Tianyi Li

Saint Louis University | SLU · Department of Civil Engineering

This study introduces a novel control framework for adaptive cruise control (ACC) in autonomous vehicles (AVs), utilizing Long Short-Term Memory (LSTM) networks and physics-informed constraints. The LSTM component captures complex vehicle dynamics and temporal dependencies, while physics constraints ensure realistic operational limits. This framewo...

Introduction: Many factors influence the yielding result of driver–pedestrian interactions, including traffic, vehicle, roadway, pedestrian attributes, and more. While researchers have examined the individual influence of these factors on interaction outcomes, there is a noticeable absence of comprehensive, naturalistic studies in current literatur...

Urban mobility and transportation systems have been profoundly transformed by the advancement of autonomous vehicle technologies. Baidu Apollo Go, a pioneer robotaxi service from the Chinese tech giant Baidu, has recently been widely deployed in major cities like Beijing and Wuhan, sparking increased conversation and offering a glimpse into the fut...

Automated Vehicles (AVs), particularly those with Adaptive Cruise Control (ACC), are increasingly integral to intelligent transportation systems, but they bring new cybersecurity challenges. This study explores the subtleties of cyberattacks targeting ACC vehicles, specifically through false data injection, and assesses their impact on traffic dyna...

Automated vehicles (AVs) hold the potential to significantly improve traffic flow, reducing travel time, energy consumption, and emissions. However, until AVs achieve high market penetration rates, navigating the transition to mixed-autonomy traffic — comprising both AVs and human-driven vehicles (HVs) — presents substantial challenges. While numer...

Various factors impact driver-pedestrian interactions, such as traffic, vehicle, roadway, and pedestrian attributes. However, comprehensive studies exploring the influence of the built environment on driver yielding are lacking in current literature. To bridge this gap, our study presents an open-source dataset derived from video data at 18 unsigna...

This paper introduces RACER, the Rational Artificial Intelligence Car-following model Enhanced by Reality, a cutting-edge deep learning car-following model, that satisfies partial derivative constraints , designed to predict Adaptive Cruise Control (ACC) driving behavior while staying theoretically feasible. Unlike conventional models, RACER effect...

With the emergence of vehicles featuring advanced driver-assistance systems like adaptive cruise control (ACC) and additional automated driving functionalities, there has arisen a heightened potential for cyberattacks targeting these automated vehicles (AVs). While overt attacks that lead to collisions are more conspicuous, subtle attacks that slig...

With the advent of vehicles equipped with advanced driver-assistance systems, such as adaptive cruise control (ACC) and other automated driving features, the potential for cyberattacks on these automated vehicles (AVs) has emerged. While overt attacks that force vehicles to collide may be easily identified, more insidious attacks, which only slight...

The emergence of automated vehicles (AVs) with driver-assist features, such as adaptive cruise control (ACC) and other automated driving capabilities, promises a bright future for transportation systems. However, these emerging features also introduce the possibility of cyberattacks. A select number of ACC vehicles could be compromised to drive abn...

The driving characteristics of individual vehicles in the flow have been shown to influence the aggregate traffic flow characteristics. This is true both for individual human drivers as well as vehicles with some level of automation, such as adaptive cruise control (ACC). Knowledge of the individual constituents of the traffic flow will allow for m...

The driving characteristics of individual vehicles in the flow have been shown to influence the aggregate traffic flow characteristics. This is true both for individual human drivers as well as vehicles with some level of automation, such as adaptive cruise control (ACC). Knowledge of the individual constituents of the traffic flow will allow for m...

The data collection took place at 18 intersections in Minnesota. Data collection was conducted at 18 sites across Minnesota to capture various road types, and intersection features during the summer months. The TIMs were deployed to each location for between one and two weeks, and video was recorded during daylight hours only. The Minnesota Traffic...

Max-pressure signal control has been analytically proven to maximize the network throughput and stabilize queue lengths whenever possible. Since there are many transit lines operating in the metropolis, the max-pressure signal control should be extended to multi-modal transportation systems to achieve more widespread usage. The standard max-pressur...

The explosive popularity of transportation network companies (TNCs) in the last decade has imposed dramatic disruptions on the taxi industry, but not all the impacts are beneficial. For instance, studies have shown taxi capacity utilization rate is lower than 50% in five major U.S. cities. With the availability of taxi data, this study finds the ta...

The explosive growth of transportation network companies (TNCs) in the last decade has posed dramatic disruptions on the taxi industry. This paper investigates how ridesourcing services impacted the taxi industry from both spatial and temporal perspectives in the city of Chicago. With the taxi data from 2014 to 2019 and TNCs data in 2019 from the C...