Public Affairs, Public Policy and Public Administration Commons^™

Incorporating The 10th Edition Institute Of Traffic Engineers (Ite) Trip Generation Rates Into Virginia Department Of Transportation Guidelines, Kun Xie, Mecit Cetin, Hong Yang, Xiaomeng Dong

Civil & Environmental Engineering Faculty Publications

The Institute of Transportation Engineers (ITE) released the Trip Generation (TG) 10th edition in 2017, which significantly updated its database, and some of its trip generation rates were substantially lower than those of earlier editions. This study aims to investigate the applicability of the TG 10th edition in various Virginia contexts and to recommend how to incorporate the TG 10th edition into state guidelines. The research team surveyed 31 state transportation agencies to obtain a clear understanding of current practices in the adoption of trip rates and trip estimation approaches. We systematically compared trip rates of TG 9th and 10th …

Assessing The Impact Of Health Benefits And Carbon Footprint In Student Parking Decisions At A University Campus, Emiliano Ruiz

Open Access Theses & Dissertations

In the student parking location problem, traditionally, the parking permit cost, the last-mile travel time, and the ease of finding an available parking stall are the only decision criteria driving permit purchases. However, a studentâ??s choice of parking location has associated walking health benefits and sustainability impacts. These impacts are related to the walking distance from the parked vehicle to the final destination on campus, in addition to the location effect on the carbon footprint of a vehicle-trip taken to campus. As such, this Thesis examined a multi-criteria decision approach to a university studentâ??s choice of parking location. This approach …

An Improved Learnable Evolution Model For Solving Multi-Objective Vehicle Routing Problem With Stochastic Demand, Yunyun Niu, Detian Kong, Rong Wen, Zhiguang Cao, Jianhua Xiao

Research Collection School Of Computing and Information Systems

The multi-objective vehicle routing problem with stochastic demand (MO-VRPSD) is much harder to tackle than other traditional vehicle routing problems (VRPs), due to the uncertainty in customer demands and potentially conflicted objectives. In this paper, we present an improved multi-objective learnable evolution model (IMOLEM) to solve MO-VRPSD with three objectives of travel distance, driver remuneration and number of vehicles. In our method, a machine learning algorithm, i.e., decision tree, is exploited to help find and guide the desirable direction of evolution process. To cope with the key issue of "route failure" caused due to stochastic customer demands, we propose a …

Exploration Of Corridor-Based Tolling Strategies For Virginia’S Express Toll Lanes, Shanjiang Zhu, Mecit Cetin, Hong Yang, Olcay Sahin, Atabak Mardan

Civil & Environmental Engineering Faculty Publications

Virginia has invested significant resources in the development of express toll lanes (ETLs), which adjust toll rates dynamically based on the level of toll lane usage. A tool is needed to investigate the potential impact of the I-66 Outside-the-Beltway (OTB) ETLs on regional traffic patterns. This study developed a microscopic traffic simulation model in TransModeler to evaluate a set of corridor-based tolling strategies for the I-66 ETLs in NOVA. This model also considered the changes in vehicle occupancy, mode split, and departure time among travelers because of tolls based on locally collected data. An interactive map-based analyzer based on the …

Data Files: Green Waves, Machine Learning, And Predictive Analytics: Making Streets Better For People On Bikes, Stephen Fickas

TREC Datasets and Databases

The project builds on a prior app that was designed for Green Light Optimized Speed Advisory (GLOSA). This is more colloquially known as keeping a vehicle in the green wave: you are at a location and moving at a speed that will allow you to (theoretically) have a green light at each intersection you encounter along a corridor. Our long-term goal is to extend the FastTrack app described in the Background section to include actuated signals along a corridor. This project takes a first step by evaluating the effectiveness of machine-learning algorithms to predict the next phase of an actuated …

Data-Driven Mobility Strategies For Multimodal Transportation, Yao-Jan Wu, Xianfeng Terry Yang, Sirisha Kothuri, Abolfazl Karimpour, Qinzheng Wang, Jason Anderson

