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The development of intelligent transportation improves road efficiency, reduces automobile energy consumption, and improves driving safety. The core of intelligent transportation is the two-way information interaction between vehicles and the road environment. At present, road environmental information can flow to the vehicle, while the vehicle’s information rarely flows to the outside world. The electronic throttle and electronic braking systems of some vehicles use sensors to get the state of the accelerator and brake pedal, which can be transmitted to the outside environment through technologies such as the Internet of Vehicles. But the Internet of Vehicles technology has not been widely used, and it relies on signal sources, which is a passive way of information acquisition. In this paper, an active identification method is proposed to get the vehicle pedal on-off state as well as the driver’s operation behavior through existing traffic facilities.

Natural gas has been considered to be one of the most promising alternative fuels due to its lower NOx and soot emissions, less carbon footprint as well as attractive price. Furthermore, higher octane number makes it suitable for high compression ratio application compared with other gaseous fuels. For better economical and lower emissions, a turbocharged, four strokes, direct injection, high pressure common rail diesel engine has been converted into a diesel/natural gas dual-fuel engine. For dual-fuel engine operation, natural gas as the main fuel is sequentially injected into intake manifold, and a very small amount of diesel is directly injected into cylinder as the ignition source. In this paper, a dual-fuel electronic control unit (ECU) based on the PowerPC 32-bit microprocessor was developed. It cooperates with the original diesel ECU to control the fuel injection of the diesel/natural gas dual-fuel engine.

H-Bahn ("hanging railway") refers to the suspended, unmanned urban railway transportation system. Through the reasonable platform layout, H-Bahn can be easily integrated into the existing urban transit system. With the development of urban roads, the associated rail facilities can be conveniently disassembled, moved and expanded. The track beam, circuits, communication equipment, and sound insulation screen are all installed in a box-type track beam so that the system can achieve a high level of integration and intelligence. The carriage of the modern H-banh vehicle is connected with the bogies by two hanging devices. The vehicle is always running in the box-type track beam; therefore there are less possibilities of derailment. Consequently, the key work focuses on the running stability evaluation and curve negotiation performance analysis.

Braking energy recovery is an important method for Battery Electric Vehicle (BEV) to save energy and increase driving range. The vehicle braking system performs regenerative braking control based on driver operations. Different braking operations have a significant impact on energy recovery efficiency. This paper proposes a method for planning the braking process of a BEV based on the Intelligent Vehicle Infrastructure Cooperative System (IVICS). By actively planning the braking process, the braking energy recovery efficiency is improved. Vehicles need to decelerate and brake before entering a curve. The IVICS is used to obtain information about the curve section ahead of the vehicle's driving route. Then calculating the reference speed of the curve, and obtaining the vehicle's braking target in advance, so as to actively plan the vehicle braking process.

Dynamic modeling and state estimation are significant in the trajectory tracking and stability control of the intelligent vehicle. In order to meet the requirement of the stability control of the eight-in-wheel-motor-driven intelligent vehicle, a full vehicle dynamics model with 12 degrees of freedom, including the longitudinal, lateral, yaw and roll motion of the body, and rotational motion of 8 wheels, is established for the research of the intelligent vehicle in this paper. By simulation with MATLAB/SIMULINK and by comparison with the TruckSim software, the reliability and practicality of the dynamics model are verified. Based on the established dynamics model, an extended Kalman filter (EKF) state observer is proposed to estimate the vehicle sideslip angle, roll angle and yaw rate, which are the key parameters to the stability control of the intelligent vehicle.

In order to perform differential control instead of the mechanical differential and improve the steering performance of distributed electric vehicles, a two-level differential speed steering control strategy is proposed. Firstly, an upper-layer controller to track the yaw rate is designed based on PID feedback and 3-D lookup table model, which could shorten the response time and reduce the impact of model parameters mismatch. Then, in order to improve the robustness to external disturbances and parameter uncertainties, a lower-layer controller to track the wheel speed is proposed based on integral sliding mode control. Moreover, three simulations are conducted to validate the proposed strategy. The first simulation results indicate that the driving torques of the inner and outer wheels are distributed properly to avoid wheel slip. In the second simulation, when the conventional steering system fails, the proposed control strategy could avoid vehicle losing steering function.

Commercial vehicle plays an important role during transportation process under the demand of high speed, convenience and efficiency. So improving active safety of commercial vehicle has become a research topic. Due to the fact that braking characteristic is the basic and most closely related to safe driving of vehicle's performances, this paper aims to improve the braking performance by researching into an integrated control method based on the mature ABS products. Firstly, a strategy which gives priority to ABS and differential yaw moment control, complementary with the hydraulic active suspension control is proposed. In comparison with ABS, the combined control of brake system and suspension system is designed not only for preventing wheels lock. But the directional control to avoid roll or spin is more focused on. Then in order to run the novel method correctly, the controlled variables and evaluation criteria are illustrated briefly.

This paper presents a Driver-In-the-Loop (DIL) bench test system for development of ESC controller. The real-time platform is built-up based on NI/PXI system and the real steering/throttle/braking actuator. In addition, the CarSim provides the vehicle model and the animator for virtual driving environment. A hierarchical ESC controller is proposed in MATLAB/Simulink then download into PXI. In the upper motion controller, the sliding mode theory is adopted and the logic threshold algorithm is used in the lower slip controller. Finally, ESC test is implemented under typical conditions by DIL and Model-In-the-Loop (MIL). The results show that, DIL could make up the shortage of driver model which can’t accurately simulate the emergency response of real driver. Therefore, DIL test could verify the ESC controller more accurately and effectively with considering the human-vehicle-road environment.

An applicable and comprehensive control strategy of a natural gas/diesel dual fuel engine is presented in this paper. The dual fuel engine is converted from a conventional mechanical pump, turbo charged, heavy duty diesel engine. In the dual fuel mode, the pedal position is explained as demanded total fuel quantity, the quantity of pilot diesel and natural gas are calculated in order to provide the equal energy with the original diesel engine at the same operation condition, the proportion of the natural gas is primarily determined by the load rate and the speed of the engine. When the engine is working under light or moderate load, the intake air is throttled in order to improve the brake mean effective pressure and reduce the hydrocarbon emissions of the dual fuel engine, according to target excess air ratio and the quantities of the two fuels, the desired air mass per cycle can be obtained.