO2 Emissions Resulting from the Transport of Maiêutica’s Academic Campus Community

info:eu-repo/semantics/publishedVersio

Tradable driving rights in urban areas: their potential for tackling congestion and traffic-related pollution

Congestion pricing as a transport demand management measure is difficult to implement because most of motorists expect a deterioration of their welfare. Tradable driving rights (TDR), that is allocating quotas of driving rights for free to urban inhabitants, could be a more acceptable alternative. This mechanism provides also a supplementary incentive to save whether trips or distance travelled by car, because of the possibility of selling unused rights. A complete system of TDR is designed in detail, aiming whether at reducing trips or vehicles-kilometres, in order to control congestion, or the same target modulated on the basis of the pollutant emission categories of vehicles in order to control atmospheric pollution. An assessment is carried out on the Lyon urban area, which points at some welfare distributive issues between motorists and the community, when compared with conventional congestion pricing.transport demand management (TMD) ; tradable driving rights (TDR) ; automobile traffic ; congestion pricing ; air pollution ; urban areas ; Lyon (France)

A Tabu Search Based Metaheuristic for Dynamic Carpooling Optimization

International audienceThe carpooling problem consists in matching a set of riders' requests with a set of drivers' offers by synchronizing their origins, destinations and time windows. The paper presents the so-called Dynamic Carpooling Optimization System (DyCOS), a system which supports the automatic and optimal ridematching process between users on very short notice or even en-route. Nowadays, there are numerous research contributions that revolve around the carpooling problem, notably in the dynamic context. However, the problem's high complexity and the real time aspect are still challenges to overcome when addressing dynamic carpooling. To counter these issues, DyCOS takes decisions using a novel Tabu Search based metaheuristic. The proposed algorithm employs an explicit memory system and several original searching strategies developed to make optimal decisions automatically. To increase users' satisfaction, the proposed metaheuristic approach manages the transfer process and includes the possibility to drop off the passenger at a given walking distance from his destination or at a transfer node. In addition, the detour concept is used as an original aspiration process, to avoid the entrapment by local solutions and improve the generated solution. For a rigorous assessment of generated solutions , while considering the importance and interaction among the optimization criteria, the algorithm adopts the Choquet integral operator as an aggregation approach. To measure the effectiveness of the proposed method, we develop a simulation environment based on actual carpooling demand data from the metropolitan area of Lille in the north of France

Shifting of air pollutants distribution during car free day event

According to Decree of Semarang Mayor No. 22/2011, car free day activities si addressed to give clean air for facilitating citizens activities. This car free day event is helm every Sunday in the morning in the city center of Semarang i.e. located at Simpang Lima square. This research is aimed at identifying the shifting of pollutant during car fee day eventby comparing ambient air pollutant concentration represented by carbon monoxide during carfree day event and non-car free day event. About 14 streets had been measured its ambient CO concentration during Saturday (non-car free day event) and Sunday (car free day event). We also modeled (using Caline4) the CO dispersion at the certain area on those streets to know The spatial distribution of concentration during those two events. The ambient CO concentration, in general, during car free day event were somewhat increase for certain roads. The emission load of vehicles emission during CFD event was 1.37 times of non-CFD event. Nevertheless, based on spatial distribution of ambient CO concentration at the area of roads of interest, its concentrations were below the ambient CO concentration standard (PP.41/99)

TOOLS TO SUPPORT TRANSPORTATION EMISSIONS REDUCTION EFFORTS: A MULTIFACETED APPROACH

The transportation sector is a significant contributor to current global climatic problems, one of the most prominent problems that today's society faces. In this dissertation, three complementary problems are addressed to support emissions reduction efforts by providing tools to help reduce demand for fossil fuels. The first problem addresses alternative fuel vehicle (AFV) fleet operations considering limited infrastructure availability and vehicle characteristics that contribute to emission reduction efforts by: supporting alternative fuel use and reducing carbon-intensive freight activity. A Green Vehicle Routing Problem (G-VRP) is formulated and techniques are proposed for its solution. These techniques will aid organizations with AFV fleets in overcoming difficulties that exist as a result of limited refueling infrastructure and will allow companies considering conversion to a fleet of AFVs to understand the potential impact of their decision on daily operations and costs. The second problem is aimed at supporting SOV commute trip reduction efforts through alternative transportation options. This problem contributes to emission reduction efforts by supporting reduction of carbon-intensive travel activity. Following a descriptive analysis of commuter survey data obtained from the University of Maryland, College Park campus, ordered-response models were developed to investigate the market for vanpooling. The model results show that demand for vanpooling in the role of passenger and driver have differences and the factors affecting these demands are not necessarily the same. Factors considered include: status, willingness-to-pay, distance, residential location, commuting habits, demographics and service characteristics. The third problem focuses on providing essential input data, origin-destination (OD) demand, for analysis of various strategies, to address emission reduction by helping to improve system efficiency and reducing carbon-intensive travel activity. A two-stage subarea OD demand estimation procedure is proposed to construct and update important time-dependent OD demand input for subarea analysis in an effort to overcome the computational limits of Dynamic Traffic Assignment (DTA) methodologies. The proposed method in conjunction with path-based simulation-assignment systems can provide an evolving platform for integrating operational considerations in planning models for effective decision support for agencies that are considering strategies for transportation emissions reduction

