Please wait a minute...
浙江大学学报(工学版)
浙江大学学报(工学版)  2024, Vol. 58 Issue (1): 87-95    DOI: 10.3785/j.issn.1008-973X.2024.01.010
交通工程、土木工程     
基于自动驾驶车辆调度的停车系统收费策略优化
冯驰1,2(),梅振宇3,4,*()
1. 衢州学院 机械工程学院，浙江 衢州 324000
2. 浙江省空气动力装备技术重点实验室，浙江 衢州 324000
3. 浙江大学 智能交通研究所，浙江 杭州 310058
4. 浙江大学 平衡建筑研究中心，浙江 杭州 310058
Optimization of parking charge strategy based on dispatching autonomous vehicles
Chi FENG1,2(),Zhenyu MEI3,4,*()
1. College of Mechanical Engineering, Quzhou University, Quzhou 324000, China
2. Key Laboratory of Air-driven Equipment Technology of Zhejiang Province, Quzhou 324000, China
3. Institute of Intelligent Transportation, Zhejiang University, Hangzhou 310058, China
4. Balance Architecture Research Center, Zhejiang University, Hangzhou 310058, China
 全文: PDF(1491 KB)   HTML
摘要：

针对有人驾驶车辆与自动驾驶车辆共存的停车系统，设计基于自动驾驶车辆调度的停车系统收费策略，以提升停车系统运行效率. 该策略在停车场无可用停车泊位但存在自动驾驶车辆时向有人驾驶车辆提供自动驾驶车辆调度服务，停车系统向有人驾驶车辆收取一定调度费用后，通过在多个停车场间调度若干自动驾驶车辆，为有人驾驶车辆在其目标停车场创造可用停车泊位. 各停车场的调度费用会影响有人驾驶车辆用户的停车选择，进而影响停车系统的运行效率，构建基于智能体的停车仿真模型，采用遗传算法差异化地设置系统内各个停车场的停车调度收费方案. 仿真结果显示，采用基于自动驾驶车辆调度的差异化收费策略，可以有效地减少有人驾驶车辆用户的行驶时间、步行时间、总出行时间及行驶里程，增加停车系统营收，降低社会成本，有效地缓解停车矛盾.
关键词： 停车调度;  停车收费;  自动驾驶车辆;  基于智能体模型;  停车策略    
Abstract:

A parking charge strategy based on dispatching autonomous vehicles was proposed in order to improve the efficiency of the parking system that accommodates both human-driven vehicles and autonomous vehicles. This strategy provides autonomous vehicles dispatch service to the human-driven vehicle when there is no available parking space in the parking lot but there are autonomous vehicles. The parking system will dispatch a number of autonomous vehicles among multiple parking lots to create an available parking space for the human-driven vehicle in its target parking lot after charging a certain dispatch fee of the human-driven vehicle’s user. Since each parking lot’s dispatch fee can affect the human-driven vehicle users’ parking choices, and thus affect the operation efficiency of the parking system. An agent-based parking simulation model was constructed, and differentiated dispatch fee of every parking lot was set by the genetic algorithm. The simulation results show that the differentiated parking charge strategy based on dispatching the autonomous vehicles can significantly reduce the driving time, walking time, total travel time and mileage of the human-driven vehicle users, increase the revenue of the parking system, reduce the social cost and effectively alleviate the parking problem.
Key words: parking dispatch    parking charge    autonomous vehicle    agent-based model    parking strategy
收稿日期: 2023-04-02 出版日期: 2023-11-07
CLC:  U 491  
基金资助: 浙江省“领雁”研发攻关计划资助项目（2021C01G6233854，2022C01143）；衢州学院科研启动经费资助项目（KYQD003223001）
通讯作者: 梅振宇     E-mail: fengchi@qzc.edu.cn;meizhenyu@zju.edu.cn
作者简介: 冯驰（1995—），男，博士，从事智能交通的研究. orcid.org/0000-0003-3520-6474. E-mail： fengchi@qzc.edu.cn
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
作者相关文章　　
冯驰
梅振宇

引用本文:

冯驰,梅振宇. 基于自动驾驶车辆调度的停车系统收费策略优化[J]. 浙江大学学报(工学版), 2024, 58(1): 87-95.

Chi FENG,Zhenyu MEI. Optimization of parking charge strategy based on dispatching autonomous vehicles. Journal of ZheJiang University (Engineering Science), 2024, 58(1): 87-95.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.01.010    或    https://www.zjujournals.com/eng/CN/Y2024/V58/I1/87

