The 3D-simulation implementation of parking guidance system

A parking guidance and information system for the Shinjuku area of Tokyo is described as Japan's first parking guidance and information system (PGIS) to have a full-fledged guidance function. The concept of the Shinjuku area parking guidance and information system is outlined. The surveys conducted before and after the introduction of the Shinjuku area PGIS confirmed its effectiveness in: (1) improving the convenience of users; (2) reducing on-street parking; (3) enhancing the order of traffic in the Shinjuku area; (4) absorbing into off-street parking lots those cars parked on-street for a short time; and (5) equalizing the number of cars parked between available parking lots. The measures to be taken for further improving the Shinjuku area PGIS are presented at the end.

A feasibility analysis and concept plan was recently developed for a parking guidance system (PGS) in downtown San Jose, California. As San Jose continues to grow, real-time parking management is needed to manage the increased demand. A PGS will direct motorists to city and privately owned parking facilities. The system will inform drivers of parking locations and availability with electronic message signs located at key locations on major streets and freeway exit ramps. Having timely and accurate information will allow drivers to make informed decisions about where to park, thus increasing the efficiency of parking facilities. The concept was developed under the direction of the city's Department of Transportation and was finalized in September 2000. With the support of city officials and downtown stakeholders, the development of plans, specifications, and engineering began in late 2000. Funding was set aside for the design and initial implementation of the program. The concept, design, and issues associated with implementation of a PGS are discussed. Following deployment, San Jose's PGS will be one of the largest applications of real-time parking management in North America.

With the development and application of intelligent transportation systems (ITS), parking guidance and information system (PGIS) has become a hot topic for research and applications. Parking variable message sign (parking VMS) is the most common form of PGIS currently in use, particularly in providing the space availability information to en-route drivers. The aim of this study is to model drivers' responses to the parking VMSs under various parking information in a dynamical way. To ensure the guiding efficiency and assist drivers to identify parking lots with vacant spaces, the display strategies of parking VMS were studied. A discriminated release strategy with a space occupancy indicator (SOI) was then proposed to determine the display content on the parking VMS, in which an agent-based simulation was introduced to incorporate both parking choice model and traffic assignment algorithm dynamically. Guiding reliability and display strategies were further analyzed to attain a discriminated release strategy with SOI effectively. The results indicate that the guiding reliability was improved by reducing the SOI value of the corresponding parking lot, and the relatively uniform guiding reliabilities of all parking lots were attained by modifying SOI values iteratively. Additionally, the performance by incorporating the waiting time into the parking choice model was investigated and recommended. The discriminated release strategy presented in this study will assist in designing and operating urban PGIS.

The primary objective of this work is to design a parking guidance system to reliably detect entering/exiting vehicles to a parking garage in a cost-efficient manner. Existing solutions (inductive loops, RFID based systems, and video image processors) at shopping malls, universities, airports etc., are expensive due to high installation and maintenance costs. There is a need for a parking guidance system that is reliable, accurate, and cost-effective. The proposed parking guidance system is designed to optimize the use of parking spaces and to reduce wait times. Based on a literature review we identify that the ultrasonic sensor is suitable to detect an entering/exiting vehicle. Initial experiments were performed to test the sensor using an Arduino based embedded system. Detection logic was then developed to identify a car after analyzing the initial test results. This logic was extended to trigger a camera to take an image of the vehicle for validation purposes. This system consists of Arduino, ultrasonic sensor, and a temperature sensor. It was installed and tested in Richard Beard Garage at the University of South Florida for five days. The test results of each trial are provided and average error for all the trials is calculated. The error cases occur due to golf carts, straddling cars on both entry/exit lanes, and people walking under the sensor. The average error of the system is 5.36% over five days (120 hrs). The estimated cost for one detector per lane is approximately $30.

This paper proposes a complete set of Urban Parking Guidance and Information System, which includes Parking Subsystem and City Parking Subsystem. The system adopts wireless sense network based on ZigBee technology for the communication network. The parking information terminals that set up in the parking areas automatically identify the parking vehicles and upload the parking information. After processing the data, the Central Control Module would distribute the parking information by LCD screens for the drivers. In terms of parking supply and demand status, the system sends the separately parking information to the corresponding phone number. The system achieves barrier-free intelligent parking management by realizing functions such as three ways of releasing the information of parking lots, inquiry of parking location and convenient register operation.

