Highlights Propose an advanced-curve speed warning system (A-CSW) to address the in-curve speed incompliance issue due to one-time warning nature. A-CSW provides guided speed warning through driving the entire course of horizontal curves via CV enabled DSRC based V2I commutation. A mixed linear model with random effects is developed to capture individuals’ driving behavior. A-CSW is adaptive to the vehicle’s real-time speed and location, updating curve advisory speed if pavement friction is changed. A-CSW significantly enhances male drivers’ speed compliance when compared to the existing CV-based curve warning system.

    Abstract Connected Vehicles (CV) technology has been used to address safety issues on highway horizontal curves. Existing curve warning systems are either using curve warning signs or providing drivers with an in-vehicle curve warning message in advance, allowing drivers to adjust their speed prior to the vehicle entering the curve. In practice, drivers might be compliant before entering the curve but may pick up the speed in the curve. Therefore, it remains a problem that existing curve warning systems are not able to guide drivers by providing necessary speed warnings through the entire course of approaching, entering, navigating, and leaving horizontal curves. Therefore, the objective of this study is to improve curve speed compliance by proposing a guidance-oriented Advanced Curve Speed Warning system (Advanced-CSW) with a focus on providing guided curve speed messages throughout the horizontal curves. The Advanced-CSW system is based on Dedicated Short-Range Communication (DSRC) enabling vehicle-infrastructure (V2I) communication. Anytime the vehicle is speeding, the guided message will be displayed until the vehicle’s speed is within compliant range. Drivers who use the Advanced-CSW can receive multiple guided messages from the in-vehicle heads-up display through the entire course of navigating through horizontal curves. Thirty participants are recruited to perform the driving experiment on the simulator of driving through a series of horizontal curves under various geometric, roadway and traffic conditions. These conditions include different curve severity, illumination, and pavement wetness levels. The Advanced-CSW system’s performance was evaluated in terms of the speed difference, which measures the gap between the in-curve mean speed and curve advisory speed. The results were compared with the performance of speed difference by driving with CSW or CSO through the entire curve. The experiment data was modeled using the mixed linear model with random effects, which includes the individual’s driving behavior. In summary, when male drivers navigate through the horizontal curves under different curve speed warning systems, their speed compliance is significantly increased with continuous and guided messages provided in comparison with the speed compliance under the one-time curve speed warning message and the curve sign only. Female drivers improve their speed compliance in the curve by using curve signs only comparing to using one-time curve speed warning message or continuous guided curve speed warning messages. Also, male drivers’ speed differences by using the guided system are significantly reduced by 6.53∼7.68 mi/h compared to driving with curve signs only or one-time curve speed warning message. In addition, there is also a speed reduction of 1.81 mi/h if male drivers receiving continuous guided messages in the curve during the daytime than during the nighttime. The proposed adaptive system based on that is adaptive to the vehicle’s real-time speed and location by providing a new direction in designing effective curve warning systems. The speed-guided messages through the entire course of approaching, entering, navigating, and leaving horizontal curves can solve the current issue of speed incompliance by using the existing curve warning systems.


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    Title :

    Guidance-oriented advanced curve speed warning system in a connected vehicle environment


    Contributors:
    Wang, Song (author) / Wang, Yi (author) / Zheng, Qi (author) / Li, Zhixia (author)


    Publication date :

    2020-09-21




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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