Highway Cross Slope Measurement Using Airborne and Mobile LiDAR

Ensuring adequate pavement cross slope on highways can improve driver safety by reducing the potential for water sheeting and ponding. Collecting cross slope data is typically only based on small sample because efficient technology and means to collect accurate cross slope data has been evasive. The advent of Light Detection and Ranging (LiDAR) scanning technology has proven to be a valuable tool in the creation of 3D terrain models. Combined with other technologies such as Global Positioning Systems (GPS) and Inertial Measurement Unit devices (IMU) it is now possible to collect accurate 3D coordinate data in the form of a point cloud while the data collection system is moving. This study provides an evaluation of both Airborne LiDAR Scanning (ALS) and Mobile Terrestrial LiDAR Scanning (MTLS) systems regarding the accuracy and precision of collected cross slope data and documentation of procedures needed to calibrate, collect, and process this data. ALS data was collected by a single vendor on a section of freeway in Spartanburg, South Carolina and MTLS data was collected by six vendors on four roadway sections in South Carolina. The MTLS cross slopes were measured on 23 test stations using conventional surveying methods and compared with the LiDAR-extracted cross slopes. Results indicate that both adjusted and unadjusted MTLS derived cross slopes meets suggested cross slope accuracies (±0.2%). Unadjusted LiDAR data did incorporate corrections from an integrated inertial measurement unit, and high accuracy real-time kinematic GPS, however, was not post-processed adjusted with ground control points. Similarly, airborne LiDAR-extracted cross slopes was compared with conventional surveying measurement on five test stations along the freeway study section. Whereas, the ALS data accuracy was over the minimum acceptable error when two sides of the travel lanes were used to estimate the cross slope, the use of a fitted line to derive the cross slope provided accuracies similar to the MTLS systems. The levels of accuracy demonstrate that MTLS and ALS can be reliable methods for cross slope verification. Adoption of LiDAR would enable South Carolina Department of Transportation (SCDOT) or other highway agencies to proactively address cross slope and drainage issues. When rain falls on a pavement surface, the water depth that accumulates can result in hydroplaning. Previous research has not clearly defined a water depth at which hydroplaning occurs; however, there is considerable agreement that a water depth equal to 0.06 inches as the acceptable upper limit of water depth to minimize the possibility of hydroplaning. This research also explored the potential for hydroplaning with regard to the range of vehicle speed, tire tread depth, tire pressure, and pavement surface texture. Using the results of the sensitivity analysis to provide roadway context combined with MTLS derived cross slope data, SCDOT and other highway agencies can use a data driven approach to evaluate cross slopes and road segments that need corrective measures to minimize hydroplaning potential and enhance safety

The Future of Carsharing: A System Dynamics Model

L'abstract è presente nell'allegato / the abstract is in the attachmen

Exploring Carsharing Diffusion Challenges through Systems Thinking and Causal Loop Diagrams

The diffusion of carsharing in cities can potentially support the transition towards a sustainable mobility system and help build a circular economy. Since urban transportation is a complex system due to the involvement of various stakeholders, including travelers, suppliers, manufacturers, and the government, a holistic approach based on systems thinking is essential to capture this complexity and its causalities. In this regard, the current research aims at identifying cause-and-effect relationships in the diffusion of carsharing services within the urban transport systems. To do so, a causal loop diagram (CLD) is developed to identify and capture the causalities of carsharing adoption. On this basis, the main four players within the carsharing domain in urban transportation were scrutinized and their causes and effects were visualized, including (i) the characteristics, behavior, and dynamics of the society population; (ii) transportation system and urban planning; (iii) the car manufacturing industry; and (iv) environmental pollution. The developed CLD can support decision-makers in the field of urban transport to gain a holistic and systemic approach to analyzing the issues within the transport sector due to their complexity. Moreover, they can help regulators and policymakers in intensifying the diffusion of more sustainable modes of transport by highlighting the role of population, car manufacturing, the transportation system, and environmental pollution

Identifying and classifying the factors affecting risk in automobile hull insurance in Iran using fuzzy Delphi method and factor analysis