Study on demand and characteristics of parking system in urban areas: A review

Parking Guidance and Information System called PGI System has been recently introduced in many cities in Japan. The PGI System is expected to reduce time for waiting a driver to park his/her car and also to contribute to smooth the peak demand for each of parking spaces. In this study, a current state of the art related to PGI System is reviewed referring to the results from the special session entitled "On User's Evaluation and Response to PGI System". The effects of the PGI System in Kofu on the user's behavior are empirically analyzed. A discriminant analysis is applied to an identification of the factors determining the use of parking information. Multinominal logit models of parking space choice behavior are calibrated to express the effect of offering information whether a parking space is full or not.

Reservation berth is one of most important part of parking guidance. This paper studies a reservation strategy model of finite berth. It develops reservation strategy of finite berth. Based on the every aspect of life, the strategy can obtain the last reservation berth by game- playing algorithm considering the controlling to berth of guidance system and park. This paper develops a game-playing algorithm of reservation berth by analyzing the four possible strategies: reserve strategy, lag reserve, advance breach of faith, and berth occupying. Simulation experiments show this reservation strategy can reserve berth having no use for accurate reserve berth and using parameters, which is more near to real life. It is of use value.

This paper proposes a new method based on multiple attribute decision making to search for the optimal parking space in a parking lot. The advantages and limits of different kinds of property weights are investigated in this paper. By improving the limits of subjective weight and combining subjective weight with objective weight, we get an integrated weight. Using this hybrid weight, we introduce how to apply multiple attribute decision making to search for the optimal parking space. Experiments show that this method has a satisfying performance and can find the real-time optimal parking space. The proposed method can be applied to city parking guidance and information system.

Microscopic simulation models have been widely used as tools to investigate the operation of traffic systems and different intelligent transportation systems applications. The fidelity of microscopic simulation tools depends on the driving behavior models that they implement. However, current models commonly do not consider human-related factors, such as distraction. The potential for distraction while driving has increased rapidly with the availability of smartphones and other connected and infotainment devices. Thus, an understanding of the impact of distraction on driving behavior is essential to improve the realism of microscopic traffic tools and support safety and other applications that are sensitive to it. This study focuses on car-following behavior in the context of distracting activities. The parameters of the well-known GM and intelligent driver models are estimated under various distraction scenarios using data collected with an experiment conducted in a driving simulator. The estimation results show that drivers are less sensitive to their leaders while talking on the phone and especially while texting. The estimated models are implemented in a microscopic traffic simulation model. The average speed, coefficient of variation of speed, acceleration noise and acceleration and deceleration time fractions were used as measures of performance indicating traffic flow and safety implications. The simulation results show deterioration of traffic flow with texting and to some extent talking on the phone: average speeds are lower and the coefficient of variation of speeds are higher. Further experimentation with varying fractions of texting drivers showed similar trends.

In tourist destinations with limited road and parking capacities, seasonal surges in private vehicle traffic often cause external diseconomy, including congestion and traffic calming issues. Conventional infrastructure-based solutions for tourist parking management are frequently too large or inflexible to address spatially and temporally localized problems effectively. This study investigates a compact, deployable parking guidance system designed to mitigate traffic issues caused by private tourist vehicles accessing a narrow street. A field experiment was conducted in Apr 2025 at Higashi-Hazu Beach, Nishio City, Japan. A real-time vehicle counting system is developed for an ungated seaside parking lot using only two roadside Light Detection and Ranging (LiDAR) sensors to monitor the entries and exits at access points. Accuracy validation against video recordings confirms consistent detection performance even under high-traffic and mixed pedestrian conditions. To proactively guide drivers, a Variable Message Sign (VMS) dynamically displays the congestion status (“Congested”, or “Full”) at a key intersection preceding a narrow access street. The display content is automatically updated based on real-time vehicle counts obtained from the LiDAR sensors. Comparative analysis between periods with and without the VMS reveal a significant increase in vehicles diverting to a fringe parking lot during “Congested” conditions when the sign is active. This study demonstrates that a compact and deployable LiDAR-based guidance system can affect driver behavior and contribute to more sustainable parking management in tourism-heavy regions, mainly in areas where the conventional methodology is too extensive to implement.

