Shuttling track system for simultaneously loading and traveling private cars and operation method

Abstract

The invention belongs to the technical field of urban traffic carbon reduction and intensive carrying, and particularly discloses a co-loading and co-traveling private car shuttle rail system and an operation method.The system comprises a co-loading and co-traveling shuttle rail unit which provides a high-speed and stable carrying foundation for private cars; the intelligent butt joint vehicle carrying tray unit realizes rapid and accurate butt joint and separation of a private car and a double-rail track; the green electricity driving carbon reduction unit provides electric driving for the simultaneous-loading and simultaneous-traveling shuttle track unit and the intelligent butt joint vehicle carrying tray unit, and carbon emission of the simultaneous-loading and simultaneous-traveling private car shuttle track system is reduced through a green electricity access scheme. And the full-process scheduling control unit dynamically schedules the operation of the intelligent docking vehicle carrying tray unit based on a traffic flow prediction model, and monitors the operation state and safety of the whole co-loading co-traveling private car shuttle track system in real time. The problems that the time cost is increased, the instant car using requirement cannot be met, the speed and carbon reduction are unbalanced and the adaptability is poor due to the fact that the current private car cross-city travel adopts a man-car separation mode are solved.

Description

Technical Field

[0001] This invention belongs to the field of urban transportation carbon reduction and intensive transportation technology, specifically involving a private car shuttle track system and operation method. Background Technology

[0002] With the acceleration of urbanization, the demand for cross-city travel by private car has surged, but traditional travel modes and the existing transportation system have three major problems that cannot be ignored: 1. Cross-city commuting is inefficient and time-consuming, and even during off-peak hours, it cannot meet the demand for efficient commuting, resulting in widespread time waste.

[0003] 2. High carbon emission intensity hinders green development. The energy consumption of traditional fuel-powered private cars increases significantly under congested conditions: According to statistics, the fuel consumption of private cars during peak congestion periods is about 8.5L / 100km, and the carbon emission factor of each liter of gasoline is 2.3kg CO2 / L.

[0004] Compared with existing electric drive solutions: Although the private car transport lines piloted in some cities are electric, they require separation of people and vehicles (drivers take the high-speed rail and vehicles are transported separately), which generates additional carbon emissions from the high-speed rail (about 0.03 kg CO2 / person·km). In addition, the pick-up / drop-off process adds 20-30 minutes of time, and the overall carbon reduction rate is only 35%, which cannot balance efficiency and carbon reduction.

[0005] 3. Significant driver fatigue, poor comfort and safety. Long driving hours and congested traffic conditions lead to a surge in driver fatigue: most drivers who spend more than 60 minutes crossing cities experience symptoms such as eye fatigue and muscle tension, and "irritability caused by congestion"; during traditional self-driving, road bumps (average amplitude 0.8-1.2mm) and sudden braking further reduce driving comfort, and traffic accidents caused by fatigued driving account for about 40% of the total number of cross-city accidents.

[0006] Current solutions for improving cross-city travel for private cars have three main flaws: Limitations of the driver-vehicle separation model: Existing rail transport systems (such as dedicated railway freight lines and dedicated vehicle transport trains) require the separation of drivers from vehicles, necessitating additional planning for drivers' round-trip transportation, increasing time costs (an average increase of 40-60 minutes), and failing to meet immediate vehicle usage needs (such as business trips and family outings). Imbalance between speed and carbon reduction: Although urban light rail, subway and other public transportation are low-carbon, they are only for passenger transport and cannot carry private cars. Moreover, the speed is mostly 60-80km / h, and the efficiency of cross-city travel is lower than that of traditional self-driving during off-peak hours. Poor adaptability: Existing rail systems are mostly designed for standardized freight vehicles and do not take into account the diversity of private car sizes (length 3.8-5.2m, width 1.7-2.1m), resulting in low docking efficiency (entry / exit time exceeds 5 minutes) and inability to adapt to the high traffic flow scenario of the ring expressway.

[0007] Therefore, there is an urgent need for a dedicated rail system that can enable "drivers and private cars to travel together", while also achieving high speed, high efficiency, significant carbon reduction, and high comfort, in order to solve the aforementioned technical pain points. Summary of the Invention

[0008] The purpose of this invention is to address the problems of the current "person-vehicle separation" mode for cross-city travel by private cars, which increases time costs, fails to meet the demand for "instant car use," results in an imbalance between speed and carbon reduction, and has poor adaptability to existing rail systems. This invention proposes a shuttle rail system and operation method for private cars traveling together.

