Towards the design of robotic drivers for full-scale self-driving racing cars

Autonomous vehicles are undergoing a rapid development thanks to advances in perception, planning and control methods and technologies achieved in the last two decades. Moreover, the lowering costs of sensors and computing platforms are attracting industrial entities, empowering the integration and development of innovative solutions for civilian use. Still, the development of autonomous racing cars has been confined mainly to laboratory studies and small to middle scale vehicles. This paper tackles the development of a planning and control framework for an electric full scale autonomous racing car, which is an absolute novelty in the literature, upon which we report our preliminary experiments and perspectives on future work. Our system leverages real time Nonlinear Model Predictive Control to track a pre-planned racing line. We describe the whole control system architecture including the mapping and localization methods employed

An Invitation to a New Transportation Mode

The trends of Personal Rapid Transit (PRT) and Automated Highways are converging. The result may be a new transportation mode built around robotic vehicles. This paper outlines how technology can transform transportation, making it more convenient, safer, more sustainable and less subject to congestion. Such a system could utilize existing infrastructure, but split highway lanes in half with vehicles less than a meter wide. This paper presents lessons from several relevant vehicles that the author's research teams have worked on. It describes open source work in progress and invites participation from other researchers

Robocart: System Design for the First Generation Autonomous Golf Cart

Inspired by ongoing research and continuous developments in autonomous vehicles, the Robocart MQP focuses on the system development for a first-generation autonomous golf cart vehicle and wireless system server. By creating the foundation for a modular and interdisciplinary system, visualization software and mechanisms can be intuitively integrated. The end result of this project is a better understanding of the efficiency of each subsystems against the real-time challenges required for an autonomous, wireless, and vision-based system. In conclusion of this project, recommendations in mechanical, electrical, and algorithm development were formed to promote further research and enhance rider usability

Kinisi: A Platform for Autonomizing Off-Road Vehicles

This project proposed a modular system that would autonomize off-road vehicles while retaining full manual operability. This MQP team designed and developed a Level 3 autonomous vehicle prototype using an SAE Baja vehicle outfitted with actuators and exteroceptive sensors. At the end of the project, the vehicle had a drive-by-wire system, could localize itself using sensors, generate a map of its surroundings, and plan a path to follow a desired trajectory. Given a map, the vehicle could traverse a series of obstacles in an enclosed environment. The long- term goal is to alter the software system to make it modular and operate in real-time, so the vehicle can autonomously navigate off-road terrain to rescue and aid a distressed individual

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs

Autonomous Shuttle Transit: An Exploratory Case Study and the Future Impact on TSU Campus