In this paper, we build parking policy analysis models (PPAM) which can evaluate the effects of parking guidance and information system introduction. Following abrief review of research literature, we develop our models incorporating parkinglocation choice model, dynamic micro simulation and parking performance model, based on a set of parking inventory data collected in Tama newtown center. In conclusion, the PPAM developed in this study have enough power of reproducing present and future parking situation in terms of parking waiting queuing time and parking demand allocation.

Cars have become an indispensable way for people to travel now. While bringing people a convenient and fast way to travel, they also bring a lot of problems and hidden dangers to the current traffic. Parking is one of the problems that need to be solved urgently. In this paper, on the basis of the traditional parking method, the intelligent parking guidance system developed by the improved bee colony algorithm is used to make full use of the characteristics of the bee colony algorithm to reasonably plan the user's parking path selection, which can solve the problem of user parking to a large extent. In this experiment, an improved bee colony algorithm is proposed, and an intelligent parking induction model based on the improved bee colony algorithm is established. Based on the change of the pheromone of the bee colony over time, it can effectively plan the user's parking path and parking lot vacancies. The experimental results show that the improved bee colony algorithm has great advantages over the traditional algorithm in terms of efficiency and quality, and different factors in the algorithm will have an impact. Within 1–2 time, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$a$</tex> shows a downward trend, while β shows an upward trend., in 2–5 time, on the contrary, it greatly reduces the user's parking time, and also enhances the safety to a certain extent, and realizes the design and development of the intelligent parking guidance system.

Notice of Violation of IEEE Publication Principles Free Parking Space Prediction and Reliability Based on Big Data Analysis by Chao Zhang, Xianwei Wang, Zhonjing Ma, in IEEE Access, Vol 8, 2020 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Data-driven Dynamic Path Optimization and Parking Guidance Models and Algorithms by Zhenzhen Yang, in the Doctoral Thesis, Beijing Jiaotong University, September 2019 The number of free parking spaces (FPSs) is highly dynamic and stochastic, calling for a parking guidance model that enables the driver to find the right parking lot. This paper explores the distribution of FPSs number in parking lots, predicts the number of FPSs, and proposes a parking guidance model with a solving algorithm. Firstly, the number of FPSs from several parking lots was subjected to big data analysis, revealing that the hourly number of FPSs obey similar trends on different weekdays. On this basis, the data on the FPSs number of the parking lots were classified by hourly, weekly and holiday features. Whereas the FPSs number obeys the normal distribution, a parking guidance model was established with the most reliable path to forecast the number of FPSs. Then, the solving algorithm was proposed based on the reliability boundary. Finally, the effectiveness of the model and algorithm was verified through simulation. Compared with the actual data, the prediction accuracy of the model is more than 95%. The research results shed new light on the development of parking guidance systems.

Parking guidance system, as one of the main ways to improve urban traffic and improve people’s travel efficiency, has become a hot research topic at present. Sufficient information on the number of empty parking spaces has become a necessary condition for relevant research, which is mainly obtained by sensors at the entrance and exit of the car park. However, because of the economic cost, installation and construction, it is impossible to deploy the sensor in every parking lot in the city, so there will be a large area of parking data missing in the city.This paper presents a new technology to repair the parking lot data with DCGAN(Deep Convolutional Generative Adversarial Networks). First, the parking lot is classified by the high-dimensional clustering in the geographical space and the parking data of the existing parking lot is mapped to the empty car rate curve image. The same kind of car parking rate image has been set up in DCGAN to generate the empty car rate image of this type of parking lot. Finally, the 2-D empty car rate image is mapped to one-dimensional time series. Experiments show that DCGAN has achieved good results in data repairing of parking lot.