This study presents multiple approaches to the analysis of crash injury severity at three- and four-legged unsignalized intersections in the state of Florida from 2003 until 2006. An extensive data ...collection process was conducted for this study.
The dataset used in the analysis included 2,043 unsignalized intersections in six counties in the state of Florida. For the scope of this study, there were three approaches explored. The first approach dealt with the five injury levels, and an ordered probit model was fitted. The second approach was an aggregated one, and dealt with only the severe versus non-severe crash levels, and a binary probit model was used. The third approach dealt with fitting a nested logit model. Results from the three fitted approaches were shown and discussed, and a comparison between the three approaches was shown.
Several important factors affecting crash severity at unsignalized intersections were identified. These include the traffic volume on the major approach, and the number of through lanes on the minor approach (surrogate measure for traffic volume), and among the geometric factors, the upstream and downstream distance to the nearest signalized intersection, left and right shoulder width, number of left turn movements on the minor approach, and number of right and left turn lanes on the major approach. As for driver factors, young and very young at-fault drivers were associated with the least fatal probability compared to other age groups.
The analysis identified some countermeasures to reduce injury severity at unsignalized intersections. The spatial covariates showed the importance of including safety awareness campaigns for speeding enforcement. Also, having a 90-degree intersection design is the most appropriate safety design for reducing severity. Moreover, the assurance of marking stop lines at unsignalized intersections is very essential.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•A CAVs distributed cooperation method for unsignalized intersections is proposed.•Rotation projection is used to transform 2D vehicle clusters to 1D virtual platoons.•A spanning tree is used to ...construct the conflict-free geometry topology.•The algebraic graph theory is used to model the system dynamics.
Connected vehicles will change the modes of future transportation management and organization, especially at intersections. In this paper, we propose a distributed conflict-free cooperation method for multiple connected vehicles at unsignalized intersections. We firstly project the approaching vehicles from different traffic movements into a virtual lane and introduce a conflict-free geometry topology considering the conflict relationship of involved vehicles, thus constructing a virtual platoon. Then we present the modeling of communication topology to describe two modes of information transmission between vehicles. Finally, a distributed controller is designed to stabilize the virtual platoon for conflict-free cooperation at intersections. Numerical simulations validate the effectiveness of this method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Cooperation of connected vehicles is a promising approach for autonomous intersection control. This article presents a systematic approach to the cooperation of connected vehicles at unsignalized ...intersections without global coordination. A task-area partition framework is proposed to decompose the mission of cooperative passing into three main tasks, i.e., vehicle state observation, arriving time optimization, and trajectory tracking control. To accomplish these tasks, a distributed observation algorithm is introduced to achieve fixed-time observation of other vehicles' states for passing sequence determination, a distributed optimization algorithm is introduced to schedule conflict-free arriving times for trajectory planning, and a distributed control algorithm is proposed to address parameter mismatches and acceleration saturation for fixed-time trajectory tracking control. Numerical simulations demonstrate that the proposed method can achieve cooperative passing of vehicles without global coordination at the cost of a growth of 8.8-18.1% average travel times in low and medium traffic volumes.
•Development of a consensus-based control logic for the movement of CAVs through signal-free intersections.•Development of CAV-level mixed-integer non-linear programs.•Minimizing each CAV’s travel ...time and speed variations while avoiding near-crash conditions.•Development of a distributed coordinated algorithm to obtain real-time CAV trajectories.•Achieving 43% to 70.5% reduction in travel time under various demand levels.
This paper develops a distributed cooperative control logic to determine conflict-free trajectories for connected and automated vehicles (CAVs) in signal-free intersections. The cooperative trajectory planning problem is formulated as vehicle-level mixed-integer non-linear programs (MINLPs) that aim to minimize travel time of each vehicle and their speed variations, while avoiding near-crash conditions. To push vehicle-level solutions towards global optimality, we develop a coordination scheme between CAVs on conflicting movements. The coordination scheme shares vehicle states (i.e., location) over a prediction horizon and incorporates such information in CAVs’ respective MINLPs. Therefore, the CAVs will reach consensus through an iterative process and select conflict-free trajectories that minimize their travel time. The numerical experiments quantify the effects of the proposed methodology on traffic safety and performance measures in an intersection. The results show that the proposed distributed coordinated framework converges to near-optimal CAV trajectories with no conflicts in the intersection neighborhood. While the solutions are found in real-time, the comparison to a central intersection control logic for CAVs indicates a maximum marginal objective value of 2.30%. Furthermore, the maximum marginal travel time, throughput, and average speed do not exceed 0.5%, 0.1%, and 0.5%, respectively. The proposed control logic reduced travel time by 43.0–70.5%, and increased throughput and average speed respectively by 0.8–115.6% and 59.1–400.0% compared to an optimized actuated signal control, while eliminating all near-crash conditions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this paper, we propose a new cooperative driving strategy for connected and automated vehicles (CAVs) at unsignalized intersections. Based on the tree representation of the solution space for the ...passing order, we combine Monte Carlo tree search (MCTS) and some heuristic rules to find a nearly global-optimal passing order (leaf node) within a very short planning time. Testing results show that this new strategy can keep a good tradeoff between performance and computation flexibility.