[0009] The technical solution of the present invention is as follows: Firstly, a shared-carriage shuttle track system for private vehicles includes a shared-carriage shuttle track unit, an intelligent docking vehicle pallet unit, a green electric drive carbon reduction unit, and a full-process scheduling and control unit. The same-carrying shuttle rail unit includes a double-track rail laid along the central median or green belts on both sides of the city's ring expressway, as well as multiple hub stations, to provide a high-speed and stable transportation base for private cars. The intelligent docking vehicle pallet unit includes an intelligent vehicle pallet, which is used to enable the rapid and precise docking and separation of private cars from the dual-track system, and to transport the private cars to the target hub station. The green electricity-driven carbon reduction unit is used to provide electric drive for the same-carrying shuttle track unit and the intelligent docking vehicle pallet unit, and to reduce carbon emissions of the same-carrying private vehicle shuttle track system through a green electricity access scheme. The full-process scheduling and control unit is used to dynamically schedule the operation of the intelligent docking vehicle pallet unit based on the traffic flow prediction model, and to monitor the operation status and safety of the entire shared private vehicle shuttle track system in real time.

[0010] Preferably, the double-track gauge is 2.4m, the double-track material is U75V heavy steel rail, and the double-track foundation is "reinforced concrete cap + pile foundation".

[0011] Preferably, the hub stations are located at the four entrances and exits of the ring expressway in the east, west, north, and south directions; each hub station is equipped with multiple inbound lanes and multiple outbound lanes.

[0012] Preferably, the intelligent vehicle carrier tray adopts a lightweight aluminum alloy design; the surface of the intelligent vehicle carrier tray is equipped with 4 sets of adjustable electromagnetic wheel locks for locking the wheels of private cars, and the clamping force of the electromagnetic wheel locks is ≥30kN.

[0013] Preferably, the intelligent vehicle pallet is equipped with a millimeter-wave radar and a high-definition camera at its front end, which work in conjunction with the sensing units on both sides of the dual-track to achieve dual guidance of "vision + radar".

[0014] As a preferred option, the intelligent vehicle carrier tray is equipped with a horizontal electric push rod at the bottom, which is used to automatically fine-tune and align the private car to ensure docking accuracy.

[0015] Preferably, the green electric drive carbon reduction unit supplies power to the same-load and same-track shuttle rail unit and the intelligent docking vehicle pallet unit through a 1500VDC third rail; wherein, a 10kV substation is set at 5km intervals along the 1500VDC third rail, and the traction motor adopts a permanent magnet synchronous motor.

[0016] As a preferred option, the green electricity access scheme specifically involves prioritizing access to urban distributed photovoltaic power stations, with green electricity accounting for 35% initially, and later increasing the proportion of green electricity to over 80% through "photovoltaics + energy storage". The energy storage battery uses lithium iron phosphate batteries to smooth out fluctuations in green electricity.

[0017] Preferably, the traffic flow prediction model uses an LSTM neural network. The input features of the traffic flow prediction model include historical traffic flow, weather, and date type. The output of the traffic flow prediction model is the traffic flow at each hub station.

[0018] The beneficial effects of this invention are: 1. This invention enables the driver and private car to travel together, breaking through the limitations of the existing rail system's "separation of people and vehicles". It allows the driver and private car to travel together throughout the journey without the need for additional transportation connections, solving the "instant vehicle use" demand and shortening the time by 40-60 minutes compared to the "separation of people and vehicles" solution. 2. This invention integrates millimeter-wave radar, LED guidance, and electric push rod fine-tuning technology to enable private cars to quickly drive in and dock within 30 seconds with an accuracy of ±2cm. It is compatible with 99% of private car sizes (length 3.8-5.2m) and the docking efficiency is 10 times higher than that of existing freight pallets. 3. This invention achieves a carbon reduction rate of ≥82% per unit vehicle when crossing cities by using "photovoltaic + energy storage" green electricity access (accounting for 80% in the later stage) and a lightweight tray (energy consumption of 0.3kWh / km), which reduces carbon emissions by more than 80% compared with traditional self-driving and improves the carbon reduction rate by 47 percentage points compared with the "human-vehicle separation" power solution. 4. This invention achieves multi-track coordinated operation during peak hours based on LSTM traffic flow prediction and dynamic departure interval control, with no traffic congestion over long distances and a punctuality rate of ≥99.5%, which is 3 times more efficient than traditional self-driving during off-peak hours (cross-city travel time reduced from 41.6 min to 8.45 min).

