Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes

In intelligent transportation systems, most of the research work has focused on lane change assistant systems. No existing work considers minimizing the interruption of traffic flow by maximizing the number of lane changes while eliminating the collisions. In this thesis, we develop qualitative and quantitative approaches for minimizing the interruption of traffic flow for three lane scenarios and show that we can extend our approach to any random number of lanes. The algorithm we propose in this thesis is able to achieve the maximum number of lane changes provided that only one vehicle per group (novel concept which is described in this thesis) is allowed to change lanes at a time. Simulation results show that our approach provides much better performance when compared with different lane change algorithms without incurring large overhead, and is hence suitable for online use

Path tracking control for inverse problem of vehicle handling dynamics

A path tracking controller based on active disturbance rejection control(ADRC) theory is presented in this paper to solve path tracking problem in inverse vehicle handling dynamics. The basic idea behind the work is to design an active disturbance rejection controller according to yaw rate and lateral displacement during a vehicle travels along a prescribed path to generate an expected trajectory which guarantees minimum clearance to the prescribed path. Aiming at this purpose, using preview follower theory, a linear extended state observer based on lateral displacement is designed. Considering yaw angle of vehicle, a non-linear combination function combined error of lateral displacement as well as error of yaw angle is designed according to monotone bounded hyperbolic of tangent function. Finally, a real vehicle test is executed to verify the rationality of the path tracking controller. At the same time, according to characteristics of pavement file in Carsim, a 3-D virtual pavement model is established and ride comfort simulation of random pavement is carried out in the software model. The results show that the minimum lateral position error of the generated path tracking trajectory can be good indicators of successful solving of the path tracking problem in inverse vehicle handling dynamics for ADRC. More precisely, there is higher calculation accuracy for the algorithm of the ADRC to solve the path tracking problem. The study can help drivers easily identify safe lane-keeping trajectories and area

Acquisition of relative vehicle trajectories to facilitate freeway merging using DSRC based V2V communication

University of Minnesota M.S.E.E. thesis.November 2017. Major: Electrical Engineering. Advisor: Imran Hayee. 1 computer file (PDF); vi, 39 pages.For the anticipated benefits of connected vehicle technology, Intelligent Transportation Systems Joint Program Office (ITSJPO) of the US Department of Transportation continues to emphasize the need for having Dedicated Short Range Communication (DSRC) based vehicle to vehicle (V2V) and/or vehicle to infrastructure (V2I) communication to enhance driver safety and traffic mobility. To take full advantage of connected vehicle technology in most safety applications, precise vehicle positioning information is neeeded in addition to V2V communication. Although, there are many techniques including vision or sensor based systems and differential GPS receivers, which can obtain precise absolute position of a vehicle at the expense of cost and complexity, some critical safety applications such as merge assist or lane change assist systems require only relative positions of surrounding vehicles with lane level resolution so a given vehicle can differentiate the vehicles on its own lane from the vehicles on adjacent lanes. We have adopted a simple approach to acquire accurate relative trajectories of surrounding vehicles using standard GPS receviers and DSRC based V2V communication. Using this approach, we have conducted field tests to successfully acquire relative trajectories of vehicles travelling on multiple lanes towards a merging junction with an accuracy of ±0.5m. The achieved accuracy level in relative trajectory was sufficient to differentiate vehicles travelling on adjacent lanes of a multiple-lane freeway

Highway Safety and Traffic Flow Analysis of Mixed traffic with Connected and Non-Connected Vehicles

Safety is the number one issue in the deployment of any vehicle technology. This leads to two interconnected challenges. First, how to ensure safety without having a significant negative impact in traffic flow. Second, how will varying penetrations of autonomous vehicles (AVs) impact safety and efficiency in mixed traffic. To address these issues, we start by proposing a risk metric that takes into account the severity of a collision that would happen under a worst-case scenario and the time the vehicle is exposed to such a collision. With this definition, we propose an autonomous lane changing procedure in which the vehicle behaves as if it was simultaneously on both lanes. This ensure that the vehicle never puts itself in a collision prone situation. Given the conservative nature of this approach, which can negatively impact traffic flow, we include the possibility of the AV accepting risks in its gap acceptance decision process. We extend this approach to a scenario with connected and autonomous vehicles (CAV), which can cooperate to generate lane change gaps through communications. In this case, a CAV in the destination lane also behaves as if it was simultaneously on two lanes, thus generating the gap for the incoming vehicle. We perform extensive micro simulations using the commercial software VISSIM with varying percentages of AVs and CAVs, different vehicle inputs, and several accepted risk values. Results indicate that, while AVs need to accept small risks in order to achieve the same traffic flow efficiency as humans, CAVs can improve both safety and efficiency without having to accept any risks. Our results also indicate that AVs and CAVs still behave safely in mixed fleets, but they do not bring significant improvements in traffic flow

2014 Year in Review

The Mountain-Plains Consortium (MPC) theme is "Transportation Infrastructure and Operations to Support Sustainable Energy Development and the Safe Movement of People and Goods". MPC is a competitively selected University Transportation Center sponsored by the U.S. Department of Transportation through its Research and Innovative Technology Administration

Utah State University Commencement, 2014 – Main Campus

127th Annual Commencement of Utah State University.https://digitalcommons.usu.edu/commencement/1126/thumbnail.jp

Security of Cyber-Physical Systems

Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems