It is well known that a multi-axle wheeled robot possesses larger load capability and also higher drive performance. However, its steering flexibility is degraded due to the large number of wheels. In order to solve this problem, in this article, we proposed three control schemes based on the center of rotation or the steering angles of both the first-and last-axle wheels. To release these control schemes, steering mode selection and also the left wheel's steering angle in a specific axle are added approaching a practical application. Thereafter, the remaining wheels' steering angles can be calculated with the Ackerman steering theorem. In order to verify the control effects, a five-axle all-wheel-steering wheeled robot has been developed with the Bluetooth wireless monitor system. Based on the newly designed robot, validation experiments are carried out, such as lateral movement, situ rotation, and multi-mode steering within a narrow space. The results indicate that the proposed design in this article can ensure a more flexible and faster movement within a narrow space. It shows large potential in obstacle avoidance compared with the conventional partial-wheel steering mode.

In order to provide basis and standards to the research on unmanned driving behaviors, a more thorough evaluation system of Intelligent Behavior for Unmanned Ground Vehicles needs to come forward. The intelligent behavior of unmanned ground vehicles in pedestrian crossing scenario is taken as an example in this paper. By using building and analyzing evaluation index system, this paper proposes an evaluation method that can comprehensively expressed the technological performance of unmanned ground vehicles based on Analytic Hierarchy Process (AHP). Compared with traditional methods, this evaluation method takes index weight into sufficient conderations and is more objective. The method properly works out with index weight of specific scenarios that reflects the actual situations. The establishment of comprehensive scoring method objectively and conveniently turns the performances of unmanned ground vehicle into scores, so that the results can be compared and ranked directly. Last but not least, a certain participating vehicle is used for case study. The result proves aforementioned method to be practical, reliable, convenient and logical. It not only evaluates the assessment comprehensively, but also evaluates the index separately to guide researchers to find out the defects of unmanned driving vehicle evaluation indexes and point out ways to improve them.

To promote the development of unmanned ground vehicle technologies, it is necessary to design a scientific and reasonable test method. Road is an important part of test environmental elements, and different road conditions can examine the adaptability of unmanned ground vehicles to the environment. Therefore, the scientific calculation of road complexity is of great importance. Previous studies on road are mainly based on the concept of road roughness; however due to the unicity of road feature indicators, road complexity can only be reflected to a certain extent. This paper proposes a new road-feature-based multiparameter road complexity calculation model of off-road environment to show the complexity of road more comprehensively. First, a multi-sensorbased data acquisition mobile platform is established to obtain more complete road data. Then, based on the analysis of road feature, road indicators like three-dimensional scale, average slope, and adhesion characteristics of travelable area are obtained. According to the analysis methods of road roughness, the principle of analytic hierarchy process, and the data collected from off-road environment, the calculation model of road complexity is determined. Finally, by calculating complexities of several cross-country roads, the feasibility of this model is verified, which provides a theoretical support for the scientific calculation and quantitative analysis of different road complexities.

In order to improve the comprehensive and rationality of examination for driving braking performance with Mean Fully Developed Deceleration (MFDD) in road test, also to provide a basis for driving braking performance evaluation with MFDD when real driving, an approach for determining the MFDD threshold is proposed considering initial braking velocity and passenger capacity. According to the vehicle braking performance road test rules in GB7258, a simulation model is built, and simulation tests are made with different initial braking velocities. Based on simulation data, MFDD is calculated, and the curve of MFDD with initial braking velocity is also given, and then the effects of initial braking velocity on MFDD and its threshold are analyzed; the curves of MFDD thresholds with initial braking velocity are plotted with no-load and full-load respectively. The influence of passenger capacity on MFDD threshold is analyzed, and the curve of MFDD threshold with passenger capacity is given, too. Finally, the formula of MFDD threshold with initial braking velocity, seating capacity and passenger capacity is resulted.

The test system for technical abilities of unmanned vehicles is gradually developed from the single test to comprehensive test. The pre-established test and evaluation system can promote the development of unmanned ground vehicles. The 2009 Future Challenge: Intelligent Vehicles and Beyond (FC’09) pushed China's unmanned vehicles out of laboratories. This paper proposed to design a more scientific and comprehensive test system for future competitions to better guide and regulate the development of China's unmanned vehicles. According to the design idea of stage by stage and level by level, the hierarchical test content from simple to advanced, from local to overall is designed. Then the hierarchic test environment is established according to the levels of test content. The test method based on multi-platform and multi-sensor is put forward to ensure the accuracy of test results. The testing criterion framework is set up to regulate future unmanned vehicle contests and to assess the unmanned vehicles scientifically and accurately.

To improve the technology of unmanned ground vehicles, it is necessary to conduct a proper evaluation on various technologies. Previous evaluation methods are mainly based on completion of the task; this may mislead most of teams of unmanned ground vehicles using a conservative strategy during the evaluation. In this paper, a new evaluation method is proposed. Based on typical working conditions including intersection, car-following, and obstacle-avoiding, the new evaluation indicator system is established, and the entropy-cost function method is applied to the comprehensive evaluation of unmanned ground vehicles. As reported in a numerical example, the proposed evaluation method can get a quantitative result that authentically reflects the intelligent behavior level of unmanned ground vehicles.

Carbon trading is an effective measure for the road transportation to reduce energy consumption and carbon emissions. Carbon emission quotas are the primary concern to ensuring the efficiency of carbon trading. However, the existing studies have mostly focused on carbon emission quotas in different regions, i.e., countries and provinces. Few literature studies simulate carbon quota allocation in the road transportation. A novel approach from the perspective of carbon emission intensity of vehicle is proposed, on the basis of data envelopment analysis (DEA) model. Unlike other studies, the idea of allocation of baseline excitation is introduced and the intensity is included in the model as the baseline. Firstly, the Delphi method is employed to select input and output indicators. Secondly, carbon emission intensity is determined by the cumulative distribution function (CDF). Furthermore, the carbon emission quotas in road transportation in 30 provinces of China are used to validate the model. The results show that (1) the carbon emission intensity of commercial trucks and buses in China’s road transport industry is 75.04 g/t·km and 13.12 g/p·km, respectively; (2) the provinces of Shanghai, Guangdong, and Xinjiang have the greatest carbon reduction potential and Henan, Hunan, and Anhui have the largest increase in emission quotas; (3) compared with traditional “history responsibility” and “baseline” methods, the proposed approach increases allocation efficiency by 19% and 14%, respectively; and (4) the approach can make the carbon emission quotas play the role of incentive while taking fairness into account and can more effectively promote the implementation of carbon trading system in road transportation.

According to the vehicle braking efficiency road test rules in GB7258, the braking efficiency on-line monitoring index, parameter, method and threshold are studied. Mean fully developed deceleration (MFDD) is selected as the evaluation index. Pitch angle which is used to monitor the road slope(less than 1%) is collected by gyroscope. Vehicle maximum deceleration is collected at the period of ABS working, which is to make sure that the road adhesion coefficient is more than 0.7. Vehicle maximum braking deceleration is analyzed, and it is used to exclude driving on pit, decelerating band, road step, even crash and so on. The rapid stop is identified with brake pedal travel senor. MFDD is calculated with braking deceleration and wheel speed, and wheel speed is collected from ABS with can bus. MFDD threshold is determined with passenger capacity monitoring with card reader. Finally, the method of vehicle braking efficiency on-line monitoring and evaluation with MFDD is given.