[0019] Secondly, a method for operating a shared-vehicle shuttle rail system includes the following steps: The full-process scheduling control unit predicts the traffic flow of each hub station in the future time period, and dynamically generates a departure interval plan based on the traffic flow of each hub station in the future time period. The departure interval plan is then sent to each hub station and the intelligent docking vehicle pallet unit. Private cars are guided to enter the dedicated lanes of each hub station for identification, and then, under the guidance of vision and radar, they drive into the precisely aligned smart vehicle tray, where they are automatically clamped by electromagnetic wheel locks. Private cars and drivers are transported to the target hub station via intelligent docking vehicle pallet units along the same-carrying shuttle track units. Attached Figure Description

[0020] Figure 1 The diagram shows the overall layout of a shared-car shuttle track system.

[0021] Figure 2 The image shown is a top view of the intelligent vehicle pallet structure.

[0022] Figure 3 The diagram shows the internal structure of the driver's cabin.

[0023] Figure 4 The image shows a comparison of carbon reduction effects.

[0024] Figure 5 The figure shows the accuracy curve of the LSTM traffic flow prediction model.

[0025] Figure 6 The diagram shows a flowchart of the operation method of a private car shuttle track system based on vehicle-track collaborative carbon emission optimization.

[0026] Figure 7 The diagram shows a flowchart of the operation method of a private car shuttle track system based on vehicle-track collaborative carbon emission optimization. Detailed Implementation

[0027] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, and are not intended to limit the scope of the invention.

[0028] Example 1: A vehicle-track collaborative carbon emission optimization system for private cars traveling in the same direction includes a vehicle-track collaborative shuttle track unit, an intelligent docking vehicle pallet unit, a green electric drive carbon reduction unit, and a full-process scheduling and control unit. The same-carrying shuttle rail unit includes a double-track rail laid along the central median or green belts on both sides of the city's ring expressway, as well as multiple hub stations, to provide a high-speed and stable transportation base for private cars. The intelligent docking vehicle pallet unit includes an intelligent vehicle pallet, which is used to enable rapid and precise docking and separation of private cars and dual-track rails; The green electric drive carbon reduction unit is used to provide electric drive for the same-carrying shuttle track unit and the docking vehicle pallet unit, and to reduce carbon emissions of the same-carrying private vehicle shuttle track system through the green electric access scheme. The full-process scheduling and control unit is used to dynamically schedule the operation of the intelligent docking vehicle pallet unit based on the traffic flow prediction model, and to monitor the operation status and safety of the entire shared private vehicle shuttle track system in real time.

[0029] In this embodiment, as Figure 1 As shown, the dual-track system is laid along the central median or the green belts on both sides of the city's ring expressway. Multiple hub stations are also located on the ring expressway. The dual-track system of the same-car, same-passage shuttle rail unit has a track gauge of 2.4m (suitable for private cars with a width ≤1.9m, with a 0.5m safety gap). The track material is U75V heavy-duty steel rail (tensile strength ≥880MPa, hardness HB260-300). The track foundation uses a reinforced concrete cap + pile foundation (single pile bearing capacity ≥1200kN) to ensure stability during operation at 350km / h. One hub station is located at each of the four entrances / exits of the ring expressway in the east, west, north, and south directions. The station spacing is determined according to the city's size (38.5km north-south and 45.2km east-west in City A) to ensure cross-city coverage of the core commuter corridor.

[0030] In this embodiment, the intelligent vehicle pallet of the intelligent docking vehicle pallet unit adopts a lightweight aluminum alloy design (density 2.7g / cm³), weighs 1.2t, and has a load-bearing capacity of ≥2.5t (covering 99% of the weight of private cars); the surface of the intelligent vehicle pallet is equipped with 4 sets of adjustable electromagnetic wheel locks (spacing 80-180cm, suitable for private car wheelbases of 2.5-3.2m), with a clamping force of ≥30kN (which can withstand the centrifugal force when running at a speed of 350km / h. The centrifugal force F is calculated as: F=mv² / r=1300kg×(97.22m / s)² / 3000m≈4043N, which is much smaller than the clamping force, where m represents mass, v represents linear velocity, and r represents the radius of rotation). like Figure 2As shown, the docking guidance technology of the intelligent docking vehicle pallet unit is as follows: two millimeter-wave radars (detection distance 50m, accuracy ±2cm) and one high-definition camera (frame rate 30fps) are installed at the front end of the intelligent vehicle pallet to work with the sensing units on both sides of the dual-track (green solid line guidance, brightness ≥500cd / m²) to achieve dual guidance of "vision + radar"; a horizontal electric push rod (travel ±50cm, response time ≤0.5s) is set at the bottom of the intelligent vehicle pallet. When the deviation of the private car is ≤50cm, it automatically makes fine adjustments to ensure docking accuracy.