TREC Final Reports

Multimodal transportation systems (e.g., walking, cycling, automobile, public transit, etc.) are effective in increasing people’s travel flexibility, reducing congestion, and improving safety. Therefore, it is critical to understand what factors would affect people’s mode choices. With advanced technology, such as connected and automated vehicles, cities are now facing a transition from traditional urban planning to developing smart cities. To support multimodal transportation management, this study will serve as a bridge to connect speed management strategies of conventional corridors to connected vehicle corridors. This study consists of three main components. In the first component, the impact of speed management strategies along …

Using Deep Learning Algorithms To Give Bicyclists The “Green Wave” At Traffic Signals, Stephen Fickas

TREC Project Briefs

Led by Dr. Stephen Fickas of the University of Oregon (UO), transportation researchers are working to give bicyclists smoother rides by allowing them to communicate with traffic signals via a mobile app.

Gaps And Opportunities In Accessibility Policy For Autonomous Vehicles, William Riggs, Anurag Pande

Mineta Transportation Institute

Nearly 1 in 5 people in the US have a disability (more than 57 million) (U.S. Census Bureau), and people with disabilities use the automobile as a travel mode at significantly lower rates than people without disabilities (Bureau of Transportation Statistics). For example, people aged 18 to 64 with disabilities make 28% fewer trips per day (2.6 v. 3.6 trips) on average than people without disabilities. The disparity is even more significant for non-workers. These statistics highlight the notable technological, design, and policy failings in today’s transportation system - that disabled individuals have considerable suppressed demand for travel that is …

Spatio-Temporal Analysis Of The Roadside Transportation Related Air Quality (Startraq) And Neighborhood Characterization, Jaymin Kwon, Yushin Ahn, Steve Chung

Mineta Transportation Institute

To promote active transportation modes (such as bike ride and walking), and to create safer communities for easier access to transit, it is essential to provide consolidated data-driven transportation information to the public. The relevant and timely information from data facilitates the improvement of decision-making processes for the establishment of public policy and urban planning for sustainable growth, and for promoting public health in the region. For the characterization of the spatial variation of transportation-emitted air pollution in the Fresno/Clovis neighborhood in California, various species of particulate matters emitted from traffic sources were measured using real-time monitors and GPS loggers …

How Do Environmental Factors Affect Drivers’ Gaze And Head Movements?, Arash Tavakoli, Vahid Balali, Arsalan Heydarian

Mineta Transportation Institute

Studies have shown that environmental factors affect driving behaviors. For instance, weather conditions and the presence of a passenger have been shown to significantly affect the speed of the driver. As one of the important measures of driving behavior is the gaze and head movements of the driver, such metrics can be potentially used towards understanding the effects of environmental factors on the driver’s behavior in real-time. In this study, using a naturalistic study platform, videos have been collected from six participants for more than four weeks of a fully naturalistic driving scenario. The videos of both the participants’ faces …

Dynamic Lane Traffic Signal Control With Group Attention And Multi-Timescale Reinforcement Learning, Qize Jiang, Jingze Li, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

Traffic signal control has achieved significant success with the development of reinforcement learning. However, existing works mainly focus on intersections with normal lanes with fixed outgoing directions. It is noticed that some intersections actually implement dynamic lanes, in addition to normal lanes, to adjust the outgoing directions dynamically. Existing methods fail to coordinate the control of traffic signal and that of dynamic lanes effectively. In addition, they lack proper structures and learning algorithms to make full use of traffic flow prediction, which is essential to set the proper directions for dynamic lanes. Motivated by the ineffectiveness of existing approaches when …

Integrating Empirical Analysis Into Analytical Framework: An Integrated Model Structure For On-Demand Transportation, Yuliu Su, Ying Xu, Costas Courcoubetis, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

On-demand transportation services have been developing in an irresistible trend since their first launch in public. These services not only transform the urban mobility landscape, but also profoundly change individuals’ travel behavior. In this paper, we propose an integrated model structure which integrates empirical analysis into a discrete choice based analytical framework to investigate a heterogeneous population’s choices on ownership, usage and transportation mode with the presence of ride-hailing. Distinguished from traditional discrete choice models where individuals’ choices are only affected by exogenous variables and are independent of other individuals’ choices, our model extends to capture the endogeneity of supply …

