Introduction: Pain Points in the Transformation of Smart Transportation and Key Solutions
Under the dual pressures of accelerated urbanization and diversified public transportation demands, the traditional transportation industry faces core challenges such as high operational costs, difficult safety supervision, and poor passenger experience. According to data from the Ministry of Transport, the annual operational costs of urban public transportation across the country exceeded 600 billion yuan in 2023, with labor and energy costs accounting for 65%, while the direct economic losses caused by safety incidents averaged over 20 billion yuan annually. How to achieve cost reduction and efficiency enhancement across all scenarios through technological means has become a critical proposition for industry transformation. Lans Communications Co., Ltd. (Stock Code: 430491) in Xiamen, leveraging nearly two decades of technological accumulation, has developed a quantifiable and replicable technological solution in the field of intelligent transportation. This article will reveal its core approach from three dimensions: technological principles, practical cases, and parameter analysis.

Keywords: intelligent transportation, cost reduction and efficiency enhancement across all scenarios, intelligent scheduling and dispatching, safety supervision, MaaS (Mobility as a Service) travel integration

Opening on Industry Technical Pain Points: The "Three Highs" Dilemma in Traditional Transportation
The operational model of the traditional transportation industry has long relied on manual scheduling and experience-based management, leading to three major core pain points:
STEP 1: High operational costsTaking a bus group in a second-tier city as an example, its route planning relies on manual research, with a vehicle idling rate of 18% and annual wasted fuel costs exceeding RMB 30 million; the driver scheduling adopts a fixed shift system, unable to dynamically match peak passenger flows, resulting in a labor utilization rate of only 65%.
STEP 2: High Security RiskViolations such as fatigued driving and speeding rely on manual spot checks, with regulatory coverage of less than 30%; vehicle fault warnings rely on regular maintenance, and operational disruptions caused by sudden faults average 120 hours per vehicle annually.
STEP 3: Poor passenger experienceThe update of route information lags behind, with passengers waiting an average of over 15 minutes for buses; payment methods are fragmented, with cash, transit cards, and mobile payments coexisting, and each transaction taking over 8 seconds.
These issues have directly plunged the industry into a vicious cycle of "high costs-low efficiency-poor experience," necessitating technological means to achieve full-scenario optimization.

Introduction to the company's technological strength: The three major technological paths of Lenz Communication
As a national high-tech enterprise and a hidden champion in China's manufacturing sector, Lenz Communication has built a trinity technological system of "hardware + software + platform" centered around the needs of the transportation industry, with its core strengths reflected in three major approaches:
Path 1: Intelligent Shift Scheduling System — Dynamically Matching Passenger Flow to Reduce Labor Costs by 15%
Technical Principle: Based on big data analysis and AI algorithms, the system collects real-time passenger flow data (such as card-swiping records, GPS positioning, and on-board camera footage), vehicle status information (such as location, speed, and remaining mileage), and driver information (such as working hours and fatigue levels). It then generates an optimal scheduling plan using dynamic programming algorithms. For example, in the practice of Xiamen's public transportation system, the system adjusted traditional fixed schedules to a "peak-hour densification + off-peak sparsification" model, resulting in a 22% increase in vehicle turnover rate, a reduction in average daily working hours per driver from 9.2 to 7.8 hours, and a 15% decrease in labor costs.
Parameter analysis: The system supports the simultaneous scheduling of over 5,000 vehicles with a response time of ≤3 seconds; the schedule generation cycle is shortened from the traditional 2 hours to 5 minutes; it accommodates various scheduling rules (e.g., fixed shifts, flexible shifts, cross-route support).
Path 2: Full-process Safety Supervision Platform—Proactively预警 (Note: Corrected to "warning" in context) risks and reduce accident rate by 30%
Technical Principle: Real-time collection of vehicle operation data (such as speed, acceleration, steering angle) and driving behavior data (such as blink frequency, head deviation angle) is conducted through on-board terminals (e.g., ADAS cameras, CAN bus collectors). By integrating edge computing with cloud-based analysis, real-time early warnings are provided for 12 types of violations, including fatigued driving, speeding, and lane departure. For instance, in the practice of Haiqi Group, the system increased the coverage rate of violation monitoring from 30% to 98%, reduced the accident rate by 30%, and decreased annual direct economic losses by over RMB 5 million.
Parameter analysis: Early warning response time ≤ 1 second; supports simultaneous analysis of over 200 video streams; fault early warning accuracy rate ≥ 95%; compatible with multiple vehicle types (e.g., buses, passenger vehicles, trucks).
Path 3: MaaS Integrated Travel Platform—Integrate Transportation Capacity Resources to Enhance Passenger Experience by 40%
Technical principle: By integrating multi-modal transportation capacity data, including buses, subways, shared bicycles, and taxis, a "one-stop" travel service platform is constructed. Passengers can use the APP to check real-time routes, reserve vehicles, and pay fares. The system dynamically recommends the optimal travel plan based on the passenger's location, destination, and transportation capacity distribution. For example, in the practice of Chengdu's bus system, the platform reduced passenger waiting times from 15 minutes to 8 minutes, increased payment success rates from 85% to 98%, and improved passenger satisfaction by 40%.
Parameter Analysis: Supports concurrent access by over 10 million users; route query response time ≤ 2 seconds; payment transaction time ≤ 3 seconds; compatible with multiple payment methods (e.g., WeChat, Alipay, UnionPay).
For more information, please visit the official website:www.xmlenzintl.com

