Big Data 19 min read

Which Car Wins on Didi? Data‑Driven Model Selection for Ride‑Hailing

Using real‑time order and fuel‑point data from the Didi driver app, the author demonstrates a systematic, data‑driven approach to identify the most cost‑effective car models for ride‑hailing across major Chinese cities, complete with methodology, analysis, and city‑specific rankings.

Programmer DD
Programmer DD
Programmer DD
Which Car Wins on Didi? Data‑Driven Model Selection for Ride‑Hailing

Background

During a family visit for the Dragon Boat Festival, the author’s friend asked which car would be best for running Didi. Although the friend had a large budget, the author wanted to avoid recommending an expensive, quickly depreciating vehicle. After reviewing generic advice online, the author decided to collect actual Didi driver data to teach the friend how to choose a car based on evidence.

How to Get Data

The required data resides in the Didi driver app under the "Didi Fuel" section, which displays two useful metrics: real‑time orders and 30‑day repeat‑customer fuel statistics. Because the page uses a dynamic token, the author avoided reverse‑engineering the token and instead used a simple man‑in‑the‑middle tool called didi-car-rank (available on GitHub) to capture the JSON responses and save them locally.

The tool intercepts the HTTP traffic, extracts the order count and fuel‑point data for each vehicle model, and writes them to a file for further analysis.

How to Interpret Data

The author assumes that the model with the highest number of real‑time orders and the highest average fuel points is the most suitable for Didi drivers, as these metrics correlate with market share, maintenance cost, and resale value. By ranking models on both dimensions, a more balanced view of suitability emerges.

For example, in Chengdu the analysis shows that while the Changan Yidong has a high average score, its low order count indicates limited market penetration, making it a risky choice for long‑term value. Conversely, models such as Toyota Corolla, Volkswagen Lavida, and Nissan Sylphy consistently rank high on both order volume and fuel points, suggesting lower fuel consumption, maintenance costs, and better resale prospects.

Conclusion

In a data‑rich environment, quantitative analysis can dramatically reduce uncertainty when selecting a vehicle for ride‑hailing. However, raw data often contains noise; cross‑checking with additional sources is advisable. The methodology presented can be applied to any city, adjusting for local policies, vehicle‑type restrictions, and incentives.

Appendix: Popular Car Rankings by City

Beijing

车型订单数量排名:
+------+--------------+------------+
| 排名 | 车型         | 实时订单数 |
+------+--------------+------------+
| 1    | 大众朗逸     | 126        |
| 2    | 日产阳光     | 116        |
| 3    | 大众新捷达   | 113        |
| ...  | ...          | ...        |
+------+--------------+------------+

车型加油积分排名:
+------+--------------+----------+----------+
| 排名 | 车型         | 加油积分 | 平均积分 |
+------+--------------+----------+----------+
| 1    | 出租车       | 17804    | N/A      |
| 2    | 大众朗逸     | 6547     | 51.96    |
| 3    | 日产阳光     | 4305     | 37.11    |
| ...  | ...          | ...      | ...      |
+------+--------------+----------+----------+

Shanghai

车型订单数量排名:
+------+---------------+------------+
| 排名 | 车型          | 实时订单数 |
+------+---------------+------------+
| 1    | 比亚迪秦      | 37         |
| 2    | 荣威550       | 37         |
| 3    | 荣威e550      | 16         |
| ...  | ...           | ...        |
+------+---------------+------------+

车型加油积分排名:
+------+---------------+----------+----------+
| 排名 | 车型          | 加油积分 | 平均积分 |
+------+---------------+----------+----------+
| 1    | 荣威550       | 4668     | 126.16   |
| 2    | 比亚迪秦      | 1940     | 52.43    |
| 3    | 荣威e550      | 1930     | 120.62   |
| ...  | ...           | ...      | ...      |
+------+---------------+----------+----------+