A Deep Ensemble Method For Multi-Agent Reinforcement Learning: A Case Study On Air Traffic Control, Supriyo Ghosh, Sean Laguna, Laura Wynter, Laura Wynter, Hasan Poonawala

Research Collection School Of Computing and Information Systems

Reinforcement learning (RL), a promising framework for data-driven decision making in an uncertain environment, has successfully been applied in many real-world operation and control problems. However, the application of RL in a large-scale decentralized multi-agent environment remains a challenging problem due to the partial observability and limited communications between agents. In this paper, we develop a model-based kernel RL approach and a model-free deep RL approach for learning a decentralized, shared policy among homogeneous agents. By leveraging the strengths of both these methods, we further propose a novel deep ensemble multi-agent reinforcement learning (MARL) method that efficiently learns to arbitrate …

User Acceptance Of Autonomous Public Transport Systems (Apts): Extended Utaut2 Model, Huseyin Korkmaz, Akif Fidanoglu, Salih Ozcelik, Abdullah Okumus

Journal of Public Transportation

The purpose of this study is to investigate the factors affecting the acceptance and use of the APTS by its potential users. To achieve this, an integrated and expanded user acceptance model is introduced to explain the factors affecting the Behavioral Intention to use the APTS. A total of 316 surveys were conducted, from 275 participants by online surveys and 41 participants by face to face interviews. With the data that are acquired from Public Transportation (PT) users in Istanbul, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model is modified and Performance Expectancy, Effort Expectancy, Social …

Webinar: The Impact Of Ride Hail Services On The Accessibility Of Nonprofit Services, Dyana Mason

TREC Webinar Series

Nonprofit organizations are responsible for providing human services across the United States, often in partnership with government agencies. In this work, they address some of the most pressing social issues – including homelessness, poverty, health care and education. While many of these organizations consider location and accessibility crucial to supporting their clients – often locating services near bus or train stops, for example – little is known about the impact of new technologies, including ride hail services (also called Transportation Network Companies, or TNCs) like Lyft and Uber, on nonprofit accessibility. Do these services help fill gaps in client needs? …

Data-Driven Methods To Address Truck Parking Shortages For Long-Haul Commercial Truck Drivers, Sharif Mahmud

Graduate Theses and Dissertations

Truck parking is a critical concern for both the trucking industry and the truck drivers. Long-haul commercial truck drivers rely on safe and adequate parking to support interstate commerce, which has become a challenge due to parking shortages. The recent electronic logging device (ELD) mandate, forcing a strict compliance to hours of service (HOS) regulations, are leading to higher demand for parking. A number of federal, regional, and local studies reveal that truck activity will increase and truck parking demand will outpace parking supply in the coming years. Such parking shortages likely disrupt freight flows and pose risks to truck …

Developing An Effective Targeted Mobile Application To Enhance Transportation Safety And Use Of Active Transportation Modes In Fresno County: The Role Of Application Design & Content, Samer Sarofim

Mineta Transportation Institute

Do pedestrians and cyclists need their own app? Pedestrians and cyclists in Fresno county think so, and this research examined this need and how it relates to the importance of app design. Survey participants (all who regularly use active transportation modes) along with a variety of transportation stakeholders, including the Fresno Council of Government, the California Department of Transportation (Caltrans) District 6, and the City of Fresno — Public Works Department, indicated the importance of designing effective communication tools to enhance the utilization of active transportation modes and to ensure the safety of vulnerable road users. In this study, over …

Unintended Consequences Of Public Policy And Government Regulation On Supply Chain Structure, Conduct, And Performance, Jonathan Phares

