Optimization of Dynamic Parking Guidance Information for Special Events

Yun

Transportation Research Record: Journal of the Transportation R

2014

The travel time distribution under interrupted flow based on radio frequency identification–detected data is analyzed. The urban road network studied is in downtown Nanjing, Jiangsu Province, in China, where video cameras and radio frequency equipment are installed at some arterial links to acquire traffic flow data including vehicle type, passing time, and spot speed. On the basis of the radio frequency identification data, the travel time distribution under interrupted flow shows a bimodal curve instead of a unimodal curve. This finding suggests that travel times under interrupted flow are not independent and identically distributed and can be divided into two components, the uninterrupted component and the interrupted component, according to whether vehicles experience intersection control delay. Six convex distribution models are presented, and an expectation–maximization algorithm is adopted to obtain the best distribution for each link unit. The results indicate that travel time under interrupted flow generally follows a bimodal distribution. The parameters of the models can distinguish travel times between those encountering delay and those without delay. This finding demonstrates that intersection control delay plays a predominant role in travel times under interrupted flow. Two main travel time reliability indexes under interrupted flow obtained by the parameters of the bimodal distribution, expected travel time and RATIO, are presented as applications. Expected travel times indicate the average levels of travel times of two independent components, and RATIO represents the ratio of the uncertain part of the travel times. The analysis indicates that these two indexes can capture the characteristics of interrupted-flow travel time reliability, which is mainly caused by link length, number of intersections, and mixed traffic flow.

mentioning

confidence: 99%

Travel Time Distribution under Interrupted Flow and Application to Travel Time Reliability

Yun

Transportation Research Record: Journal of the Transportation R

2014

“…Previous work zone driver behavior model calibration studies are similar in that they all agree that desired time headway (CC1) and longitudinal following threshold (CC2) are the parameters that should be calibrated [9,14,31]. Introducing a second vehicle class (i.e., trucks) to the calibration process doubles the size of the solution region or search space for optimal driver behavior parameters, and there is a trade-off between the dimension of search space and the time required to identify optimal solutions.…”

Section: Framework For Determining Driver Behavior Parametersmentioning

confidence: 89%

“…To the best of the authors' knowledge, this is the first paper to investigate the PSO algorithm for the calibration of driver behavior model parameters. Particle swarm optimization is used to develop train timetables [29], optimize the structure of short-term traffic flow prediction models [30], optimize traveler information systems [31], and to optimize the vertical alignment of roadways to reduce travel time, fuel consumption, and costs associated with the maintenance of pavements [32].…”

Section: Differentiation From Previous Literaturementioning

confidence: 99%

Driver Behavior Models for Heavy Vehicles and Passenger Cars at a Work Zone

Mahmood

Kianfar

2019

Sustainability

Traffic impact assessment is a key step in the process of work zone planning and scheduling for transportation agencies. Microscopic traffic simulation models enable transportation agencies to conduct detailed analyses of work zone mobility performance measures during the planning and scheduling process. However, traffic simulation results are valid only when the simulation model is calibrated to replicate driver behavior that is observed in the field. Few studies have provided guidance on the calibration of traffic simulation models at work zones and have offered driver behavior parameters that reproduce capacity values that are observed in the field. This paper contributes to existing knowledge of work zone simulation by providing separate driver behavior model parameters for heavy vehicles and passenger vehicles. The driver behavior parameters replicate the flow and speed at the work zone taper and at roadway segments upstream of the work zone. A particle swarm optimization framework is proposed to improve the efficiency of the calibration process. The desired time headway was found to be 2.31 seconds for heavy vehicles and 1.53 seconds for passenger cars. The longitudinal following threshold was found to be 17.64 meters for heavy vehicles and 11.70 meters for passenger cars. The proposed parameters were tested against field data that had not previously been used in the calibration of driver behavior models. The average absolute relative error for flow rate at the taper was 10% and the mean absolute error was 54 veh/h/ln. The GEH statistic for the validation dataset was 1.48.

Transportation Research Record: Journal of the Transportation R

“…This technique aims to help vehicles reduce the cost of cruising for parking. Conventional PGI systems rely on variable message signs (VMSs) located on the roadside or at key intersections ( 13 , 16 , 17 ). VMSs disseminate dynamic information about available parking lots, but do not include information about the routes to them.…”

mentioning

confidence: 99%

Parking Planning With Route Assignment for Planned Special Events

Zheng

Cao

Shen

et al. 2022

During a planned special event (PSE), vehicular and pedestrian movements are concentrated around the PSE venue for short periods, leading to potential conflicts and safety issues. Vehicles tend to park as close as possible to the venue for the convenience of attendees. Taking into account the characteristics of PSE traffic patterns, a strategic vehicle parking planning model is proposed to integrally optimize the assignment of parking lots and inbound/outbound routes around the venue. Two prioritized objectives were considered for traffic safety and for the convenience of attendees. The proposed model was first validated in a small-scale example, and then adopted in a real-world case that took place in Taiyuan, China. The resulting parking plan presented an efficient reduction in the conflict points between vehicular and pedestrian movements, leading to an acceptable average walking distance for attendees. To evaluate the impact of different management preferences on the parking plan, a series of weights for conflict points were set according to potential conflict locations, occurrence times, and types. The results demonstrated that the number of conflict points with higher weights could be effectively reduced by the parking plan.