襄阳市智慧停车用户分级数据

在智慧交通与城市停车管理领域，该数据用于襄阳市街道停车管理系统。系统面向停车管理部门、停车服务运营商以及停车用户，需要实时收集、存储和分析停车数据。
停车管理部门：通过分析用户在各街道的停车次数、时长、收费等数据，优化停车资源配置，规划新增停车位，制定更合理的交通政策，缓解城市停车难问题。
停车服务运营商：根据用户评级，为高等级用户提供优惠、优先停车等差异化服务，提高用户满意度和忠诚度，进而提升运营收益；同时，通过分析停车数据，优化停车收费策略。一、数据处理：对采集到的停车用户敏感信息进行加密处理，如车牌号和手机号敏感信息不被泄露 。 二、1. 停车频率分（权重 40%）计算逻辑：阶梯式分段评分，鼓励高频次停车行为。评分规则：该街道停车次数50次及以上：100分（高频用户）；该街道停车次数40-49次：80分（次高频用户）;该街道停车次数30-39次：60分（中频用户）;该街道停车次数20-29次：40分（低频用户）;该街道停车次数10-19次：20分（极低频用户）;该街道停车次数10次以下：10分（新用户或休眠用户）。2. 消费金额分（权重 60%）计算逻辑：分段线性计分 + 封顶机制，侧重激励中高消费用户，总分严格控制在 0-100 分。评分规则：累计停车费0-100元：每1元得0.3分（如50元得15分，100元得30分）；累计停车费101-300元：基础30分+超出部分×0.2分（如200元得 30+100×0.2=50分）；累计停车费301元及以：基础70分+超出部分×0.1分（如500元得 70+200×0.1=90分）；封顶100分（防止高消费过度主导评分）；公式表达：消费金额分=累计停车费×0.3（0≤累计停车费≤100）、30+(累计停车费−100)×0.2（100 <累计停车费≤300）、70+(累计停车费−300)×0.1（300<累计停车费≤900）、100（累计停车费>900）；3. 综合评分计算规则：计算逻辑：将停车频率分和消费金额分按权重加权求和，公式如下：综合评分=停车频率分×40%+消费金额分×60%。权重分配依据：消费金额分（60%）：侧重用户经济贡献，引导合理消费；停车频率分（40%）：体现用户粘性，避免 “高消费低频率” 用户过度占优。4. 用户分级规则：钻石会员：综合评分≥90分 高价值用户，高频次且高消费，享受顶级服务；白金会员：70分≤综合评分 < 90分 中高价值用户，消费或频率表现突出，为重点维护对象；黄金会员：50分≤综合评分 < 70分 中等价值用户，行为稳定，具备提升潜力；白银会员：30分≤综合评分 < 50分 基础价值用户，需通过活动提升粘性；青铜用户：综合评分<30分 低价值或新用户，需引导养成停车习惯。

This dataset is developed for the Xiangyang City Street Parking Management System, targeting the field of smart transportation and urban parking management. The system serves parking management departments, parking service operators, and parking users, and requires real-time collection, storage, and analysis of parking data.

### Usage for Stakeholders
1. **Parking Management Departments**: By analyzing parking-related data such as users' parking frequency, duration, and charging fees across various streets, they can optimize the allocation of parking resources, plan new parking spaces, formulate more rational traffic policies, and alleviate urban parking shortages.
2. **Parking Service Operators**: They can provide differentiated services such as discounts and priority parking for high-tier users based on user ratings, thereby improving user satisfaction and loyalty and increasing operating revenue; meanwhile, they can optimize parking charging strategies by analyzing parking data.

### Data Processing
Sensitive information of collected parking users must be encrypted to prevent leakage of sensitive data such as license plate numbers and mobile phone numbers.

### Scoring System
#### 1. Parking Frequency Score (Weight: 40%)
Calculation logic: Adopt stepped segmental scoring to encourage high-frequency parking behavior. Specific scoring rules are as follows:
- 100 points (High-frequency users): ≥50 parking times on a certain street
- 80 points (Sub-high-frequency users): 40-49 parking times on a certain street
- 60 points (Medium-frequency users): 30-39 parking times on a certain street
- 40 points (Low-frequency users): 20-29 parking times on a certain street
- 20 points (Very low-frequency users): 10-19 parking times on a certain street
- 10 points (New users or dormant users): <10 parking times on a certain street

#### 2. Consumption Amount Score (Weight: 60%)
Calculation logic: Adopt segmented linear scoring combined with a capping mechanism, focusing on incentivizing medium and high-consumption users, with the total score strictly controlled within the range of 0-100. Specific scoring rules are as follows:
- 0-100 yuan cumulative parking fee: 0.3 points per yuan (e.g., 50 yuan yields 15 points, 100 yuan yields 30 points)
- 101-300 yuan cumulative parking fee: 30 basic points + 0.2 points per excess yuan (e.g., 200 yuan yields 30 + 100×0.2 = 50 points)
- ≥301 yuan cumulative parking fee: 70 basic points + 0.1 points per excess yuan (e.g., 500 yuan yields 70 + 200×0.1 = 90 points)
- Capped at 100 points (to prevent excessive dominance of the score by high-consumption users)
Formal expression:
Consumption Amount Score = 0.3 × Cumulative Parking Fee (when 0 ≤ Cumulative Parking Fee ≤ 100); 30 + 0.2 × (Cumulative Parking Fee − 100) (when 100 < Cumulative Parking Fee ≤ 300); 70 + 0.1 × (Cumulative Parking Fee − 300) (when 300 < Cumulative Parking Fee ≤ 900); 100 (when Cumulative Parking Fee > 900)

#### 3. Comprehensive Score Calculation Rule
Calculation logic: Calculate the weighted sum of the parking frequency score and consumption amount score, with the formula as follows:
Comprehensive Score = Parking Frequency Score × 40% + Consumption Amount Score × 60%
Weight allocation basis: The Consumption Amount Score (60%) focuses on users' economic contribution to guide reasonable consumption; the Parking Frequency Score (40%) reflects user stickiness to avoid excessive dominance by "high-consumption, low-frequency" users.

#### 4. User Classification Rules
- **Diamond Member**: Comprehensive Score ≥90 points. High-value users with high parking frequency and high consumption, enjoying top-tier services.
- **Platinum Member**: 70 ≤ Comprehensive Score <90. Medium and high-value users with outstanding performance in consumption or parking frequency, as key maintenance targets.
- **Gold Member**: 50 ≤ Comprehensive Score <70. Medium-value users with stable behavior and development potential.
- **Silver Member**: 30 ≤ Comprehensive Score <50. Basic-value users who need to improve user stickiness through activities.
- **Bronze User**: Comprehensive Score <30. Low-value or new users who need to be guided to develop regular parking habits.

搜集汇总

背景与挑战

背景概述

该数据集为襄阳市智慧停车用户分级数据，包含1102条记录，每年更新一次，主要用于智慧交通与城市停车管理。数据通过停车频率和消费金额的综合评分对用户进行分级，支持停车管理部门和服务运营商优化资源配置和提供差异化服务。