图 1  有人驾驶车辆与自动驾驶车辆出行者的停车模式示意图
图 2  有人驾驶车辆的停车流程示意图
图 3  自动驾驶车辆的停车流程示意图
图 4  停车调度系统的运营流程
图 5  自动驾驶车辆调度方案的对比图
方案1 方案2
AV 原停车场 新停车场 ${l_{pp'}}$ ${l_{p'd}}$ ${l_{pd}}$ $l$ 总成本 AV 原停车场 新停车场 ${l_{pp'}} $ ${l_{p'd}} $ ${l_{pd}} $ $l $ 总成本
AV1 P1 P3 6 5 1 10 10 AV1，AV2 P1，P2 P2，P3 3，3 2，2 1，1 4，4 8
表 1  自动驾驶车辆调度方案的成本对比表
图 6  调度服务费制定的流程图
图 7  武林商圈区位示意图
图 8  武林商圈的路网拓扑图
进入点 目的地
1 2 3 4
1 150 250 150 150
2 100 250 150 100
3 150 250 200 100
4 150 250 100 100
表 2  出行分布表
参数 参数值 说明
$ {\alpha _{\text{t}}} $ 1 行驶时间权重系数
$ {\alpha _{\text{f}}} $ 1 停车费用权重系数
$ {\alpha _{\text{e}}} $ 2 AV行驶能耗权重系数
$ {\alpha _{\text{w}}} $ 3 步行时间权重系数
${{V} }$ 27.5元/h 时间价值系数
${{F} }$ 0.8元/km 单位距离能耗
${v_{\text{f}}}$ 45 km/h 路段自由流速度
${v_{\text{0}}}$ 16.1 km/h 路段最小速度
${g_{\text{a}}}$ 186 veh/km 路段临界密度
${g_{\text{b}}}$ 18.6 veh/km 路段阻塞密度
$\;\beta $ 1.25 交通流速度相关系数
表 3  基于agent模型的参数取值表
图 9  不同策略下有人驾驶车辆的平均时间指标
图 10  不同策略下有人驾驶车辆的平均行驶里程
图 11  不同策略下自动驾驶车辆的平均停车里程
图 12  不同策略下的调度服务费收入
图 13  不同策略下的社会成本
图 14  不同策略下的综合指标
1 ZHANG W, WANG K Parking futures: shared automated vehicles and parking demand reduction trajectories in Atlanta[J]. Land Use Policy, 2020, 91: 103963
doi: 10.1016/j.landusepol.2019.04.024
2 BARONE R E, GIUFFRÈ T, SINISCALCHI S M, et al Architecture for parking management in smart cities[J]. IET Intelligent Transport Systems, 2014, 8 (5): 445- 452
doi: 10.1049/iet-its.2013.0045
3 FULMAN N, BENENSON I Approximation method for estimating search times for on-street parking[J]. Transportation Science, 2021, 55 (5): 1046- 1069
doi: 10.1287/trsc.2021.1067
4 ZAKHARENKO R Self-driving cars will change cities[J]. Regional Science and Urban Economics, 2016, 61: 26- 37
doi: 10.1016/j.regsciurbeco.2016.09.003
5 HARPER C D, HENDRICKSON C T, SAMARAS C Exploring the economic, environmental, and travel implications of changes in parking choices due to driverless vehicles: an agent-based simulation approach[J]. Journal of Urban Planning and Development, 2018, 144 (4): 04018043
doi: 10.1061/(ASCE)UP.1943-5444.0000488
6 ZHANG X, LIU W, WALLER S T A network traffic assignment model for autonomous vehicles with parking choices[J]. Computer-Aided Civil and Infrastructure Engineering, 2019, 34 (12): 1100- 1118
doi: 10.1111/mice.12486
7 LIU W An equilibrium analysis of commuter parking in the era of autonomous vehicles[J]. Transportation Research Part C: Emerging Technologies, 2018, 92: 191- 207
doi: 10.1016/j.trc.2018.04.024
8 WANG S, LEVIN M W, CAVERLY R J Optimal parking management of connected autonomous vehicles: a control-theoretic approach[J]. Transportation Research Part C: Emerging Technologies, 2021, 124: 102924
doi: 10.1016/j.trc.2020.102924
9 RADVAND T, BAHRAMI S, YIN Y, et al Curbing cruising-as-substitution-for-parking in automated mobility[J]. Transportation Research Part C: Emerging Technologies, 2022, 143: 103853
doi: 10.1016/j.trc.2022.103853
10 BAHRAMI S, ROORDA M Autonomous vehicle parking policies: a case study of the City of Toronto[J]. Transportation Research Part A: Policy and Practice, 2022, 155: 283- 296
doi: 10.1016/j.tra.2021.11.003
11 MILLARD-BALL A The autonomous vehicle parking problem[J]. Transport Policy, 2019, 75: 99- 108
doi: 10.1016/j.tranpol.2019.01.003
12 YAN H, LI M, LIN X Time-dependent on-street parking planning in a connected and automated environment[J]. Transportation Research Part C: Emerging Technologies, 2022, 142: 103745
doi: 10.1016/j.trc.2022.103745