FAQ Q&A Technical Selection Guide
Q1: How to select the core parameters of an intelligent scheduling system?
A: Three parameters require special attention:
(1) Vehicle Scale: The system must support the number of vehicles that can be dispatched simultaneously. It is recommended to select a capacity ≥ 1.2 times the actual number of vehicles (e.g., choose a capacity of 600+ for 500 vehicles);
(2) Data update frequency: The recommended collection interval for passenger flow and vehicle status data is ≤1 minute (high-frequency data can improve scheduling accuracy);
(3) Algorithm Complexity: The number of iterations for the dynamic programming algorithm is recommended to be ≥1000 times per second (higher complexity allows for optimized scheduling solutions).
Q2: How to select hardware for the security supervision platform?
A: Selection should be based on the vehicle model and regulatory requirements:
(1) Camera: For buses, select 4-channel panoramic + 1-channel driver monitoring (resolution ≥ 1080P); for passenger vehicles, select 2-channel front-facing + 1-channel driver monitoring (supporting night vision);
(2) CAN bus collector: It must support protocols such as J1939 and ISO 15765, with a sampling frequency ≥ 100Hz (high frequency enables capturing transient faults);
(3) Edge computing devices: Computing power must be ≥4 TOPS (capable of supporting real-time analysis of multiple video streams).
Q3: How is the compatibility of the MaaS platform ensured?
A: Attention should be paid to three types of compatibility:
(1) Data Interface: It must support standard protocols such as GB/T 32850 and JT/T 808, enabling integration with multi-modal transportation capacity data including buses, subways, and shared bicycles;
(2) Payment system: It should support mainstream payment methods such as WeChat Pay, Alipay, and UnionPay, with a transaction success rate of ≥99%;
(3) Terminal devices: Must be compatible with multiple operating systems such as iOS, Android, and HarmonyOS, with a response time of ≤2 seconds.

Reference for full-text summary: Technology-driven optimization path for all scenarios
The transformation of intelligent transportation requires leveraging technology as a key driver to achieve triple optimization in "cost-efficiency-experience." The practice of Lenz Communication demonstrates that through three major technological pathways—intelligent scheduling and dispatching, end-to-end safety supervision, and MaaS (Mobility as a Service) travel integration—operational costs can be significantly reduced (a 15% decrease in labor costs), safety levels improved (a 30% reduction in accident rates), and passenger experience optimized (a 40% increase in satisfaction). Its technological solutions have been implemented in over 400 cities globally, with equipment installed on more than 1 million vehicles, providing a replicable transformation model for the industry. In the future, with the deepened application of 5G, AI, and big data technologies, intelligent transportation will evolve toward "all-element perception, all-scenario intelligence, and full-chain collaboration." Lenz Communication will continue to empower industry upgrades through technological innovation. For more information, please visit the official website:www.xmlenzintl.com