自动代客泊车技术发展现状及趋势分析

自动代客泊车被认为将是最先大规模商业化落地的L4级自动驾驶系统之一,具有广阔的应用前景,逐渐成为行业研究的重点和热点。重点分析了自动代客泊车的市场需求、政策环境、技术环境、技术演进过程、系统方案,对其发展趋势做出预测,并对未来代客泊车产业发展提出建议。     

驻车拉索固定支架断裂的故障改进研究

某车型在盐城试验场进行耐久试验时出现了驻车拉索固定支架断裂的质量问题,故障里程为1 200 km,同时在高寒试验时也出现了同样的故障,文章以该故障为基础,通过对驻车拉索的工作原理以及在整车环境的运行状态进行分析,提出了多种改进方案。经改进件的试制、装车和道路耐久路试等程序,验证改进方案可行,该故障得到了有效解决,未将该隐患输出到市场中,避免了市场车辆可能出现的抱怨,同时对类似故障模式的预防也有很好的设计借鉴意义。     

探究居住区停车共享存在问题及对策

文章采用实地观察统计与调查问卷的方法针对重庆市停车共享现状展开调研,针对居住区停车泊位使用特性,对重庆市2处居住区及附近商场开展了5天的停车状况调查,整理数据分析居民区停车共享可行性。文章对重庆市江北区、渝北区、渝中区、南岸区、大渡口区、沙坪坝区共计12个已使用共享停车这种模式的停车场发放问卷调查,从建设运营方、提供车位共享方、共享停车使用方、不使用停车共享方四方发放共享停车满意度调查问卷,整理问卷结果,从技术、用户、管理三方面提出停车共享存在的问题并给出相应对策。     

Establishing parking generation rates/models of selected land uses for Palestinian cities

Estimating parking demand in Palestine requires more oriented studies towards parking generation to enrich transportation planning, design, and management. Using regional or international models and rates of parking demand may not be appropriate for Palestine. This research is conducted to establish a reference for provision of parking supply for three major types of land uses, which are residential, office, and retail.Seventy-three sites of different land uses were selected through field investigations, interviews, and availability of information for each site. The study covered all main cities in the West Bank, Palestine. Data collection was conducted manually, which contains site characteristics and average of two-day parking counts during three periods (AM, PM, and Peak of the Development).Numerous models and rates were investigated yielding variable statistical accuracies. Most appropriate statistical models/rates were summarized and highlighted for each type of land use, and parking generation models with acceptable statistical significance were recommended, otherwise, parking generation rates were recommended. Simple linear regression, natural logarithmic linear regression, and power were the forms of the recommended models for the studied land uses.This study forms the first step of a future Palestinian “Parking Generation Manual” that should contain various local land use types.     

Turning meter transactions data into occupancy and payment behavioral information for on-street parking

Over 95% of on-street paid parking stalls are managed by parking meters or kiosks. By analyzing meter transactions data, this paper provides a methodology to estimate on-street time-varying parking occupancy and understand payment behavior in an effective and inexpensive way. We propose a probabilistic payment model to simulate individual payment and parking behavior for each parker. Aggregating the payment/parking of all transactions leads to time-varying occupancy estimation. Two data sets are used to evaluate the methodology, parking spaces near Carnegie Mellon University (CMU) campus, and near the Civic Center in San Francisco. The proposed model generally provides reliable estimations of occupancies at a low error rate and substantially outperforms other naive models in the literature. From the results of the experiments we find that people generally tend to slightly underpay in CMU area, whereas for Civic Center area, payment behavior varies by time of day and day of week. For Fridays, people generally tend to overpay and stay longer in the mornings, compared to underpaying and parking for shorter durations in the late afternoons. Parkers’ payment behavior, in general, is more variable and noisier around Civic Center than around CMU. Moreover, we explore the effective granularity, defined as the highest spatial resolution for this model to perform reliably. For CMU areas, the effective granularity is around 10–20 spaces for each block of streets, while it is 150–200 spaces for the Civic Center area due to more random parking behavior.     

Dynamic pricing and reservation for intelligent urban parking management

Despite rapid advances of information technologies for intelligent parking systems, it remains a challenge to optimally manage limited parking resources in busy urban neighborhoods. In this paper, we use dynamic location-dependent parking pricing and reservation to improve system-wide performance of an intelligent parking system. With this system, the parking agency is able to decide the spatial and temporal distribution of parking prices to achieve a variety of objectives, while drivers with different origins and destinations compete for limited parking spaces via online reservation. We develop a multi-period non-cooperative bi-level model to capture the complex interactions among the parking agency and multiple drivers, as well as a non-myopic approximate dynamic programming (ADP) approach to solve the model. It is shown with numerical examples that the ADP-based pricing policy consistently outperforms alternative policies in achieving greater performance of the parking system, and shows reliability in handling the spatial and temporal variations in parking demand.     

别克荣御轿车双驻车辅助系统

主要阐述双驻车辅助系统(DPA)的结构及工作原理,对其电路工作情况进行了分析,介绍了该系统进行故障自诊断的方法及步骤。     

US residential charging potential for electric vehicles

We assess existing and potential charging infrastructure for plug-in vehicles in US households using data from the American Housing Survey and the Residential Energy Consumption Survey. We estimate that less than half of US vehicles have reliable access to a dedicated off-street parking space at an owned residence where charging infrastructure could be installed. Specifically, while approximately 79% households have off-street parking for at least some of their vehicles, only an estimated 56% of vehicles have a dedicated off-street parking space – and only 47% at an owned residence. Approximately 22% vehicles currently have access to a dedicated home parking space within reach of an outlet sufficient to recharge a small plug-in vehicle battery pack overnight. Access to faster charging, required for vehicles with longer electric range, will usually require infrastructure investment ranging from several hundred to several thousand dollars, depending on panel and construction requirements. We discuss sensitivity of results to uncertain factors and implications for the potential of mainstream penetration of plug-in vehicles.     

Parking Spaces Repurchase Strategy Design via Simulation Optimization

Because of the rapid increase of vehicle numbers and land values, there is an increasing shortage in the supply of parking facilities in many cities. In many parking lots, residential drivers bought private parking spaces with high prices to ensure that they have spaces to park at any time. Recently, some parking lot operation companies plan to temporally repurchase a few private parking spaces back during certain time periods in a day and sell these places to public users to fully utilize the limited parking resources. How to choose the repurchase amounts and stopping time so as to maximize the profit then becomes an important problem. To solve this problem, a Gaussian mixture model is first proposed in this article to describe the time-varying arriving/departing behaviors of drivers and meanwhile the stochastic constraints of the profit maximization problem. Then, the expected optimal repurchase amounts and stopping time are estimated via simulation optimization. This new approach not only provides a useful statistical tool for parking spaces modeling but also overcomes several key limitations of current queuing based methodologies. Particularly, it emphasizes how to model drivers' behaviors on a small time-scale and explains the resulting benefits.     

Assessing transportation user benefits with maximum trip lengths

Maximum time lengths of urban trips can be used to calculate major user benefits of transportation improvements. These benefits include those associated with reduced cost of travel, those associated with travel to additional destinations, and those associated with improved quality of destinations. Maximum trip lengths can be measured using techniques of psychological scaling.