revolutionize ride sharing: the global optimization through D1 platform

global optimization through the cloud

topic: cloud optimization through the D1 platform brings the future of efficiency

topic: d1 platform is a cloud optimization solution that feautres at efficiency

ourdesign is the application of d1 platform

D1 platform is a cloud based solution

Revolutionize the ridesharing experience and business through cloud based solution (is only a background)

Our background: cloud based solutions are available and has the potential to revolutionize xxxx (in system efficiency and user experience)

Our design: update the old design to stress ride sharing expeinrices and maximize the potential

Our design: compared to the old ones, we focued on user experience?

The challenge in B2C/2B business mode and the design applications

Topic: the future of ridesharing business and experiences through cloud based solutions

Topic: The future of the ridesharing business and experiences through cloud-based solutions

The challenge: the unique design challenge at the intersection of two different business modal: the need of the users, and the need of system efficiency

(Introduce two different business modal in small texts, briefly talks about customer research)

Our solution: the D1 platform, and our application of D1 platform (which is our design - here gives the technology overview and our design overview, choose one image to introduce our 4 features of designs, give external link to technology introductions)

(Compare our design with old ones in small windows, could be static images, briefly talks about design considerations behind changes)

Design features and use cases in details: explain how this is connected to our strategic business goals and reflections

Search for charging stations (old): go to main menu, open navigation, search charging, select destination, start navigation

Search for charging stations(new): switching to show chargers mode on the left, start navigation

taking order, and charging scenario.

The survey insights guided the design changes, backed with cloud computing, help drivers better decide orders and charging schedules. In the similar pricing market, on achieving a near 350km range and fast charging form 20% to 80% in 30min in real world sets up the satisfaction threshhold, The strategic enhancement over charging experineice in the software level set D1 unique and competitive among ride hailign vehicles.

(还是太长了）

To further implement efficient operation on HMI desiwe adopded a scnario-based approach that increase HMI efficiency and usability.

Re-organize relevant features specific for ride hailing, visually prioritize information in the sequence of: assignment system = navigation info > driver/passenger personal info, car settings, media, other app. the new desgin flatten the layered structure of in-widgets app and reduce app switching in decision making when taking orders and finding chargers. (give a brief introdcution over the screen accessibility)

A un-tampered data from the connected vehicle provides informaytion on driver-specific battery usage. this data is transmitted to the cloud and get analyzed, and get battery configured with a new parameter which is tailored to the current battery condition. In user expereinice, the continuous monitoring enables the accurate predictions and sets the bases to distribute orders always within range.

In a addition, the case-specific configuration also allow vehicle automatic switching between gental, standard and fast charging modes, connected with Didi’s in-network charging stations, thus create better charging schedule recommendations for battery longevity. In user expernice, this enables drivers to be suggested best charging hours and locations, and received guranteed times and prices upon reservation.

in order assignment and charging suggestion are a combined result from 982algorighs in battery evaluation, batch matching and traffic prediction. The bloud-based battery management enables these improvments in driver’s expernieces.

D1’s smart suggestions in order assignment and charging suggestion are a combined result by algorighs in battery evaluation, batch matching and traffic prediction. It not only assist driver in making deicions, but also hlep effectively manages the power network, and ride demand help the entire rideshare community.

D1’s smart recommendation algorithm uses big data ( pull from south asia,

to predict current ride demands. It also optimizes based on a analysis of recent orders (within last 2 mins within km ). This approach reduces minimal waiting times for both drivers and passengers across the system, while also accommodating traffic fluctuations throughout the day, standard diviation duoshao mins.

Meanwhile, EVs connected to the cloud network demonstrate the inherent advantages of battery interconnection. This technology enables the platform to not only monitor ride demand saturation through driver’s app usage but also to optimize battery performance via real-time battery monitoring. 20% Usually, EV batteries degrade over time at rate of , leading to a decreased overall capacity, increased consumption rates of , and slower charging speed. These issues impact drivers' decisions on charging times, reducing operational efficiency. Cloud-based battery management addresses these challenges by using real-time data pull source whin area or model more accurately reflects the current battery conditions by numbers of aspects. This allows for targeted adjustments to battery parameters based on individual driving habits, such as..

