published journal article
published journal article
Preprint Journal Article
Ensuring safe and human-like trajectory planning for automated vehicles amidst real-world uncertainties remains a critical challenge. While existing car-following models often struggle to consistently provide rigorous safety proofs alongside human-like acceleration and deceleration patterns, we introduce a novel multi-phase projection-based car-following model. This model is designed to balance safety and performance by incorporating bounded acceleration and deceleration rates while emulating key human driving principles. Building upon a foundation of fundamental driving principles and a multi-phase dynamical systems analysis (detailed in Part 1 of this study citep{jin2025WA20-02_Part1}), we first highlight the limitations of extending standard models like Newell’s with simple bounded deceleration. Inspired by human drivers’ anticipatory behavior, we mathematically define and analyze projected braking profiles for both leader and follower vehicles, establishing safety criteria and new phase definitions based on the projected braking lead-vehicle problem. The proposed parsimonious model combines an extended Newell’s model for nominal driving with a new control law for scenarios requiring projected braking. Using speed-spacing phase plane analysis, we provide rigorous mathematical proofs of the model’s adherence to defined safe and human-like driving principles, including collision-free operation, bounded deceleration, and acceptable safe stopping distance, under reasonable initial conditions. Numerical simulations validate the model’s superior performance in achieving both safety and human-like braking profiles for the stationary lead-vehicle problem. Finally, we discuss the model’s implications and future research directions.
research report
This report documents work performed on PATH TO 5323. Due to an administrative mandate, the work performed and reported herein constitutes only the early stages of the multi-year project that was approved under PATH TO 5323, and subsequently divided into two distinct awards—TO 5323 and TO 6323. Moreover, a series of events during the early stages of the project substantially redirected the original effort. These factors led to a major redirection from the original project. The majority of the work performed under the revised TO 5323 was then to develop a methodology consistent with the new direction of the project, which is detailed in this report.Under the revised direction, the objective of the project is to develop and implement a real-time adaptive control system for corridor management. The proposed control strategy is based on a mathematical representation that describes the behavior of the real-life processes (traffic flow in corridor networks and actuated controller operation). In formulating the optimal control problem, we have restricted our attention to control of only those parameters commonly found in modern actuated controllers (e.g., Type 170 and 2070 controllers). By doing this, we hope to ensure that the procedures developed herein can be implemented with minimal adaptation of existing field devices and the software that controls their operation.
research report |
Mar 2010
Phd Dissertation
Urban transportation systems face ongoing challenges, including noise, air pollution, congestion, and the inefficient use of space. Shared micromobility services (SMSs), including both dockless and station-based bikes and scooters, offer a potential solution to these issues. By providing a flexible mobility alternative, SMSs not only improve urban accessibility but also reduce dependency on short car trips, which can help alleviate traffic congestion and emissions. However, SMSs have received criticism for serving a narrow demographic of residents and visitors while underserving underrepresented individuals. This limitation reduces SMSs’ ability to support a more equitable transportation system.To ensure equitable access to SMS, understanding demand patterns across different communities is crucial. This includes predicting where services will be most needed and ensuring a minimum vehicle supply in underserved areas. However, creating a reliable and equitable service is not straightforward. Each city or region where an SMS exists has unique factors, like geography, demographics, and land use, which all impact SMS demand and access needs. Moreover, cities have differing equity policies that attempt to increase access to SMS in disadvantaged communities.In light of this background, this dissertation addresses the following research questions:What are the key determinants of SMS ridership—both docked and dockless—identified in the existing literature, and how consistent are these factors across different cities and regions with varying urban and socioeconomic characteristics?How do these determinants influence dockless SMS ridership patterns within different zones of a city, and how do these patterns vary between small- and large-sized cities with distinct urban features?What are the existing dockless SMS equity policies, are there systematic biases in the availability of SMS vehicles, and to what extent do equity policies address inequities in SMS accessibility for underserved