On the Feasibility of Social Network-based Pollution Sensing in ITSs

Intense vehicular traffic is recognized as a global societal problem, with a multifaceted influence on the quality of life of a person. Intelligent Transportation Systems (ITS) can play an important role in combating such problem, decreasing pollution levels and, consequently, their negative effects. One of the goals of ITSs, in fact, is that of controlling traffic flows, measuring traffic states, providing vehicles with routes that globally pursue low pollution conditions. How such systems measure and enforce given traffic states has been at the center of multiple research efforts in the past few years. Although many different solutions have been proposed, very limited effort has been devoted to exploring the potential of social network analysis in such context. Social networks, in general, provide direct feedback from people and, as such, potentially very valuable information. A post that tells, for example, how a person feels about pollution at a given time in a given location, could be put to good use by an environment aware ITS aiming at minimizing contaminant emissions in residential areas. This work verifies the feasibility of using pollution related social network feeds into ITS operations. In particular, it concentrates on understanding how reliable such information is, producing an analysis that confronts over 1,500,000 posts and pollution data obtained from on-the- field sensors over a one-year span.Comment: 10 pages, 15 figures, Transaction Forma

Congestion-Clearing Payments to Passengers

Peak period motor vehicle traffic volume congests roads all over the world. This project hypothesizes implementing congestion- clearing payments to passengers as a permanent congestion-management solution. Ongoing congestion-free travel would be achieved by removing existing congestion, and absorbing (re)generated demand, at costs that would be expected to increase as the total number of travelers increases over time. The project develops a comprehensive, step-by-step methodology to calculate the benefits and costs of paying for drivers to become passengers at a congestion-clearing level and to maintain this level over time. The method is derived from the literature, analysis by the project team, and development of a case study. The case study, based on a long-standing bottleneck location in California, enabled the project team to think through the real challenges of developing and evaluating such a solution. The project finds that the conceptual underpinning of the solution is sound. Based on a survey, the case study finds that there is a level of payment that could clear congestion and maintain free-flow for twenty years, with benefits that outweigh costs on a net present value basis by about four to one—though calibration is required. After the initial reward clears the queue at the bottleneck, a significant intra-peak demand shift would occur as existing and new travelers depart home at times that are more to their liking, potentially causing the queue to re-form. A second incentive manages time of travel, rewarding people for traveling as passengers earlier (or later) than the preferred high demand peak-of-the-peak. In the case study, the high proportion of people who say they will only drive alone would eventually result in some periods of single-occupant-vehicle-only traffic during peak, which is an unintended and undesirable consequence. For the case study route, a limit on single-occupant-vehicle travel during the peak- of-the-peak would ensure that high-occupancy-vehicle travel is given preference and would reduce the overall cost of the solution. For the case study, the cost of the congestion-clearing payments-to-passengers solution on a net present value basis is within the estimated range of costs of the alternative of expanding the facility, and the benefits are expected to be greater than for facility expansion. Congestion-clearing payments to passengers can be implemented much sooner and will have greater positive long-term economic impacts. Facility expansion would provide lower and shorter-term benefits and would be expected to return to congested conditions within a year. The project team proposes a pilot project on the case study route to test and calibrate the solution, as well as recommending development of further case study routes to find out how different routes vary and determine the causes of any variations

Citywide Transportation Greenhouse Gas Emissions Inventories: A Review of Selected Methodologies

Outlines the methodological issues in creating transportation emissions inventories and how they affect the results, reviews currently used methodologies, and explores ways to integrate inventories with climate policies to inform reduction strategies

Greening Your Non-Profit from the Inside Out: A NeighborWorks Guide for Community Development Organizations

Read this guide to learn how community development organizations can"go green" through NeighborWorks Green Course curriculum. The guide includes information on education and skills training in healthy homes and green construction,and launching a Green Certificate program to train practitioners in successful strategies for green building and sustainable design