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

Modern vehicles are equipped with various sensors of high accuracy and sensitivity, based on which it is possible to implement passing collision warning systems (PCWS) for two-lane highways. In previous systems, the time required to complete the passing maneuver safely was formulated based on pre-established regression models. In this paper, this time is formulated based on actual vehicle characteristics. The new vehicle dynamics model for the PCWS prototype includes steering control and drivetrain models, and allows more accurate prediction of the required passing time. The geometry of the passing maneuver (for the case of an impeding truck), the main phases of the passing process, and the distances related to the conditions for predicting passing time are described. The interactions between the PCWS and driver actions are formulated. The steering control model is based on a two-dimensional perspective representation of the three-dimensional reality perceived by the driver. The drivetrain model, including inertial and mechanical losses in the drivetrain, considers automatic gear shift and the presence of a torque converter to simulate vehicle performance accurately. The proposed PCWS was tested using MATLAB Simulink.

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Passing collisions are one of the most serious traffic safety problems on two-lane highways. These collisions occur when a driver overestimates the available sight distance. This paper presents a framework for a passing collision warning system (PCWS) that assists drivers in avoiding passing collisions by reducing the likelihood of human error. The system uses a combination of a camera and radar sensors to identify the impeding vehicle type and to detect the opposing vehicles traveling in the left lane. The study involved the development of a steering control model providing lane-change maneuvers, the design of a driving simulator experiment that allows for the collection of data necessary to estimate passing parameters, and the elaboration of the algorithm for the PCWS based on sensor signals to detect impeding vehicles such as trucks. Simulation tests were carried out to confirm the effectiveness of the proposed PCWS algorithm. The impact of driver behavior on passing maneuvers was also investigated. Mathematical and imitation models were enhanced to implement Simulink for replications of real-life driving scenarios. The different factors that affect system accuracy were also examined.