Graduate Theses and Dissertations

Supply chains, and the firms within them, change their behaviors in response to industry conditions so they can provide efficiency, effectiveness, strategic enablement, and customer utility. Social and economic policies enacted to promote social welfare by correcting market failures can alter these conditions. While these policies may serve their intended purposes, they may also create unintended consequences that may make managing logistics, operations, and supply chains more challenging. This dissertation contributes to the nascent body of knowledge concerning the intended and unintended consequences of policy on supply chain management by examining three unique contextual settings using different methodologies and levels …

Steps To Supplement Park-And-Ride Public Transit Access With Ride-And-Ride Shuttles, John S. Niles, J. M. Pogodzinski

Mineta Transportation Institute

Public transit ridership in California declined in the five years before the pandemic of 2020–21 and dropped significantly further after the pandemic began. A sharp downward step in the level of transit boarding occurred after February 2020, and continues to the date of this report as a result of the public-health guidance on social distancing, expanded work-at-home, and a travel mode shift from public transit to private cars. A critical issue has come to the foreground of public transportation policy, namely, how to increase the quality and geographic reach of transit service to better serve the essential trips of mobility …

A Model For Integrating Rail Services With Other Transportation Modalities: Identifying The Best Practices And The Gaps For California’S Next State Rail Plan, Eric Peterson, Wenbin Wei, Lydon George

Mineta Transportation Institute

The California State Rail Plan (CSRP) is among the best rail plan documents published by any jurisdiction in the United States to date. As such, the CSRP is used in this paper as the basis of comparison to other state rail service plans. These plans will have been submitted to the Federal Railroad Administration (FRA) on record as of June 2020—as required under Section 303 of the Passenger Rail Investment and Improvement Act (PRIIA) of 2008. The purpose of this paper is to identify the best practices and gaps that may inform California and other states in their future rail …

Researching Relationships Between Truck Travel Time Performance Measures And On-Network And Off-Network Characteristics, Sarvani Duvvuri, Srinivas S. Pulugurtha

Mineta Transportation Institute

Trucks serve significant amount of freight tonnage and are more susceptible to complex interactions with other vehicles in a traffic stream. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel result in loss of revenue to the trucking companies. There is a significant research on the traffic congestion mitigation, but a very few studies focused on data exclusive to trucks. This research is aimed at a regional-level analysis of truck travel time data to identify roads for improving mobility and reducing congestion for truck traffic. The objectives of the research are to compute and evaluate …

Step-Wise Deep Learning Models For Solving Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

Routing problems are very important in intelligent transportation systems. Recently, a number of deep learning-based methods are proposed to automatically learn construction heuristics for solving routing problems. However, these methods do not completely follow Bellman's Principle of Optimality since the visited nodes during construction are still included in the following subtasks, resulting in suboptimal policies. In this article, we propose a novel step-wise scheme which explicitly removes the visited nodes in each node selection step. We apply this scheme to two representative deep models for routing problems, pointer network and transformer attention model (TAM), and significantly improve the performance of …

Move: Mobile Observers Variants And Extensions, Ryan Florin

Computer Science Theses & Dissertations

Traffic state estimation is a fundamental task of Intelligent Transportation Systems. Recent advances in sensor technology and emerging computer and vehicular communications paradigms have brought the task of estimating traffic state parameters in real-time within reach.

This has led to the main research question of this thesis: Can a vehicle accurately estimate traffic parameters using onboard resources shared through CV technology in a lightweight manner without utilizing centralized or roadside infrastructure?

In 1954 Wardrop and Charlesworth proposed the Moving Observer method to measure traffic parameters based on an observed number of vehicle passes. We start by proposing methods for detecting …

النقل السري بمدينة فاس, مخلص الدرقاوي العلوي

Dirassat

Clandestine Transport in Fez

The article introduces the peculiarity of the “Clandestine Transport” in Fez and its types, and it assesses its size and spatial distribution. The purpose here is to know the structure of the clandestine transport network and, thus, explain the phenomenon by uncovering its causes. The study makes use of the analysis of bibliographic data and of the opinions of the actors.