[0031] The intelligent vehicle carrier tray is designed to accommodate a full-size private car (18m long, 3.2m wide, and 2.2m high). It includes a driver's cab, allowing the driver and car to travel together without additional transportation, addressing the need for immediate vehicle use and reducing travel time by 40-60 minutes compared to a separate driver-vehicle solution. The driver's cab's internal structure is as follows. Figure 3 As shown, the driver's cabin is equipped with a ventilation system, a temperature control panel, an emergency escape door, and an observation window. The observation window (tempered glass, light transmittance ≥92%) is located at the front of the intelligent vehicle carrier tray. The intelligent vehicle carrier tray is equipped with an independent ventilation system (air volume 150m³ / h), a temperature control panel (adjustable from 18-26℃), and an emergency escape door (opening time ≤10s), ensuring the driver's safety and comfort during transport and allowing real-time observation of the track's operating status. This enables "co-transportation," ensuring the driver remains inside their private vehicle throughout the journey, traveling across cities with the vehicle via the rail system without separation, thus meeting immediate transportation needs.

[0032] In this embodiment, the green electric drive carbon reduction unit provides electric drive for the same-load and same-track shuttle track unit and the docking vehicle pallet unit. Specifically, the same-load and same-track shuttle track unit adopts 1500VDC third rail power supply, and a 10kV transformer box (transformer efficiency ≥92%) is set every 5km. The traction motor adopts permanent magnet synchronous motor (efficiency ≥95%), and the energy consumption per pallet is optimized to 0.3kWh / km (including traction, ventilation and temperature regulation).

[0033] The green electricity access scheme is as follows: the system will prioritize access to urban distributed photovoltaic power stations, with green electricity accounting for 35% in the initial stage, and will be increased to more than 80% in the later stage through the "photovoltaic + energy storage" system. The energy storage battery adopts lithium iron phosphate battery to smooth out the fluctuation of green electricity.

[0034] In this embodiment, the carbon reduction of the private car shuttle system is quantitatively calculated: Traditional self-driving carbon emissions for:

[0035] The carbon emissions of the co-carriage and co-traffic private car shuttle rail system proposed in this invention are optimized based on vehicle-rail coordination (initially 35% green electricity). for:

[0036] The carbon emissions of the co-carriage and co-traffic private car shuttle rail system proposed in this invention are optimized based on vehicle-rail coordination (80% of which will be green electricity in the later stages). for:

[0037] Carbon reduction rate: Initial carbon reduction rate = (7.4-4.4) / 7.4×100%≈40.5%, later carbon reduction rate = (7.4-1.3) / 7.4×100%≈82.4%, far exceeding the 35% of existing schemes; The above energy consumption and carbon emission calculation logic has been automated through code, and the carbon reduction effect is, for example... Figure 4 As shown.

[0038] In this embodiment, the full-process scheduling and control unit uses an LSTM neural network to predict traffic flow at each station. Input features include historical traffic flow, weather (rainfall, wind speed), and date type (weekday / holiday), with a prediction accuracy of ≥92%. The departure interval is dynamically adjusted based on the prediction results: 30 seconds / trip during peak hours (hourly capacity of a single track = 3600s / 30s × 1 vehicle = 120 vehicles), and 60 seconds / trip during off-peak hours (hourly capacity of 60 vehicles). During the initial trial operation phase, 4 round-trip tracks are prioritized (4 in one direction, 8 in two directions), with a one-way hourly capacity of 4 × 120 = 480 vehicles, which can handle approximately 5.1% of the traffic flow during peak hours, verifying the system's stability. In the long term, the tracks will be deployed according to passenger flow demand to ensure intensive and efficient operation. The training, validation, and real-time prediction logic of the LSTM traffic flow prediction model have been implemented in code. The accuracy curve of the LSTM traffic flow prediction model is shown below. Figure 5 As shown.

