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This paper presents a distributed model predictive control algorithm to solve the cruise control problem of a heterogeneous platoon. Each following vehicle in the platoon can use the communication equipment to receive the information of the leading vehicle and its preceding adjacent one. The vehicles in the platoon are dynamically decoupled and have different dynamic parameters. Each vehicle solves a local optimal control problem independently. The cost function of each vehicle’s local optimal control algorithm is designed with traceability as the control objective, and its asymptotic stability is guaranteed by using the terminal constraint method. In addition, the timestamps of all vehicles in the platoon are synchronous, which means that in each sampling period, a specific vehicle in the platoon cannot obtain the solution results of other vehicles’ local optimal control problems at the current sampling moment. Under this restriction, the constraints that each vehicle needs to meet to realize the platoon’s string stability are also designed. Finally, the simulation results show the effectiveness of the algorithm.

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The paper uses the productivity index based on data envelopment analysis (DEA) to calculate the total factor productivity (TFP) from 2008 to 2014, and also compares the differnces of TFP changes in three regions: eastern, central and western part. . Then we use the panel data model to seek and discuss the factors affecting the regional difference of total factor productivity growth. Results indicate that Chinese information service industry's total factor productivity shows a rising trend; the investment on education level and information level has a significant role in promoting the improvement of technological progress, technology efficiency and productivity; in addition, R&D, government behavior and urbanization are the important factors that affect regional difference of the development of Chinese information service industry.

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