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Route guidance variable message signs (VMS) are widely applied in traffic incident management on highways by providing real-time spatiotemporal guidance information. The improper panel of route guidance VMS is likely to diminish the compliance with guidance and induce risky driving behaviors, disrupting the traffic flow or even causing crashes. This article aims to investigate the effects of route guidance VMS on driving behaviors in three aspects, vehicle operation, visual perception, and route choice. A driving simulation study with 32 participants was carried out to investigate the driving performance under four different VMS recognizing conditions: baseline (a typical guide sign) and three route guidance VMS panel schemes. Significant differences in average speed, speed fluctuation, average acceleration, and fixation proportion were found under various VMS recognition conditions. VMS3 had the least negative effects on vehicle operation and visual perception, and the compliance rate under VMS3 was the highest. The possible reasons are as follows: VMS3 has the simplified highway network structure and highlights the road directions with an eye-catching symbol, which can increase the comprehensibility of the guidance information while driving. Drivers need to take multiple actions under high-speed driving conditions while recognizing VMS, including reading the route guidance VMS, remaking route decisions, and operating the vehicle concurrently. Under such circumstances, the improper VMS panel would attract more drivers' attention and induce excessive risk compensatory behaviors, reducing drivers' compliance with guidance and situation awareness, and increasing crash risks. In addition, some VMS related traffic management strategies were proposed to improve safety and mobility of highways and further provide a basis for the formulation of related standards. [ABSTRACT FROM AUTHOR]

The real-time traffic conflict risk warning system (RTCRWS) is proposed as a new proactive crash prevention and control strategy for intersections designed to reduce traffic on the main road to rural unsignalized intersections when a vehicle enters the access roads. This study aims at evaluating the effectiveness of the RTCRWS with different locations based on a driving simulation experiment. In this study, four types of the RTCRWS installation location schemes (i.e., no installation, 50 m/100 m/150 m away from the unsignalized intersection) are designed. Twenty-two experienced drivers participated in the driving simulation experiment, and seven evaluating indicators representing driving behavior data are proposed. Two methods to analyze the data are applied: (1) descriptive analysis of driving behavior characteristics different location schemes of the RTCRWS and (2) entropy weight-fuzzy comprehensive evaluation of the RTCRWS. The results show that the RTCRWS has a significant effect on slowing vehicles when approaching the rural unsignalized intersections. If the location of the RTCRWS is 50 m, 100 m, and 150 m from the intersection, the comprehensive score of fuzzy evaluation is 75.82, 74.91, and 77.22, respectively, which implies that the scheme with the RTCRWS 150 m ahead of the intersection is the most effective. [ABSTRACT FROM AUTHOR]

• Driving simulation data and naturalistic driving data are verified mutually. • Distribution of ' speed-spacing-TTCi ' is applied to classify the risky state. • Intervention methods include visual, acoustics and acousto-optical. • The three-level graded alarm is calibrated by driving styles. Rear-end collision and side collision are two types of accidents with the highest accident rate in the world. Numerous studies have focused on rear-end accident research, but only a few constructive countermeasures are put forward. Driving risk evolution at the driver operational level before an accident is critical to collision avoidance. This paper puts forward a driver operational level identification of driving risk and graded alarm under near-crash conditions. Firstly, driving simulation is utilized to acquire the operation data of SV (subjective vehicle) under the condition of emergent deceleration of LV (leading vehicle). The kinematic model is built to characterize the law of the risk discrimination indices of SV including THW (time headway), SHW (space headway) and TTCi (the reciprocal of time to collision). The predicted results are consistent with the naturalistic driving data. Secondly, the three-dimensional distribution ' speed-spacing-TTCi ' is applied to classify the risky driving state of SV. The precarious distribution is concentrated at the area where relative velocity increased to 23–40 km/h and spacing decreased to 18–30 m. Finally, based on the reaction time and braking distance reduction, the optimal external intervention is determined to be the acousto-optic way by driving simulation. For moderate drivers, a three-level alarm of 2.94 s, 1.94 s and 1.1 s is calibrated considering different driving styles and cumulative frequency curve of reaction time. [ABSTRACT FROM AUTHOR]