[0039] In this embodiment, the full-process scheduling and control unit uses "5G + Beidou positioning" (accuracy ±1m) to monitor the position, speed, and wheel lock status of the intelligent vehicle pallet in real time. The central control platform (located at the East Station) displays the full-link data. When the intelligent vehicle pallet deviates (deviation ≥5cm) or the wheel lock loosens (clamping force <25kN), the system automatically triggers emergency braking (braking distance ≤50m at a speed of 350km / h). Two emergency lanes are reserved at each station. In case of failure, vehicles can return to the ring expressway through the emergency lanes to ensure no delays.

[0040] This addresses the problems of low efficiency, high time costs, high carbon emissions, and hindered green development associated with traditional travel modes and existing transportation systems. Taking the A City Ring Expressway as a typical case: According to the 2023 traffic big data from the A City Ring Expressway Operating Company, its total length is 80.35km, with an average daily cross-city traffic flow of 52,000 vehicles, of which private cars account for 82% (42,640 vehicles / day). During peak hours (7:00-9:00, 17:00-19:00), the proportion of private car traffic rises to 88% (11,000 vehicles / hour). For north-south cross-city travel (railway distance 38.5km), the average speed of traditional private driving is only 32km / h. Adding to this the toll station queues (10-15 minutes) and delays due to accidents / cutting off (10-20 minutes), the total travel time reaches 103.8 minutes. Even during off-peak hours, the cross-city travel time is still 41.6 minutes, far from meeting the needs of efficient commuting. Extending this to other megacities: In City B, the east-west cross-city journey (42km) via the city's ring expressway (85km total length) takes 112 minutes during peak hours; in City C, the north-south cross-city journey (52km total length) via the city's ring expressway (120km total length) takes 135 minutes during peak hours, indicating widespread time wastage. Meanwhile, taking City A's north-south cross-city journey (38.5km) as an example, the carbon emissions per private car per trip are approximately (38.5 ÷ 100) × 8.5 × 2.3 ≈ 7.4 kg. If we calculate based on an average of 42,640 private cars crossing the city's ring expressway daily, the daily carbon emissions reach approximately 42,640 × 7.4 ≈ 315,500 kg (315.5 tons), resulting in annual carbon emissions exceeding 115,000 tons.

[0041] To address the aforementioned issues, this invention proposes a vehicle-rail coordinated carbon emission optimization system for private cars traveling in the same direction. Specifically designed for cross-city travel scenarios, this system utilizes technologies such as high-speed rail transport, intelligent docking, and green electric drive to shorten cross-city travel time, reduce carbon emissions, and improve driving comfort. It can be widely applied to ring roads of megacities with a resident population of ≥5 million and intercity corridors within metropolitan areas with a radius of ≤100km (such as Xi'an-Xianyang and Guangzhou-Foshan). It enables shared transportation, ensuring that the driver remains inside the private car throughout the journey, traveling across cities together with the vehicle via the rail system without separating the driver and vehicle, thus meeting immediate transportation needs; it drastically reduces cross-city travel time: during peak hours, cross-city travel time is ≤10 minutes (taking a cross-city distance of 38-50km as an example), and during off-peak hours, it is ≤15 minutes, with a time saving rate of ≥80%; it significantly reduces carbon emissions: the carbon emissions of a private car traveling across cities are ≤1.5kg, with a comprehensive carbon reduction rate of ≥80%, and annual carbon emissions are reduced by more than 90,000 tons compared to traditional self-driving; at the same time, it also improves comfort and safety: the driver does not need to operate the vehicle, the track running amplitude is ≤0.2mm, the frequency of rapid acceleration / sudden braking is ≤0.1 times / 100km, and driver fatigue is reduced by more than 90%.

