Passing collisions are one of the most dangerous traffic safety problems. These head-on collisions occur when the driver of the passing vehicle is distracted or does not assess the situation appropriately. The purpose of this study is to develop a passing collision warning system (PCWS) for drivers on two-lane highways to prevent passing collisions and improve road safety. This paper presents a framework and algorithm design for a PCWS that ensures that drivers have an adequate sight distance for a safe passing maneuver. The system uses an available radar sensor to detect the closest opposing vehicle traveling in the left lane and calculates its position, speed, and acceleration rate to estimate the time to collision and compare it with the time required for the passing vehicle to clear the lane. Realistic initial time and passing time models were established using actual experimental field data collected using a global positioning system (GPS) data logger device that was installed in the passing, impeding, and opposing vehicles and used to record the position and speed of different passing vehicles at 1-s intervals. The MATLAB simulation was developed and used to replicate real-life passing maneuvers and was also used to create the algorithm for the proposed warning system. The passing maneuver parameters were selected from probability distribution curves based on field data. The simulation model determines the relative distance and speed of the opposing vehicle at four different time intervals. The different factors that impact system accuracy were also examined.
28Gap availability is an important element of safe passing on two-lane highways. Time gaps are 29 used to determine passing behaviour based on human factors. In this paper, the decision whether 30 to accept or reject an available passing gap is modelled using logistic regression technique that 31 included driver characteristics (age and experience) and the gap size. Field studies were 32 conducted to collect experimental data regarding passing driver behaviour. The data were 33 collected using Dual Camera Car DVRs and a GPS data logger device that records the 34 instantaneous speed and position of the three vehicles involved in the passing maneuver: passing 35 vehicle, impeding vehicle, and opposing vehicle. Regression models that include driver age and 36 gender (required as input to the gap acceptance model) were established for initial passing time, 37 starting gap, ending gap, and time to collision. The gap acceptance model was implemented in 38 SIMULINK and the results revealed that driver characteristics significantly affect gap 39 acceptance decisions. 40 41
The paper presents models of path and control planning for parking, docking, and movement of autonomous vehicles at low speeds considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models are used. Recent works on the development of parking algorithms for autonomous vehicles are reviewed. Bicycle kinematic models for vehicle motion are considered for three basic types of vehicles: passenger car, long wheelbase truck, and articulated vehicles with and without steered semitrailer axes. Mathematical descriptions of systems of differential equations in matrix form and expressions for determining the linearization elements of nonlinear motion equations that increase the speed of finding the optimal solution are presented. Options are proposed for describing the interaction of vehicle overall dimensions with the space boundaries, within which a maneuver should be performed. An original algorithm that considers numerous constraints is developed for determining vehicle permissible positions within the closed boundaries of the parking area, which are directly used in the iterative process of searching for the optimal plan solution using nonlinear model predictive control (NMPC). The process of using NMPC to find the best trajectories and control laws while moving in a semi-limited space of constant curvature (turnabouts, roundabouts) are described. Simulation tests were used to validate the proposed models for both constrained and unconstrained conditions and the output (state-space) and control parameters' dependencies are shown. The proposed models represent an initial effort to model the movement of autonomous vehicles for parking and has the potential for other highway applications.
In passing maneuvers on two-lane highways, assessing the needed distance and the potential power reserve to ensure the required speed mode of the passing vehicle is a critical task of speed planning. This task must meet several mutually exclusive conditions that lead to successful maneuvers. This paper addresses three main aspects. First, the issues associated with a rational distribution of the speed of the passing vehicle for overtaking a long commercial vehicle on two-lane highways are discussed. The factors that affect the maneuver effectiveness are analyzed, considering the safety and cost. Second, a heuristic algorithm is proposed based on the rationale for choosing the necessary space and time for overtaking. The initial prediction’s sensitivity to fluctuations of the current measurements of the position and speed of the overtaking participants is examined. Third, an optimization technique for the passing vehicle speed distribution during the overtaking time using the finite element method is presented. Adaptive model predictive control is applied for tracking the references being generated. The presented model is illustrated using a simulation.
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