By 2040 the third-largest city in the United States, Houston, Texas, a top global city for traffic congestion, will become a significant metropolis with future growth possibilities of 11 million people passing Chicago (HGAC, 2018). For this purpose, Houston and surrounding growing populations will contribute to gridlock traffic, with highway expansions increasing ozone and inefficient transit systems with longer commutes in underserved, sidelined communities. Above all, historically, persons of color, notably Black Indigenous Persons of Color (BIPOC) in Black and Brown marginalized communities, are deprived of transportation accessibility. Undoubtedly, Driverless Shuttle (DS) rideshare platforms reflect that higher-income whites are admittedly more likely to hold discriminatory attitudes toward fellow passengers of different classes and races (Middleton & Zhao, 2019). At the same time, Environmental Justice (EJ) studies have shown that Black and Brown low-income disenfranchised communities are more exposed to inefficient transit systems. They are characterized by unequal treatment and accessibility to the bus than affluent White commuters (Bullard, Johnson, and Torres, 2004). As a result, systemic racism, an unfair burden of environmental injustice, has plagued the Greater Third Ward transit-dependent population. For this purpose, Houston\u27s Metropolitan Transit Authority (METRO) riddle inequities have shaped public transportation for every minoritized BIPOC within the community (Spieler, 2020). Most importantly, Blacks are twice as likely to experience inferior transportation access as their more affluent counterparts (Sisson, 2019; Bullard, Johnson, and Torres, 2004, p.2). According to Harvard Law (2021), Bullard states, In 1990, Dumping in Dixie: Race, Class and Environmental Quality assuredly documented that environmental vulnerability mapped closely with Jim Crow segregation. This why racial redlining discriminatory zoning, and inefficient land use practices, (Bullard, 2021, p. 245; Bullard, 1990) target Houston\u27s Black and Brown neighborhoods, hindering economic and social advancement in employment, education, and health care (Bullard, 2021, p. 245; Bullard, 1990; Freemark, 2020; Talbott, 2020). The problem of injustice was examined by longitudinal data where an Autonomous Vehicle bus pilot associated with the built environment in this study highlighted 1. Transportation inequality along the TSU Campus Tiger Walk is related to bus stops. 2. Distance between three designated bus stop locations. 3. Safety and critical driving functions fully driverless for an entire trip. 4. First/last mile driverless shuttle connectivity interacting with Metro buses and Light Rail in Houston\u27s Greater Third Ward neighborhood. The methods of research incorporated qualitative and quantitative analysis. The study used a driverless shuttle to compare racial and social economics between bus stops at Texas Southern University, a historically black university, during an Autonomous Vehicle (AV) Shuttle pilot study. For this purpose, Autonomous Shuttle Transit, an additional mode of mobility, will connect Houston\u27s Greater Third Ward transit-dependent population to Metro’s bus and light rail networks. In addition to bus stops along the TSU Campus Tiger Walk. This study made a similar theoretical comparison of the Tiger Tram to AV two years before the TSU Shuttle pilot. The results pointed to a link between income and transit-dependent populations using a driverless shuttle under specific conditions. A Google map determined the half-mile distance along the TSU Campus Tiger Walk. The driverless shuttle and socioeconomics of Political Science, Administrative Justice, and Psychology undergraduate classes were used to measure transportation equity horizontally. A regression analysis was carried out to determine if the socioeconomic factors had statistical significance. Also, linear regression modeling was used to determine which sociodemographic variables strongly predict the transport mode used. The findings revealed that Blacks, people with disabilities, and the TSU AV shuttle working with metro buses were statistically significant at a 95% confidence level. Also, a predictor of respondents walking, and biking will use the Autonomous Shuttle as an additional mode of transportation. Also, the data analysis results indicate a significant negative correlation between the driverless shuttle time intervals along the TSU Tiger Walk and the Metro bus service. This correlation implies that higher percentages of respondents will walk further from the TSU campus Tiger Walk central location to the bus stop connecting Third Ward’s transit-dependent residents to the Metro Light rail. Likewise, in the Third Ward community, low-income transit-dependent populations in the Cuney Homes are disproportionately exposed to inadequate transit access than any other area in the neighborhood. The results also support the Environmental Justice (EJ) claim that minorities and low-income transit-dependent populations are closer to bus stops and farther away from the light rail. Although the results showed that race, income, and disability variations are likely to predict that TSU’s transit-dependent population will use the TSU Autonomous Shuttle connecting the Third Ward community. Comparing the social demographic indicators along the TSU Tiger Walk and the Third Ward area shows that deed restrictions do not address EJ concerns associated with bus stops and transportation modes. The conclusion indicates that despite several decades of EJ policies and transit regulations, institutional racism in the Third Ward neighborhood is embedded. Over the decades, African Americans and other people of color have been disproportionately exposed to transit injustice because they are concentrated in neighborhoods with less transit accessibility. However, the TSU Campus Tiger Walk still has fewer efficient transit options than other Third Ward census tracts that map closer to bus stops with higher income

Automated driving and autonomous functions on road vehicles

In recent years, road vehicle automation has become an important and popular topic for research and development in both academic and industrial spheres. New developments received extensive coverage in the popular press, and it may be said that the topic has captured the public imagination. Indeed, the topic has generated interest across a wide range of academic, industry and governmental communities, well beyond vehicle engineering; these include computer science, transportation, urban planning, legal, social science and psychology. While this follows a similar surge of interest – and subsequent hiatus – of Automated Highway Systems in the 1990’s, the current level of interest is substantially greater, and current expectations are high. It is common to frame the new technologies under the banner of “self-driving cars” – robotic systems potentially taking over the entire role of the human driver, a capability that does not fully exist at present. However, this single vision leads one to ignore the existing range of automated systems that are both feasible and useful. Recent developments are underpinned by substantial and long-term trends in “computerisation” of the automobile, with developments in sensors, actuators and control technologies to spur the new developments in both industry and academia. In this paper we review the evolution of the intelligent vehicle and the supporting technologies with a focus on the progress and key challenges for vehicle system dynamics. A number of relevant themes around driving automation are explored in this article, with special focus on those most relevant to the underlying vehicle system dynamics. One conclusion is that increased precision is needed in sensing and controlling vehicle motions, a trend that can mimic that of the aerospace industry, and similarly benefit from increased use of redundant by-wire actuators