The researcher relied mainly- due to the limited data - on the field observation technique as a systematic approach to the article to find the elements to capture the implications of the clandestine transport phenomenon, …

Webinar: Electric Bus Deployment: Cost And Environmental Equity, Cathy Liu

TREC Webinar Series

This presentation introduces an innovative spatiotemporal analytical framework and web-based visualization platform developed by researchers at the University of Utah to assist transit agencies in identifying optimal deployment strategies for a battery-electric bus (BEB) system by using a combination of mathematical programming methods, GIS-based analysis, and multi-objective optimization techniques. The framework allows transit agencies to optimally phase in BEB infrastructure and deploy the BEB system in a way that can minimize the capital and operational cost of the BEB system while maximizing its environmental benefits (i.e., emission reduction).

Equity In Accessibility, A Case Study Of City Of Sacramento, Meredith C. Milam

City and Regional Planning

This paper is a Geographic Information Systems (GIS) spatial analysis of the transportation accessibility and equity in Sacramento, California. A literature review examines discriminatory regulatory policies in the 1900s that wrote racial segregation into law. The effects of these policies have lasting effects on spatial dispersal of people and create barriers to accessibility and therefore result in inequitable transportation systems. The accessibility and equity analysis in Sacramento explores demographic data, job concentration and available modes of transportation, and commuter data. The results of the analysis suggest that there is no “one-size-fits-all” approach when it comes to measuring accessibility and equity. …

Parking Spaces To People Places, Shawn Canny, Natalie Knowles, Arva Hussain, Ann Le, Megan Doherty, Elizabeth Cox

Master of Urban and Regional Planning Workshop Projects

In partnership with the Portland Bureau of Planning and Sustainability (BPS), we sought to better understand how off-street parking space could accommodate economic activity in East Portland, the city’s most economically and racially diverse neighborhood. We focused on two different neighborhoods based on equity considerations and interest: the Rosewood and the Jade Districts. The goal was to better understand these areas with granularity but also to juxtapose them looking for similarities and differences that could guide our recommendations for using parking spaces and serving the community. This project was exploratory in nature. Our research questions and resulting deliverables were dynamic. …

Do Multi-Use-Path Accessibility And The Clustering Effect Play A Role In Residents' Choice Of Walking And Cycling?, Chih-Hao Wang, Na Chen

Mineta Transportation Institute

The transportation studies literature recognizes the relationship between accessibility and active travel. However, there is limited research on the specific impact of walking and cycling accessibility to multi-use paths on active travel behavior. Combined with the culture of automobile dependency in the US, this knowledge gap has been making it difficult for policy-makers to encourage walking and cycling mode choices, highlighting the need to promote a walking and cycling culture in cities. In this case, a clustering effect (“you bike, I bike”) can be used as leverage to initiate such a trend. This project contributes to the literature as one …

Robotic Parking Technology For Congestion Mitigation And Air Quality Control Around Park & Rides, Mahdi Yoozbashizadeh, Forouzan Golshani

Mineta Transportation Institute

A lack or limited availability for parking may have multiple consequences, not the least of which is driver frustration, congestion, and air pollution. However, there is a greater problem that is not widely recognized by the public, namely the negative effect on the use of transit systems due to insufficient parking spaces close to key transit stations. Automated parking management systems, which have been successfully deployed in several European and Japanese cities, can manage parking needs at transit stations more effectively than other alternatives. Numerous studies have confirmed that quick and convenient automobile access to park-and-ride lots can be essential …

What Do Americans Think About Federal Tax Options To Support Transportation? Results From Year Twelve Of A National Survey, Asha Weinstein Agrawal, Hilary Nixon

Mineta Transportation Institute

This report summarizes the results from the twelfth year of a national public opinion survey asking U.S. adults questions related to their views on federal transportation taxes. A nationally-representative sample of 2,516 respondents completed the online survey from February 5 to 23, 2021.

The questions test public opinions about raising the federal gas tax rate, replacing the federal gas tax with a new mileage fee, and imposing a mileage fee just on commercial travel. In addition to asking directly about support for these tax options, the survey collected data on respondents’ views on the quality of their local transportation system, …