This study constructs a decision-making control framework for autonomous ego vehicles (AEVs) based on Soft Actor-Critic (SAC) in a random driving task scenario at an unsignalized intersection. The ...environment vehicles include both AEV and surrounding vehicles, and the three driving tasks through unsignalized intersections are going straight, left turn, and right turn. Since the driving tasks of AEV and surrounding vehicles are random, the environment is characterized by high uncertainty and difficulty. There are three innovative points in this paper. First, this paper proposes a new Mix-Attention Network based on the attention mechanism. Second, this paper improves the state by introducing a new input quantity to represent the driving task of the vehicle itself. Third, this paper has been enhanced in replay buffer, using more collision and arrival experiences to train the neural network. In this paper, the performance of the original and improved models is evaluated in terms of safety and efficiency. The simulation results show that all three proposed improvement methods can improve performance and achieve better results.
Objectives: The present study is an attempt to analyze and compare the distraction effects caused by the use of a phone and a music player at unsignalized intersections.
Method: Eighty-eight ...participants performed simulated driving experiments where they faced a sequence of gaps in the major road traffic at 2 unsignalized intersections. In this process, their driving behavior was evaluated in terms of gap acceptance probability, accepted lag, and maneuver completion time. These parameters were modeled with a generalized estimating equation (GEE) method by considering distraction, demographic factors, driving history, maneuver types, and driving attributes in the approach and completion zones as independent variables.
Results: The results showed that gap acceptance probability decreased by 46% during the conversation task, whereas it increased by 66% during the music player task. Lower gap acceptance could be a compensatory behavior adopted by drivers during the conversation task, whereas no such measure was adapted during the music player task. The results indicate that a higher approach speed during the music player task might have led to increased gap acceptance. Further, though the effect of distraction on the accepted lag was not evident, the completion time was reduced during the conversation task.
Conclusions: Overall, the results suggest that drivers are more likely to adopt a compensatory measure in complex driving situations only if they perceive a high risk. Hence, drivers are exposed to a greater risk while operating a music player, because this is not perceived as risky behavior.
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Knowledge transfer is a promising concept to achieve real-time decision-making for autonomous vehicles. This paper constructs a transfer deep reinforcement learning (RL) framework to transform the ...driving tasks in the intersection environments. The driving missions at the unsignalized intersection are cast into a left turn, right turn, and running straight for automated vehicles. The goal of the autonomous ego vehicle (AEV) is to drive through the intersection situation efficiently and safely. This objective promotes the studied vehicle to increase its speed and avoid crashing other vehicles. The decision-making policy learned from one driving task is transferred through three transfer rules in another driving mission and evaluated. Simulation results reveal that the decision-making strategies related to similar tasks are transferable and have a high success rate. It indicates that the presented control framework could reduce time consumption and realize online implementation. Therefore, the transfer RL concept is helpful for establishing the real-time decision-making policy for autonomous vehicles.
We partially correct and significantly deepen the Siegloch’s method (1973), which is currently used to determine the capacity of unsignalized intersections. Taking into account current knowledge ...about microstructure of vehicular traffic flows we suggest Generalized Inverse Gaussian distribution as a theoretically and empirically substantiated alternative to the exponential distribution of priority-stream clearances, considered in Siegloch’s original methodology. Furthermore, we formulate a statistical model for gap-acceptance theory and present a series of validated theoretical calculations leading to general formulas for proportion and statistical distribution of priority-stream clearances that exactly k minor-stream vehicles have utilized for their inclusion maneuver (accepted-clearance distribution of order k). Using up-to-date empirical data-sets we test hypotheses of priority-stream clearance-distribution and analyze sample acceptance-ratios and empirical distribution of accepted clearances. By means of an original concept we finally estimate an implicit acceptance-rule, with the help of which a minor-street driver is deciding on acceptance/rejection of an offered priority-clearance.
•We deepen and partially correct the Siegloch’s method for determination of capacity of unsignalized intersections.•We introduce advanced probabilistic model for Gap Acceptance problem.•We investigate clearance distribution of urban vehicular traffic.•We introduce compact mathematical model for statistics of gaps being accepted by exactly k vehicles.•We reveal the acceptance rule for decision-making of minor-street drivers.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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