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Field tests of a dynamic green driving strategy based on inter- vehicle communication

机译：基于车辆间通信的动态绿色驾驶策略的现场测试

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摘要

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles' speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.
机译：本文介绍了关于基于车辆间通信（IVC）的算法绿色驾驶策略在走走停停交通中的环境效益的现场测试的设计和结果，该研究在Yang和Jin（2014）中提出。绿色驾驶策略可动态计算配备IVC设备的车辆的建议速度限制，以平滑其速度曲线并减少其排放和燃料消耗。对于现场测试，我们开发了基于智能手机的IVC系统，该系统通过GPS和嵌入在智能手机中的加速度传感器收集车辆的速度和位置，并通过专门设计的智能手机应用程序，中央服务器和4G来实现车辆之间的通信。蜂窝网络。在慢速或快速停走交通条件下，在不间断的环路上进行了六个现场测试。我们比较了三种替代方案的性能：无绿色驾驶，启发式绿色驾驶和基于IVC的算法绿色驾驶。结果表明，启发式绿色驾驶比没有绿色驾驶具有更好的平滑性和环境效果，但是基于IVC的算法绿色驾驶均优于两者。将来，我们对更现实的交通条件下的现场测试感兴趣。

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