Exploring and Visualizing Spatial Effects and Patterns in Ride-Sourcing Trip Demand and Characteristics

The complex demand pattern of ride-sourcing remains to be a challenge to transportation modeling practitioners due to the infancy and the inherently dynamic nature of the ride-sourcing system. Spatial effects exploration and analysis protocols can provide informative insights on the underlying structure of demand and trip characteristics. Those protocols can be thought of as an opportunistic strategy to alleviate the complexity and help specifying the appropriate econometric models for the system. Spatial effects exploration is comparable to point pattern analysis, in which, signals from spatial entities, like census tracts, can be analyzed statistically to reveal whether a specific phenomenon respective signal distribution is a completely random process or if it follows some regular pattern. The results of such analysis help to explore the investigated phenomenon and conceptualize its causal forces. In this paper, we apply spatial pattern analysis edge methods integrated into a visual analytics framework to: (1) test the null hypothesis of system demand complete randomness; (2) further analyze and explain this demand in terms of the origin-destination (OD) flow and trips characteristics, i.e., length and duration; and (3) develop a pattern profile of the demand and trip characteristics to provide potential directions to modeling and predictive analytics approaches. This framework helps explain the ride-sourcing system demand and trip characteristics in space and time to fill the gap in integrating the system in multimodal transportation frameworks. We use the ride-sourcing trip dataset released from the City of Chicago, USA, for the year 2019 to showcase the proposed methods and their novelty in capturing such effects as well as explaining the underlying complexities in a streamlined workflow. The ride-sourcing demand hotspots were explored and identified in the city’s central business district. A novel method to capture and analyze the origin-destination flowlines was developed and implemented. Finally, a complementary trip characteristics pattern analysis was conducted to fully comprehend the system and validate the findings from the system demand points and OD-flowlines

Crash Risk Analysis of Distracted Driving Behavior: Influence of Secondary Task Engagement and Driver Characteristics

Distracted driving has long been acknowledged as one of the main contributors to crashes in the US. According to past studies, driving behavior proved to be influenced by the socioeconomic characteristics of drivers. However, only few studies attempted to quantify that influence. The study proposed a Crash Risk Index to estimate the crash risk associated with the socioeconomic characteristics of drivers and their tendency to experience distracted driving. The analysis is conducted using data from the SHRP 2 Naturalistic Driving Study (NDS). The proposed Crash Risk Index (CRI) is developed based on a grading system of three measures: the crash risk associated with performing secondary tasks during driving, the effect of socioeconomic attributes (e.g. Age) on the likelihood of engagement in secondary tasks, and the effect of specific categories within each socioeconomic attribute (e.g. Age\u3e60) on the likelihood of engagement in secondary tasks. Logistic Regression analysis was performed on the secondary tasks, socioeconomic attributes, and the specific socioeconomic characteristics. The results identified the significant secondary tasks with high crash risk and the socioeconomic characteristics with significant effect on determining drivers’ involvement in secondary tasks among each tested parameter. These results were used to quantify the grading system measures and hence estimate the proposed CRI. This index indicates the relative crash risk associated with the socioeconomic characteristics of drivers and considering the possibility of engagement in secondary tasks. The proposed CRI and the associated grading system are plausible methods for estimating auto insurance premiums

Development of Guidelines for Collecting Transit Ridership Data

Transit ridership is a critical determinant for many transit applications such as operation optimizations and project prioritization under performance-based funding mechanisms. As a result, the quality of ridership data is of utmost importance to both transit administrative agencies and transit operators. Many transit operators in Virginia report their ridership data to the Department of Rail and Public Transportation (DRPT) and the National Transit Database (NTD). However, with no specific guidelines available to transit agencies in Virginia for collecting ridership data, the heterogeneous mixture of diverse data collection methods and technologies has often raised concerns about the consistency and quality of the reported data. This study investigated the ridership data collection practices adopted by transit agencies in Virginia and developed high-level guidelines to facilitate data collection with improved quality. Specifically, it examined the data collection practices discussed in the literature and those adopted by local transit agencies in Virginia. The research team surveyed 39 transit agencies to obtain a clear understanding of their current practices in data collection scope, technological solutions, sampling and estimation techniques, and data storage and reporting, among others. To evaluate the potential estimation errors based on sampled data, the researchers requested and obtained actual data from five transit agencies of different sizes in Virginia. Comparisons between selected data collection solutions were conducted, and the estimation errors were tested based on different sample data from these agencies. Based on the findings from literature review, surveys, and analysis of actual data, a set of high-level data collection guidelines was proposed. This study recommends that DRPT distribute the developed guidelines among transit agencies in Virginia to help facilitate improved data collection practices across Virginia. It is also recommended that DRPT require the submission of each agency’s ridership data collection methods and correction (adjustment) procedures, in addition to the agency’s reported ridership data

Improving Safety Service Patrol Performance

Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: a) generate alternative feasible SSP beat configurations for a corridor; b)predict incidents and SSP characteristics (e.g., incident frequency, SSP service time) for a given SSP beat configuration; c) estimate performance measures (e.g., SSP response time, number of incidents responded to); and d) identify and present the best SSP configuration(s) through visual aids that facilitate decision making. To generate the incident data needed for the simulation-based SSP-OPT tool, a hierarchical negative binomial model and a hierarchical Weibull model are developed for incident frequencies and incident durations, respectively, based on the historical incident data. These models have been found to be effective in simulating the spatiotemporal distribution of incidents along highway corridors and for generating their attribute data (e.g., incident type, duration). The simulation program employs a discrete event-based approach and requires a few calibration parameters (e.g., SSP vehicle speed). After calibrating the model, the validation results show good agreement with field observations when applied to a sample SSP corridor from I-95. A user interface is created for the SSP-OPT tool in MS Excel to facilitate data entry and visualization of the output metrics for a given corridor. The output includes the list of alternative feasible beat configurations and aggregated performance measures from multiple runs for each individual beat, as well as for each alternative beat configuration spanning the entire corridor. The proposed SSP optimization model could be applied to corridors with or without existing SSP service. The tool will help identify the best beat configurations to minimize SSP response times and maximize SSP response rates for a given number of SSP vehicles on a corridor. Implementing these optimal solutions in the field will result in travel time savings and improve highway safety since the SSP resources will be more efficiently utilized, thus reducing the impacts of incidents on traffic flow