[0042] Example 2: Based on Example 1, this embodiment of the invention provides an operation method for a shared-carriage private car shuttle track system based on vehicle-track cooperative carbon emission optimization, such as... Figure 6 and Figure 7 As shown, the specific steps include: S1. Predict the traffic flow of each hub station in the future time period through the full-process scheduling control unit, and dynamically generate the departure interval plan based on the traffic flow of each hub station in the future time period, and send the departure interval plan to each hub station and the intelligent docking vehicle pallet unit. S2. Private cars are driven into the dedicated lanes of each hub station for identification, and then driven into the precisely aligned smart vehicle tray under visual and radar guidance, and automatically clamped by electromagnetic wheel locks; Specifically: Private cars enter the dedicated ramp of the station from the main road of the ring expressway. The vehicle type (private car / other vehicle type) is identified by ETC, and the system allocates the corresponding entry lane (3.5m wide, 1:20 slope). The speed limit at the end of the ramp is 5km / h. The vehicle drives along the LED trajectory light strip, and the in-vehicle APP displays the "deviation value" in real time (such as "15cm deviated to the left"), and the driver makes minor adjustments to the direction. When the front wheels of the vehicle press on the trigger line at the front of the tray, the millimeter-wave radar detects the position, and the tray automatically makes minor adjustments to align (time ≤2s). When the vehicle is fully driven into the tray (the rear wheels pass the trigger line at the end), the electromagnetic wheel lock automatically clamps (time ≤3s), and the system prompts "Secured successfully, about to start" with a voice prompt.

[0043] The entire process of entering takes ≤30s, and exiting takes ≤15s (unlocking + guided exit), which is far less than the 5min of the existing baggage handling system.

[0044] S3. Private cars and drivers are transported to the target hub station via intelligent docking vehicle pallet units along the same load and travel shuttle track units.

[0045] Example 3: Based on Example 1, this embodiment of the invention takes a pilot project on a ring expressway in a certain city as an example to provide a detailed description of the deployment and operation of the same-carriage and same-track private car shuttle track system based on vehicle-track collaborative carbon emission optimization.

[0046] I. Implementation Preparation Phase 1. Data collection and track planning: Collect traffic flow data and road condition data (location of congested road sections and average speed) for nearly 12 months, determine the track laying route (along the central median, avoiding special sections such as bridges and tunnels), and complete the site selection of stations in four directions; 2. Equipment R&D and Testing: Develop an intelligent docking vehicle pallet (aluminum alloy material, weight 1.2t, load capacity 2.5t), and complete wheel lock clamping force test (30kN meets the standard) and energy consumption test (0.3kWh / km meets the standard) in the laboratory; train an LSTM traffic flow prediction model, input historical traffic flow data, and verify that the model meets scheduling requirements; 3. Green electricity access plan determined: Initially, 35% of the electricity will be green electricity, and later, through a 100MWh energy storage battery, the proportion of green electricity will be increased to 80%, thereby optimizing the carbon emissions per vehicle.

[0047] II. Construction and Implementation Phase 1. Track and Station Construction: A segmented construction method will be adopted, first constructing the north-south track (38.5km) and the north and south stations, then constructing the east-west track (45.2km) and the east and west stations; seamless welding technology will be used for track laying to ensure that the flatness error is ≤2mm / 10m; each station will have 3 entry lanes and 3 exit lanes, and will be equipped with LED guide light strips, millimeter-wave radar, and intelligent robotic arm docking devices; 2. System Integration and Debugging: Integrate the track system, vehicle pallet, dispatching system, and green power supply system to complete no-load test run (test track stability, amplitude ≤0.2mm at 350km / h), full-load test run, and peak simulation test run, and solve problems such as "wheel lock response delay" and "traffic flow prediction deviation" found during debugging.

[0048] III. Pilot Operation Phase 1. Phased operation: Initially, the north-south rail line will be opened. The LSTM traffic flow prediction model will be called through the central control platform to predict traffic flow in real time and calculate carbon emissions. Monitoring results show that the cross-city travel time, carbon emissions, and driver fatigue reduction index all meet the standards. Long-term optimization of forecast parameters will reduce the departure interval from 30 seconds to 25 seconds, increase capacity, and implement optimization strategies such as adding tracks. 2. Data Monitoring and Optimization: Build a big data platform for "time-carbon emissions-comfort" to calculate energy consumption and carbon emissions daily, collect driver comfort survey data, output optimization reports monthly, and optimize energy consumption by adjusting the power of the pallet ventilation system.

[0049] IV. Promotion and Operation Phase 1. Extend the vehicle-rail coordinated carbon emission optimization private car shuttle rail system to the surrounding districts and counties of a certain city, covering a 100km metropolitan area, and carry an average (long-term) 60,000 private cars crossing the city every day. The annual carbon reduction is calculated to be 60,000 × (7.4-1.3) × 365 ≈ 13.395 million kg (13,400 tons). 2. Based on the pilot experience in a certain city, we formulated the "Construction Standard for Private Car Shuttle Rail System with Shared Rides" and promoted it in other cities, providing a solution for reducing carbon emissions in cross-city transportation across the country.

