Collaborative Optimization Model of Truck Speed and Signal
Timing Based on Minimum Fuel Consumption

doi:10.16097/j.cnki.1009-6744.2023.02.009

Abstract

Abstract: This paper proposes an integer nonlinear programming model for collaborative optimization of truck speed and signal timing to reduce the fuel consumption caused by frequent stopping and start of trucks at signalized intersections. The objective function of the model was the truck travel fuel consumption based on the Virginia Tech Comprehensive Power-based Fuel Consumption Model. Truck travel fuel consumption included road fuel consumption, intersection stopping fuel consumption and speed recovery fuel consumption. The road section was divided into acceleration area, uniform speed area and deceleration area. Considering the acceleration process of the multi-gear gradient of the truck, the upper and lower limits of acceleration and shift time were defined for each gear of the truck. The queue dissipation process at the downstream intersection was analyzed using the traffic wave theory, and the spacetime trajectory constraint of the truck was considered. The optimization variables include acceleration at each gear of the truck, acceleration time, uniform speed, uniform driving time, deceleration, deceleration time, intersection green light extension time and red light early return time. The example analysis included 10 typical truck arrival situations generated at uniform intervals. The results show that compared with no speed guidance, the fuel consumption from the proposed model is reduced by 29.9 % at the maximum, 3.9 % at minimum, and 13.7 % on average. The number of truck stops is reduced by 71.4 %, and the total stopping time is reduced by 174 seconds (89.2 %). The model effectively reduces the fuel consumption and number of stops for trucks crossing the intersections.

Key words: intelligent transportation, collaborative optimization, nonlinear programming, signal timing, truck fuel consumption, speed guidance

摘要： 为解决货车受信号灯影响频繁停和启而造成油耗过高的问题，本文建立货车车速与信号配时协同优化的整数非线性规划模型。模型的目标函数是基于弗吉尼亚理工大学综合油耗模型的货车行程油耗，包括路段行驶油耗、交叉口停车油耗以及速度恢复油耗。将路段划分为加速区、匀速区和减速区；考虑货车多档渐变的加速过程，货车每个挡位设定加速度以及换挡时间的上下限；采用交通波理论分析下游路口的排队消散过程，建立货车的时空轨迹约束。优化变量包括货车各挡位加速度、加速时间、匀速区速度、匀速行驶时间、减速度、减速时间、交叉口绿灯延长时间和红灯早断时间。以均匀间隔生成的10种货车到达情形为例进行分析，结果表明：与无车速引导相比，本模型行程油耗最高减少29.9%，最低减少 3.9%，平均减少 13.7%；货车停车次数减少5次(降低71.4%)，总停车时间减少174 s(降低89.2%)。模型有效减少了货车通过交叉口的燃油消耗和停车次数。

关键词: 智能交通, 协同优化, 非线性规划, 信号配时, 货车油耗, 车速引导

CLC Number:

U491

ZHANG Peng, GU Yun-xiang, SUN Chao, LI Wen-quan. Collaborative Optimization Model of Truck Speed and Signal Timing Based on Minimum Fuel Consumption[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(2): 84-91.

张鹏, 顾云翔, 孙超, 李文权. 基于最小油耗的货车车速与信号配时协同优化模型[J]. 交通运输系统工程与信息, 2023, 23(2): 84-91.

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Collaborative Optimization Model of Truck Speed and Signal Timing Based on Minimum Fuel Consumption

基于最小油耗的货车车速与信号配时协同优化模型

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