Analysis of jet wall flow and heat transfer conveying ZnO-SAE50 nano lubricants saturated in Darcy-Brinkman porous medium

The problem of 2D (two-dimensional) wall jet flow, along with heat transfer incorporated by nanofluid in a Darcy-Brinkman medium, while recognizing the requirement for efficient heating and cooling systems. Following the use of similarity variables, the resultant system of ODEs (ordinary differential equations) is solved using the well-known and efficient bvp4c (boundary-value problem of the 4th order) technique. The significance of physical quantities for the under-consideration parameters is illustrated and explained. The findings show that the nanoparticle volume fraction and porosity parameters decrease the velocity, but increase the temperature. In addition, the temperature uplifts in the presence of radiation effect. The suction parameter initially decreases and then increases the velocity near the surface, while the temperature declines

Impact of Smoluchowski temperature and Maxwell velocity slip conditions on axisymmetric rotated flow of hybrid nanofluid past a porous moving rotating disk

Colloidal suspensions of regular fluids and nanoparticles are known as nanofluids. They have a variety of applications in the medical field, including cell separation, drug targeting, destruc-tion of tumor tissue, and so on. On the other hand, the dispersion of multiple nanoparticles into a regular fluid is referred to as a hybrid nanofluid. It has a variety of innovative applications such as microfluidics, heat dissipation, dynamic sealing, damping, and so on. Because of these numerous applications of nanofluids in minds, therefore, the objective of the current exploration divulged the axisymmetric radiative flow and heat transfer induced by hybrid nanofluid impinging on a porous stretchable/shrinkable rotating disc. In addition, the impact of Smoluchowski temperature and Maxwell velocity slip boundary conditions are also invoked. The hybrid nanofluid was formed by mixing the copper (Cu) and alumina (Al2 O3 ) nanoparticles scattered in the regular (viscous) base fluid (H2 O). Similarity variables are used to procure the similarity equations, and the numerical outcomes are achieved using bvp4c in MATLAB software. According to the findings, double solutions are feasible for stretching (λ > 0) and shrinking cases (λ < 0). The heat transfer rate is accelerated as the hybrid nanoparticles increases. The suction parameter enhances the friction factors as well as heat transfer rate. Moreover, the friction factor in the radial direction and heat transfer enrich for the first solution and moderate for the second outcome due to the augmentation δ1, while the trend of the friction factor in the radial direction is changed only in the case of stretching for both branches

Radiative mixed convective flow induced by hybrid nanofluid over a porous vertical cylinder in a porous media with irregular heat sink/source

Purpose: Hybrid nanofluids have higher mechanical resistance, thermal conductivity, chemical stability, and physical strength when compared to normal nanofluids. Our approach in the current paper is to present a novel exploration comprising radiative mixed convection flow of hybrid nanofluids with irregular heat source/sink effect through a porous vertical cylinder immersed in a porous media. Both opposing and assisting flows are discussed. Methodology: The transmuted similarity ODEs are numerically worked out utilizing the assist of the bvp4c package in MATLAB for different values of physical parameters. The hybrid nanofluids contain a couple of nanoparticles namely aluminum and copper particles with water as base fluid. Findings: It was observed that fundamental similarity equations disclose double solutions (first and second branches) for buoyancy assisting and opposing flows. The drag force is enhanced due to the radiation as well as curvature parameters. In addition, the velocity declines due to heat source/sink and radiation parameter. Originality/value: The writers agree that all numerical outcomes are novel and have not previously been published for the current problem

Ramification of hall and mixed convective radiative flow towards a stagnation point into the motion of water conveying alumina nanoparticles past a flat vertical plate with a convective boundary condition: the case of non-newtonian williamson fluid

Heat transfer technologies are experiencing rapid expansion as a result of the demand for efficient heating and cooling systems in the automotive, chemical, and aerospace industries. Therefore, the current study peruses an inspection of mixed convective radiative Williamson flow close to a stagnation point aggravated by a single nanoparticle (alumina) from a vertical flat plate with the impact of Hall. The convective heating of water conveying alumina (Al2O3) nanoparticles, as appropriate in engineering or industry, is investigated. Using pertinent similarity variables, the dominating equations are non-dimensionalized, and after that, via the bvp4c solver, they are numerically solved. We extensively explore the effects of many relevant parameters on axial velocity, transverse velocity, temperature profile, heat transfer, and drag force. In the opposing flow, there are two solutions seen; in the aiding flow, just one solution is found. In addition, the results designate that, due to nanofluid, the thickness of the velocity boundary layer decreases, and the thermal boundary layer width upsurges. The gradients for the branch of stable outcome escalate due to a higher Weissenberg parameter, while they decline for the branch of lower outcomes. Moreover, a magnetic field can be used to influence the flow and the properties of heat transfer

Thoughts on the future of artificial intelligence and transportation

In this concluding chapter of the Circular, we have asked members of our committee to share with the readers their personal thoughts on the future of AI and transportation. We are pleased herein to present select quotes from the committee members, organized alphabetically, on that topic