Automobile hull insurance has attracted much attention due to the high rate of vehicle applications in daily lives. Since purchasing these policies is optional in Iran and their premium rates are set competitively, a competition is formed among the insurance companies for attracting low risk drivers. However, most of the insurers still use comparative rates and pay no or less attention to the factors affecting risk in premium calculations. Considering the importance of fair ratemaking in attracting and maintaining good risks and encouraging bad risks to repent or leave the portfolio, and taking into account the shortcomings of the available databases, this paper focuses on determining and classifying the risk factors affecting premium calculation in automobile hull insurance from the viewpoint of the experts. In this regard, Fuzzy Delphi method is utilized, the factors are classified and the efficiency of the classification is checked by using Confirmatory Factor Analysis (CFA)

Safety effectiveness of adding by-pass lanes at unsignalized rural intersections in Kansas

Master of ScienceDepartment of Civil EngineeringSunanda DissanayakeConstruction of by-pass lanes at rural intersections typically has been considered a low-cost safety improvement. Safety analysis utilizes two common approaches to evaluate treatment effectiveness: before-and-after study and cross-sectional study. This research performed paired sample t-test statistical analysis to estimate changes in total of crash frequency, crash rates, EPDO crash frequency, and EPDO crash rates at intersections, three to five years after adding a by-pass lane compared to identical time period before the by-pass lane was added. Crash data between 1990 and 2011 were obtained from Kansas Crash and Analysis Record System (KCARS) maintained by the Kansas Department of Transportation (KDOT). In order to perform a cross-sectional study, intersections with by-pass lanes were compared to intersections with no countermeasures; crash data were obtained for more than 1,100 intersections in the state of Kansas. According to before-and-after study, addition of by-pass lanes improves safety at unsignalized rural intersections; crashes and their severities are reduced after adding by-pass lanes. But, these reductions are not statistically significant under 95% confidence level. However, when considering intersection related crashes, a statistically significant reduction in crash rates is happened after adding by-pass lanes at 3-legged intersections. In cross-sectional study, crashes and their severities are lower at 3-legged intersections with the by-pass lanes versus 3-legged intersections without the by-pass lanes. However, these reductions are not statistically significant under 95% confidence level. When considering 300 feet intersection crash box, statistically significant reductions are happened at 4-legged intersection. In contrast, crashes and their severities increased at 4-legged intersections with the by-pass lanes, but these changes are not statistically significant under 95% confidence level. The Crash Modification Factors were calculated to evaluate safety effectiveness of adding by-pass lanes at unsignalized rural intersections. The calculated CMFs less than 1.0, indicate a reduction in crashes after implementation of by-pass lanes. Finally, this study concluded that expected crashes at intersections with by-pass lanes are lower than intersections without by-pass lanes

The Pandemic Implications for Carsharing: An Italian Context

Carsharing, as an innovative mobility option, can potentially support the urban transition towards a more sustainable mobility system and achieving sustainable development goals. This short communication aims at providing the status of carsharing services in Italy, with a focus on Turin, before and after the COVID-19 pandemic. In this regard, an overview of the role of carsharing in urban traffic is provided. Then, carsharing services in Italy before and after the pandemic are mapped. Accordingly, the implications of the pandemic outbreak for carsharing services are discussed. The provided insights confirm that although carsharing services have been affected by the pandemic, even after returning to normal life, the usage of carsharing is still far below its pre-pandemic level in Italy. Finally, to support sustainable mobility and incentivize using shared mobility services, a research agenda for further research is proposed, targeting the research gaps regarding (i) the factors leading to lower usage of carsharing after the pandemic, (ii) potential solutions and policies to support carsharing services return to their pre-pandemic level and exceeding it, and (iii) examining the impact of provided supports by governments during the pandemic, such as bonuses for purchasing bikes and scooters, on the adoption of carsharing services for the post-pandemic era

A big data approach to map the service quality of short-stay accommodation sharing

