Implementation of Predictive Adaptive Cruise Control Strategy Based on ADAS Map

Author:

Qian Guoping1,Lu Zhenghua1,Tian Juntao1,Liu Lianfang1,Xi Chong1,Zhou Xiaoying1

Affiliation:

1. Foton Motors: Beiqi Foton Motor Co Ltd.

Abstract

<div class="section abstract"><div class="htmlview paragraph">Heavy vehicles are major fuel consumers in road transportation, and the traditional way to reduce fuel consumption is to reduce weight, resistance, improve mechanical transmission efficiency, and improve engine thermal efficiency. However, European heavy-duty truck companies took the lead in realizing predictive cruise control (PCC) technology on the basis of cruise through intelligent network technology, based on ADAS maps, and achieved good fuel saving effects. In this paper, by studying the fuel consumption characteristics of trucks, designing the dynamic parameters of the load and whole vehicle, the predictive adaptive cruise control (PACC) technology is realized based on the predictive cruise strategy, and the statistics of fuel saving rate under different cruise ratio conditions are analyzed through the big data platform.</div></div>

Publisher

SAE International

Reference16 articles.

1. Keqiang , L. , Yifan , D. , Shengbo , L. et al. Development Status and Trend of Intelligent Connected Vehicle (ICV) Technology Journal of Automotive Safety and Energy 8 1 2017 1 14

2. Gauss. Scania Launches Proactive Predictive Cruise Control-A New Low Fuel Consumption Cruise Control System Using GPS Data Transpo World (Transportation Vehicles) 1 2012 105 107

3. Hongwei Peng , Dongdong Liu Development and Application of a Predictive Fuel-Saving Cruise System for Commercial Vehicles Intelligent Connected Vehicles 2022

4. Wang , Y. , Xingkun , L. , Penglei , Z. et al. Real-Time Optimization Algorithm of Truck Predictive Cruise Based on ADAS Map Automotive Engineering 42 10 2020 1335 1339

5. Qingsong , Z. , Junwei , L. , Xuezi , C. et al. Predictive Cruise Strategy of Trucks Based on High-Precision Electronic Map Agricultural Equipment and Vehicle Engineering 59 8 2021 20 25

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