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
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.
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.
Fig.1Parking patterns of human-driven and autonomous vehicle users
Fig.2Parking flow diagram of human-driven vehicle
Fig.3Parking flow diagram of autonomous vehicle
Fig.4Operation process of AV dispatch system
Fig.5Comparison of autonomous vehicles dispatch schemes
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
Tab.1Cost comparison of autonomous vehicles dispatch schemes
Fig.6Flow chart of dispatch service fee formulation
Fig.7Location of Wulin Business District, Hangzhou
Fig.8Road network of Wulin Business District
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
Tab.2Travel distribution
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
Tab.3Value of parameters of agent-based model
Fig.9Average time of human-driven vehicles under different strategies
Fig.10Average travel mileage of human-driven vehicles under different strategies
Fig.11Average parking mileage of autonomous vehicles under different strategies
Fig.12Dispatch service income under different strategies
Fig.13Social cost under different strategies
Fig.14Comprehensive index under different strategies
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