Purpose: The purpose of this paper is to map the service quality (SQ) of Airbnb, to provide additional insight for such top player of short-stay accommodation in the sharing economy context. Design/methodology/approach: A mixed-method approach is used in two phases. In the qualitative phase, 112,138 online review comments of Airbnb guests were analyzed to generate the service attributes. In the quantitative phase, an online survey (n = 814) was conducted to calculate the performance and importance values of extracted attributes to plot them in an Importance-Performance Analysis (IPA) matrix. Findings: A holistic image of the Airbnb extracted service attributes was presented through the IPA plot. Four types of SQ strategies were proposed, considering the actions priority. “Price reasonability” was the most important service attribute of Airbnb for guests, whereas “Check-in flexibility” was the best performed one. Practical implications: The results shed light on the most relevant SQ attributes of Airbnb and proposed suitable strategies that can prioritize relevant stakeholders’ actions and decisions. The study significantly contributes to all decision makers involved in the short-stay accommodation sharing industry to further understand and develop SQ. Originality/value: This research, using a comprehensive hybrid method, opens a lens to see more clearly the positioning of different attributes of Airbnb service from importance and performance viewpoints. As a contribution, the SQ of Airbnb was mapped by conducting an IPA for the first time in the literature

The imbalance of food and biofuel markets amid Ukraine-Russia crisis: A systems thinking perspective

The Ukraine war has immensely affected both food and energy systems due to the significant role of Russia in supplying natural gas and fertilizers globally and the extensive contribution of both Russia and Ukraine in exporting grains and oilseeds to the international markets. Hence, the Ukraine-Russia conflict has resulted in a shortage of crops and grains in the food market, especially in Europe, causing speculations if these resources should still be used for biofuel production (1st Generation). However, the International Energy Agency has warned that lowering biofuel mandates could result in rising petroleum demand and supply concerns. In light of these unfolding events, a systems thinking approach is required to monitor and analyze the implications of this crisis for food and biofuel markets as a whole to alleviate the concerns faced and plan sustainably. In this vein, based on the trade-offs between food system elements and the biofuel supply chain, as well as the potential effects of the war on the food and energy systems worldwide, a causal loop diagram is developed in the present work. According to the insights provided, the key to preventing food insecurity and keeping biofuel mandates on an increasing trend simultaneously amid the Ukraine war is to switch from the 1st Generation biofuels to higher generations. This transition would reduce not only the pressure on the food market to move toward zero hunger (SDG 2) but also pave the way to move towards a circular economy and clean and affordable energy (SDG 7) during the post-war er

Conceptualizing environmental effects of carsharing services: A system thinking approach

Emerging carsharing services and their interconnections with other modes of urban transport, regulations, car manufacturing and population have affected the dynamics of energy consumption, environmental pollution and greenhouse gas emission within a complex system. However, although some aspects of environmental impacts of transport sector have been investigated in the literature, well-deserved studies on the environmental effects of carsharing services following a system thinking approach is missing. This research aims at providing a comprehensive conceptual framework to systematize the interconnections between carsharing services and their environmental effects. To do this, system dynamics (SD) modeling, as a tool to simulate complex and dynamic systems, is applied and the proposed framework model is illustrated by using a causal-loop diagram (CLD). Along with analyzing the main identified causal loops within the presented CLD, relevant strategies are proposed to reduce the negative environmental effects associated with the carsharing services, considering the whole lifecycle of a shared vehicle. The proposed framework can help environment policy makers and shared mobility practitioners in long-term strategic decision-making. Moreover, it can be applied by the researchers as a basis for future research, not only for SD modeling but also other simulation and analysis structures

Digitally enabled food sharing platforms towards effective waste management in a circular economy:A system dynamics simulation model

As a solution to tackle the food waste (FW) challenge, digitally enabled food sharing platforms (FSPs) are emerging as FW warriors and anti-waste social movements. Despite the rapidly growing number of users, the amount of FW prevented per user in these platforms is relatively low. Hence, the real contribution of FSPs to the circular economy (CE) by preventing FW is still blurred. To fill this gap, a System Dynamics simulation model is developed in this research to unfold how people adopt such platforms over time, and how such platforms contribute to the CE through FW prevention. The model is used to simulate the adoption and performance of Italy’s Too Good To Go (TGTG) platform spanning 2015-2060 as a reference case. The results show that although TGTG is a successful FSP in terms of adoption, it can still significantly improve in terms of performance. Besides, while the current TGTG’s marketing strategy is effective, knowledge-enhancing activities should be strengthened to improve performance. Hence, this research recommends a winning policy, which can reduce approximately 3% of the total FW generated at the country level (Italy) in 2060, a significant contribution to the CE transition