Abstract

This paper develops a novel anticipatory Variable Speed Limit (VSL) control strategy that incorporates driver behavior based on trajectory data from probe vehicles. In particular, the research examines how the speed limit controls can be coordinated and optimized to reduce lane changing and overall braking, thus to achieve greater traffic throughput, safety, and sustainability. Driver behavior, such as acceleration/deceleration and lane changing, as reflected in individual trajectory data from GPS enabled probe vehicles are crucial for early detection of shockwave formation and proactive selection of speed limits; and consequently delay, or even eliminate breakdown formation. The core of this approach is the incorporation of a lane changing model which provides a more robust integrated speed limit selection and shockwave detection framework than the one we have developed in an earlier paper. The control principle is formulated in a generic fashion that finds the optimal speed limit control variables for either separate or simultaneous reduction of travel time, crash rates, and fuel consumption over a prediction horizon. The findings from the paper suggested that the VSL strategy was able to result in fewer lane changing rate (LCR) compared to the No-VSL case. Also, the developed algorithm was able to produce higher frequency of lower acceleration and deceleration rates than the No-VSL case, which indicated a smoother acceleration and deceleration pattern that corresponded to lower emission and fuel consumption. The performance of the algorithm was also examined under different probe penetration rates and congestion levels to identify the % of probe needed to achieve simultaneous mobility, safety, and environmental objectives.

摘要

本文开发了一种新颖的预期可变速度限制 (VSL) 控制策略，该策略结合了基于探测车辆轨迹数据的驾驶员行为。该研究特别研究了如何协调和优化限速控制以减少换道和整体制动，从而实现更大的交通吞吐量、安全性和可持续性。驾驶员行为，例如加速/减速和变道，反映在来自启用 GPS 的探测车辆的个人轨迹数据中，对于早期检测冲击波形成和主动选择速度限制至关重要；从而延迟甚至消除击穿的形成。这种方法的核心是结合了车道变换模型，该模型提供了比我们在早期论文中开发的更强大的集成速度限制选择和冲击波检测框架。控制原理以通用方式制定，为单独或同时减少行驶时间、碰撞率和预测范围内的燃料消耗找到最佳速度限制控制变量。该论文的研究结果表明，与 No-VSL 情况相比，VSL 策略能够降低换道率 (LCR)。此外，与 No-VSL 情况相比，开发的算法能够产生更高频率的更低加速和减速率，这表明更平稳的加速和减速模式对应于更低的排放和燃料消耗。