A prime example is the adaptive switching of charging modes. EVs have built-in charging systems that can adjust between fast, standard, and gentle charging presets. This system benefits most when continuously monitoring to determine the most suitable charging rhythm to prolong battery life, slow degration by how much

Furthermore, connected batteries can communicate seamlessly with Didi’s in-network chargers, greatly improving charging reliability and grid transmission efficiency. Drivers can view charging station information such as and reserve spots through the car client, allowing drivers to know the cost and time in how many time advance. The grid can also get prepared for energy transmission thus benefit the whole EV ridesharing community.

across the entire D1 fleet. The broader dataset allows for more precise and effective algorithms for battery predictions. Furthermore, connected batteries constantly interact with Didi's in-network chargers, enabling drivers to reserve and guarantee charging spots 24 hours ahead. While the battery adjusts the electricity current curves and the grid power network prepares for the energy transmission, it prolongs the battery life up to 20% for the single vehicle, and increases the grid transmission efficiency that benefits the whole ride-sharing community.

Compared to the built-in battery management systems of other electric vehicles, the D1's cloud-based battery solution can gather data types at a rate ten times higher, monitor and store data throughout the entire battery lifecycle, and analyze data across all D1 vehicles. This extensive dataset enables the development of more accurate and effective battery prediction algorithms. Additionally, the connected batteries actively communicate with Didi's network of chargers, allowing drivers to book and secure charging spots 24 hours in advance. As the battery optimizes the electricity current curves and the power grid readies for energy transfer, it extends the battery life by up to 20% per vehicle and enhances grid transmission efficiency, benefiting the entire ride-sharing community.

thus drivers can reserve charging spots which ensure the cost and time 24h ahead, while the battery and charging station plan ahead, all in an effort to prolong the battery life up to 20% and improve safer and faster charging experience.

D1's smart recommendation algorithm uses big data to predict ride demands and optimizes order distribution. The system builds upon a batch matching strategy, which predicts the density of supply and demand in the future 2 seconds within a 1.5-2km range, and creates an intelligent match based on global optimization. This intelligent assignment improves order response rate by 20%, and it accommodates traffic fluctuations in peak times, allowing more than 90% order response rates throughout the day.

As an EV fleet connected to the same network, D1 also benefits from centralized management over the battery. Usually, the EV battery cannot achieve its expected driving range due to the use of air conditioning, the friction coefficient of the road, weather, wind, etc., which can affect its range by up to 50%. Inaccurate battery prediction results in at least a 5% increase in ride-hailing matching failures, while 85% of Chinese ride-hailing vehicles are EVs (as of 2023).

The research towards Didi registered EV drivers helped the team identify key improvements and centralize the focus on operation efficiency.

According to the survey insights, efficient operation stands out among all driver needs, and range anxiety (90%) becomes a main barrier for those considering leasing or buying D1. For full-time drivers who work 8 to 13 hours daily, the long-distance dispatch, unpredictable charger availability, and inaccurate battery predictions add difficulty to operating ride-hailing on EV.

To strategically solve the problem, Didi adopts advanced algorithms for order and charging management. The HMI design takes a user-centered approach, supporting the change with usability and efficiency improvements under the driver's working scenarios.

project name: improving hmi for efficient rid-hailing and charging: innovations in the D1 EV

Project introduction:

the D1 EV, born from a collaboration between Didi and BYD, is revolutioninzing the ride-hailing industry. This project is an improved HMI design, aimed at bosting operational efficiency and addressing commone challenges faced by drivers. This article delves into the cutting-edge features and technologies that make the D1 a game-changer in the EV ride hailing market.

[pic D1]

First section heading: Key design features

Real-time demand view

Drivers can easily toggle on the heatmap view on the dashboard. It provides real-time demand visualization using color gradients.