[0050] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A shuttle track system for private cars traveling in the same direction, characterized in that, It includes a co-carrying shuttle track unit, an intelligent docking vehicle pallet unit, a green electric drive carbon reduction unit, and a full-process scheduling and control unit; The same-carrying shuttle rail unit includes a double-track rail laid along the central median or green belts on both sides of the city's ring expressway, as well as multiple hub stations, to provide a high-speed and stable transportation base for private cars. The intelligent docking vehicle pallet unit includes an intelligent vehicle pallet, which is used to enable the rapid and precise docking and separation of private cars from the dual-track system, and to transport the private cars to the target hub station. The green electricity-driven carbon reduction unit is used to provide electric drive for the same-carrying shuttle track unit and the intelligent docking vehicle pallet unit, and to reduce carbon emissions of the same-carrying private vehicle shuttle track system through a green electricity access scheme. The full-process scheduling and control unit is used to dynamically schedule the operation of the intelligent docking vehicle pallet unit based on the traffic flow prediction model, and to monitor the operation status and safety of the entire shared private vehicle shuttle track system in real time.

2. The shared-vehicle shuttle track system according to claim 1, characterized in that, The double-track track has a gauge of 2.4m and is made of U75V heavy-duty steel rails. The double-track track foundation is constructed using a reinforced concrete cap and pile foundation.

3. The shared-vehicle shuttle track system according to claim 1, characterized in that, The hub stations are located at the four entrances and exits of the ring expressway in the east, west, north, and south directions; each hub station has multiple entry lanes and multiple exit lanes.

4. The shared-vehicle shuttle track system according to claim 1, characterized in that, The intelligent vehicle carrier tray adopts a lightweight aluminum alloy design; the surface of the intelligent vehicle carrier tray is equipped with 4 sets of adjustable electromagnetic wheel locks for locking the wheels of private cars, and the clamping force of the electromagnetic wheel locks is ≥30kN.

5. The shared-carriage shuttle track system for private vehicles according to claim 1, characterized in that, The intelligent vehicle pallet is equipped with millimeter-wave radar and a high-definition camera at its front end, which work in conjunction with the sensing units on both sides of the dual-track system to achieve dual guidance of "vision + radar".

6. The shared-carriage and-transport private vehicle shuttle track system according to claim 1, characterized in that, The intelligent vehicle carrier tray is equipped with a horizontal electric push rod at the bottom, which is used to automatically fine-tune and align private cars to ensure docking accuracy.

7. The shared-vehicle shuttle track system according to claim 1, characterized in that, The green electric drive carbon reduction unit supplies power to the same-load shuttle track unit and the intelligent docking vehicle pallet unit through a 1500VDC third rail; among them, 10kV substations are set every 5km along the 1500VDC third rail, and the traction motor adopts a permanent magnet synchronous motor.

8. The shared-carriage and-transport private vehicle shuttle track system according to claim 1, characterized in that, The green electricity access scheme is as follows: priority is given to accessing urban distributed photovoltaic power stations, with green electricity accounting for 35% in the initial stage. In the later stage, the proportion of green electricity will be increased to more than 80% through "photovoltaics + energy storage". The energy storage battery adopts lithium iron phosphate batteries to smooth out the fluctuation of green electricity.

9. The shared-carriage and-transport private vehicle shuttle track system according to claim 1, characterized in that, The traffic flow prediction model uses an LSTM neural network. The input features of the traffic flow prediction model include historical traffic flow, weather, and date type. The output of the traffic flow prediction model is the traffic flow at each hub station.

10. A method for operating a shared-carriage shuttle rail system based on any one of claims 1-9, characterized in that, Includes the following steps: The full-process scheduling control unit predicts the traffic flow of each hub station in the future time period, and dynamically generates a departure interval plan based on the traffic flow of each hub station in the future time period. The departure interval plan is then sent to each hub station and the intelligent docking vehicle pallet unit. Private cars are guided to enter the dedicated lanes of each hub station for identification, and then, under the guidance of vision and radar, they drive into the precisely aligned smart vehicle tray, where they are automatically clamped by electromagnetic wheel locks. Private cars and drivers are transported to the target hub station via intelligent docking vehicle pallet units along the same-carrying shuttle track units.

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