and minority populations?Chapter 2 of this dissertation identifies the critical factors influencing SMS ridership through a meta-analysis of the existing studies on SMS demand forecast. The meta-analysis aggregates and synthesizes findings from 29 empirical studies and aims to provide: a) a clearer understanding of which SMS ridership predictors have been validated in the literature and should be prioritized for SMS ridership forecast and b) estimates of how these factors impact SMS usage. This meta-analysis serves as a foundation for Chapter 4 of this dissertation.In Chapter 3, the datasets and preprocessing methods that underpin the analyses in subsequent chapters are introduced. This chapter provides a comprehensive overview of the data sources, including Spin’s SMS ridership and operation data, sociodemographic attributes from the American Community Survey (ACS), land use and built environment metrics from the EPA’s Smart Location Database (SLD), transit infrastructure data from General Transit Feed Specifications (GTFS), and points-of-interest (POIs) from Google Places. By combining spatial data, equity policies, and performance metrics, this chapter lays the foundation for understanding how sociodemographic, built environment, and infrastructure variables shape SMS usage and access patterns.Chapter 4 of this dissertation employs spatial regression models, specifically spatial lag models, to analyze dockless SMS ridership across three U.S. cities with diverse urban characteristics: Washington D.C., San Francisco, and Fort Collins. This chapter examines how sociodemographic, built environment, transit supply, and infrastructure factors influence SMS demand, providing city-specific insights into the determinants of ridership. The methodological approach allows for the exploration of spatial dependencies and spillover effects. The findings also reveal significant variability in how these factors impact SMS ridership across cities. By comparing the elasticity findings to meta-analyses of docked SMS systems, this chapter highlights both universal and context-specific drivers of SMS demand. Core factors such as income, population density, employment density, and transit accessibility remain critical across system types. However, the observed variations across cities underscore the necessity of localized SMS strategies tailored to unique urban dynamics.In Chapter 5, this dissertation investigates the distributional equity of dockless SMS in Washington D.C., focusing on the relationship between reliable access to SMS vehicles and socio-demographic, land use, and built environment characteristics. Two proposed metrics for reliable SMS access are developed, combining acceptable walking distances with the number of nearby available scooters. Using data from SMS provider Spin, spatial analyses are conducted to quantify disparities in SMS vehicle access across neighborhoods. The results reveal that areas with higher poverty ratios are consistently underserved, while neighborhoods with higher non-white populations are oversupplied, highlighting inequities in vehicle accessibility. Additionally, areas with an abundance of activity locations (parks, museums, restaurants, and hotels) often face undersupply.
published journal article
Public interest in the environment is building as we gain information about the deterioration in air quality and the potential threat of global warming. This research addresses the dichotomy between an individual’s behavior and his or her attitudinal support for policies which are promoted as benefiting the environment. We study how responses to attitudinal survey questions are interrelated, and how such responses are related to actual travel behavior using data from a survey undertaken in six capital cities in Australia in 1994. A measurement model is used to establish a set of latent attitudinal factors, and these factors are related in a structural equations model to a set of behavioral variables representing commuters’ mode choice and choice of compressed work schedules, conditioned by a set of exogenous variables. Individuals with a strong environmental commitment are more likely to be female, from smaller households with fewer cars, be either under 30 years old or over 50 years old, have high household income and be highly educated. However, women are likely to view the car as a status symbol, and this attitude is conducive to choice of solo driving. Commuters who use public transport are more likely to support policies aimed at reducing greenhouse gas emissions. Switching commuters away from solo driving can have effects that transcend the benefit obtained from reduced vehicle use for the journey to work alone. (C) 1998 Elsevier Science Ltd. All rights reserved.
published journal article
conference paper
working paper
This paper presents an event-based simulation framework designed specifically for applying activity-based transportation models to a variety of problems. General concepts of activity-based travel modeling are discussed followed by a specification of abstract con cepts common to most activity modeling approaches. A simulation framework is developed and implemented in two examples to demonstrate the feasibility of the concepts presented.
book/book chapter