One best order

A recommended order will be highlighted once the driver goes online. This suggestion is calculated based on current demand and predicted traffic. It displays essential earnings and battery consumption for ride-hailing drivers.

No out-of-range orders

The system takes into account the remaining mileage and filters out out-of-range orders. This helps drivers manage their charging anxieties and reduces the order cancellation rate.

Reserve a charging spot

Drivers can easily access the charging tab and reserve a spot at in-network charging stations. This reduces their idle time finding available fast chargers.

Second section heading: Survey Insights: Range anxiety is the top one issue for EV drivers

Research on Didi-registered EV drivers has enabled the team to identify key improvements and focus centrally on operational efficiency.

According to the survey insights, efficient operation stands out among all driver needs, and range anxiety (90%) becomes a main barrier for those considering leasing or buying D1. Full-time drivers, who work between 8 to 13 hours daily, face challenges such as long-distance dispatches, unpredictable charger availability, and inaccurate battery predictions, making it difficult to operate EVs effectively in ride-hailing.

To strategically address these issues, Didi has implemented advanced algorithms for managing orders and charging. The HMI design adopts a user-centered approach, supporting these changes with usability and efficiency enhancements tailored to the drivers' working scenarios.

We streamline the system structure and collect essential drivers’ tools from system widgets into one mega working scene.

Homescreen (old) [with picture]

Display working information on widget on homepage.

Driver's Scene (new) [with picture]

Display working information only under working scene. Improve privacy, reduce system complexity

Driver's app (old) [with picture]

Displays shortcuts that redirect to functions.

Driver's scene (new) [with picture]

Taking orders, choosing tasks, viewing demands, deciding routes, can be completed on one screen without app switching.

Arrive at Pickup Location (Old) [with picture]

Displays order-related information in a navigation setting.

Arrive at Pickup Location (New) [with picture]

Prevent multiple threads of information while driving. Prioritize passenger-related actions when approaching the destination.

Third section heading: Tech behind design

D1's smart recommendation algorithm utilizes big data to predict ride demands and optimize order distribution. The system is based on a batch matching strategy, which forecasts the density of supply and demand within the next two seconds in a 1.5-2km range, and facilitates an intelligent match through global optimization. This intelligent assignment boosts the order response rate by 20% and adapts to traffic fluctuations during peak times, ensuring more than 90% of orders are responded to throughout the day.

As part of an EV fleet connected to the same network, D1 also benefits from centralized battery management. Typically, an EV's battery may not reach its expected driving range due to factors like air conditioning use, road friction, weather conditions, and wind, which can reduce its range by up to 50%. Inaccurate battery predictions lead to at least a 5% increase in ride-hailing matching failures, while 85% of Chinese ride-hailing vehicles are EVs (as of 2023).

Compared to the built-in battery management systems of other EVs, the D1's cloud-based battery solution can gather data types at a rate ten times higher, monitor and store data throughout the entire battery lifecycle, and analyze data across all D1 vehicles. This extensive dataset enables the development of more accurate and effective battery prediction algorithms. Additionally, the connected batteries actively communicate with Didi's network of chargers, allowing drivers to book and secure charging spots 24 hours in advance. As the battery optimizes the electricity current curves and the power grid readies for energy transfer, it extends the battery life by up to 20% per vehicle and enhances grid transmission efficiency, benefiting the entire ride-sharing community.

Research on Didi-registered EV drivers has enabled the team to identify key improvements and focus centrally on operational efficiency.

According to the survey insights, efficient operation stands out among all driver needs, and range anxiety (90%) becomes a main barrier for those considering leasing or buying D1. Full-time drivers, who work between 8 to 13 hours daily, face challenges such as long-distance dispatches, unpredictable charger availability, and inaccurate battery predictions, making it difficult to operate EVs effectively in ride-hailing.

To strategically address these issues, Didi has implemented advanced algorithms for managing orders and charging. The HMI design adopts a user-centered approach, supporting these changes with usability and efficiency enhancements tailored to the drivers' working scenarios.