Guangzhou

车型订单数量排名:
+------+--------------+------------+
| 排名 | 车型         | 实时订单数 |
+------+--------------+------------+
| 1    | 日产轩逸     | 88         |
| 2    | 丰田卡罗拉   | 79         |
| 3    | 比亚迪秦     | 77         |
| ...  | ...          | ...        |
+------+--------------+------------+

车型加油积分排名:
+------+--------------+----------+----------+
| 排名 | 车型         | 加油积分 | 平均积分 |
+------+--------------+----------+----------+
| 1    | 比亚迪秦     | 3702     | 48.08    |
| 2    | 日产轩逸     | 3465     | 39.38    |
| 3    | 出租车       | 2891     | N/A      |
| ...  | ...          | ...      | ...      |
+------+--------------+----------+----------+

Shenzhen

车型订单数量排名:
+------+----------------+------------+
| 排名 | 车型           | 实时订单数 |
+------+----------------+------------+
| 1    | 丰田卡罗拉     | 92         |
| 2    | 日产轩逸       | 70         |
| 3    | 福特麦柯斯     | 39         |
| ...  | ...            | ...        |
+------+----------------+------------+

车型加油积分排名:
+------+----------------+----------+----------+
| 排名 | 车型           | 加油积分 | 平均积分 |
+------+----------------+----------+----------+
| 1    | 日产轩逸       | 5569     | 79.56    |
| 2    | 丰田卡罗拉     | 4988     | 54.22    |
| 3    | 比亚迪秦       | 3269     | 88.35    |
| ...  | ...            | ...      | ...      |
+------+----------------+----------+----------+

Hangzhou

车型订单数量排名:
+------+--------------+------------+
| 排名 | 车型         | 实时订单数 |
+------+--------------+------------+
| 1    | 比亚迪秦     | 46         |
| 2    | 别克凯越     | 18         |
| 3    | 大众朗逸     | 14         |
| ...  | ...          | ...        |
+------+--------------+------------+

车型加油积分排名:
+------+--------------+----------+----------+
| 排名 | 车型         | 加油积分 | 平均积分 |
+------+--------------+----------+----------+
| 1    | 出租车       | 4768     | N/A      |
| 2    | 比亚迪秦     | 3290     | 71.52    |
| 3    | 日产轩逸     | 1345     | 96.07    |
| ...  | ...          | ...      | ...      |
+------+--------------+----------+----------+

Chengdu

车型订单数量排名:
+------+--------------+------------+
| 排名 | 车型         | 实时订单数 |
+------+--------------+------------+
| 1    | 大众新捷达   | 52         |
| 2    | 斯柯达明锐   | 50         |
| 3    | 大众宝来     | 46         |
| ...  | ...          | ...        |
+------+--------------+------------+

车型加油积分排名:
+------+--------------+----------+----------+
| 排名 | 车型         | 加油积分 | 平均积分 |
+------+--------------+----------+----------+
| 1    | 丰田卡罗拉   | 1613     | 41.36    |
| 2    | 大众朗逸     | 1504     | 35.81    |
| 3    | 斯柯达明锐   | 1452     | 29.04    |
| ...  | ...          | ...      | ...      |
+------+--------------+----------+----------+

Chongqing

车型订单数量排名:
+------+-------------+------------+
| 排名 | 车型        | 实时订单数 |
+------+-------------+------------+
| 1    | 标致408     | 19         |
| 2    | 本田凌派    | 16         |
| 3    | 长安逸动    | 16         |
| ...  | ...         | ...        |
+------+-------------+------------+

车型加油积分排名:
+------+--------------+----------+----------+
| 排名 | 车型         | 加油积分 | 平均积分 |
+------+--------------+----------+----------+
| 1    | 长安逸动     | 548      | 34.25    |
| 2    | 本田凌派     | 427      | 26.69    |
| 3    | 日产天籁     | 379      | 27.07    |
| ...  | ...          | ...      | ...      |
+------+--------------+----------+----------+
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data analysisDidiRide Hailingcar selectionvehicle depreciation
Programmer DD
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Programmer DD

A tinkering programmer and author of "Spring Cloud Microservices in Action"

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