面向异质化需求的无人驾驶电动公交接驳路径优化  

Feeder transit routing optimization of driverless electric buses for heterogeneous demands

作　　者：奇格奇 邹恺杰 邹婕 李文倩 曹靖萱 吴介豪 张文义[1,2] QI Geqi;ZOU Kaijie;ZOU Jie;LI Wenqian;CAO Jingxuan;WU Jiehao;ZHANG Wenyi(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China;Beijing Research Center of Urban Traffic Information Sensing and Service Technologies,Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]北京交通大学交通运输学院,北京100044 [2]北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室,北京100044 [3]北京交通大学北京市城市交通信息智能感知与服务工程技术研究中心,北京100044

出　　处：《清华大学学报（自然科学版）》2022年第7期1178-1185,共8页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(71961137008)。

摘　　要：在以连接地铁站点为目的的短途接驳服务中,常规公交、共享单车、小汽车因车内拥挤、环境暴露、等待时间长所造成的不舒适、不方便、不准时等问题,往往会成为乘客放弃公共交通出行的主要原因。同时,由于人群对服务质量的要求不尽相同,需求均质化假设仍难以充分考虑乘客在准时性、快捷性、舒适性等方面的需求差异。该文提出一种面向出行者异质化需求的无人驾驶电动公交接驳路径优化方法,在需求产生阶段允许用户对准时性、快捷性与舒适性等个性化指标进行选择,充分考虑个人偏好满足度对目标函数的影响,建立多轮次带多软时间窗的车辆路径规划模型,并使用禁忌搜索算法求解。通过问卷调查获取用户对各需求指标偏好的分布情况,选择北京丰台科技园地铁站及周边4 km^(2)的范围进行案例计算与结果分析,发现提出的方法相较传统方案能显著提高规划结果对出行者异质化需求的满足度。The discomfort, inconvenience, and delays caused by congestion, environmental exposure and long wait time for conventional buses, shared bicycles or taxis for short feeder trips to and from subway stations are often the main reasons for passengers to quit public transportation. The wide variety of passenger service quality requirements for punctuality, speed, and comfort are difficult to fully satisfy when assuming demand homogenization. This study presents a feeder transit routing optimization method for driverless electric buses for meeting the heterogeneous demands of travelers. In the demand generation stage, users choose personalized indicators such as punctuality, speed, and comfort so that the model can fully consider the impact of personal preferences on the objective function. A vehicle route planning model is then developed with multiple routes and multiple soft time windows with the Tabu search algorithm used to solve the problem. A questionnaire is used to survey the user preferences for each demand index for a case study of the Beijing Fengtai Science and Technology Park subway station and its surrounding area of 4 km^(2). This method significantly improves the ability of the planning results to satisfy heterogeneous commuter demands than the traditional method.

关 键 词：城市交通 异质化需求 接驳路径优化 无人驾驶电动公交 

分 类 号：U492.2[交通运输工程—交通运输规划与管理]