13 SAYARSHAD H Designing intelligent public parking locations for autonomous vehicles[J]. Expert Systems with Applications, 2023, 222: 119810
doi: 10.1016/j.eswa.2023.119810
14 XIE M, ZHANG X, WU Z, et al A shared parking optimization framework based on dynamic resource allocation and path planning[J]. Physica A: Statistical Mechanics and its Applications, 2023, 616: 128649
doi: 10.1016/j.physa.2023.128649
15 RAMEZANI M, NOURINEJAD M Dynamic modeling and control of taxi services in large-scale urban networks: a macroscopic approach[J]. Transportation Research Part C: Emerging Technologies, 2018, 94: 203- 219
doi: 10.1016/j.trc.2017.08.011
16 KHALID M, WANG K, ASLAM N, et al From smart parking towards autonomous valet parking: a survey, challenges and future works[J]. Journal of Network and Computer Applications, 2021, 175: 102935
doi: 10.1016/j.jnca.2020.102935
17 ZHAO C, LIAO F, LI X, et al Macroscopic modeling and dynamic control of on-street cruising-for-parking of autonomous vehicles in a multi-region urban road network[J]. Transportation Research Part C: Emerging Technologies, 2021, 128: 103176
doi: 10.1016/j.trc.2021.103176
18 ZHAO C, CAO J, ZHANG X, et al From search-for-parking to dispatch-for-parking in an era of connected and automated vehicles: a macroscopic approach[J]. Journal of Transportation Engineering, Part A: Systems, 2022, 148 (2): 04021112
doi: 10.1061/JTEPBS.0000640
19 BANSAL P, KOCKELMAN K M Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies[J]. Transportation Research Part A: Policy and Practice, 2017, 95: 49- 63
doi: 10.1016/j.tra.2016.10.013
20 SUN D J, NI X Y, ZHANG L H A discriminated release strategy for parking variable message sign display problem using agent-based simulation[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17 (1): 38- 47
doi: 10.1109/TITS.2015.2445929
21 CHIU Y C, ZHOU L, SONG H Development and calibration of the anisotropic mesoscopic simulation model for uninterrupted flow facilities[J]. Transportation Research Part B: Methodological, 2010, 44 (1): 152- 174
doi: 10.1016/j.trb.2009.06.001
22 NI X Y, SUN D J, PENG Z R An improved incremental assignment model for parking variable message sign location problem[J]. Journal of Advanced Transportation, 2015, 49 (7): 817- 828
doi: 10.1002/atr.1305
[1] 陈喜群,钱忆薇,莫栋. 电动汽车充电平台充电桩数量和价格协同优化[J]. 浙江大学学报(工学版), 2023, 57(9): 1785-1793.
[2] 王殿海,谢瑞,蔡正义. 基于最优汇集时间间隔的城市间断交通流预测[J]. 浙江大学学报(工学版), 2023, 57(8): 1607-1617.
[3] 卢凯,尹帅帅,江书妍,周志洁,李青. 考虑交织路段掉头车流的邻近交叉口信号协调控制[J]. 浙江大学学报(工学版), 2023, 57(8): 1618-1628.
[4] 吴中,梁明琰,杨海飞. 基于换道时间分布的交通流随机微分方程[J]. 浙江大学学报(工学版), 2023, 57(8): 1629-1635.
[5] 宋秀兰,董兆航,单杭冠,陆炜杰. 基于时空融合的多头注意力车辆轨迹预测[J]. 浙江大学学报(工学版), 2023, 57(8): 1636-1643.
[6] 徐标,路庆昌. 共享单车停车需求的多尺度时空影响因素[J]. 浙江大学学报(工学版), 2023, 57(2): 380-391.
[7] 孙启鹏,武智刚,曹宁博,马飞,杜婷竺. 基于风险预测的自动驾驶车辆行为决策模型[J]. 浙江大学学报(工学版), 2022, 56(9): 1761-1771.
[8] 潘义勇,管星宇. 基于分位数回归的随机优化速度跟驰模型[J]. 浙江大学学报(工学版), 2022, 56(8): 1553-1559.
[9] 侯越,韩成艳,郑鑫,邓志远. 基于时空融合图卷积的交通流数据修复方法[J]. 浙江大学学报(工学版), 2022, 56(7): 1394-1403.
[10] 俞怡,曾佳棋,王殿海. 基于数据采样方法的城市道路自由流行程时间估计[J]. 浙江大学学报(工学版), 2022, 56(6): 1241-1248.
[11] 余佳洁,季彦婕,卜卿,郑岳标. 考虑断点成本的长干线分段绿波控制方法[J]. 浙江大学学报(工学版), 2022, 56(4): 640-648.
[12] 李根,翟伟,邬岚. 基于梯度提升决策树的汇合交互作用研究[J]. 浙江大学学报(工学版), 2022, 56(4): 649-655.
[13] 陈永恒,吴场建,白乔文,熊帅,李婉宁,李浩楠. 快速路出口匝道衔接段交通特性与安全分析[J]. 浙江大学学报(工学版), 2022, 56(2): 379-387.
[14] 曹宁博,赵利英. 路段环境自动驾驶汽车通行权决策方法[J]. 浙江大学学报(工学版), 2022, 56(1): 118-127.
[15] 张楠,董红召,佘翊妮. 公交专用道条件下公交车辆轨迹的Seq2Seq预测[J]. 浙江大学学报(工学版), 2021, 55(8): 1482-1489.