Double Parking Research Articles

Prospects and Sustainability in Car Parking Systems in select Neighbourhoods of Port Harcourt Municipality

Well-organised parking in cities promotes urban environmental sustainability and livability. The study aimed to explore and sustain the prospects of parking systems in neighbourhoods of Port Harcourt Municipality, Nigeria. The objectives were ascertaining the parking systems of neighbourhoods of the study area, identifying prospects of parking systems of neighbourhoods of the study area, and identifying measures to sustain the prospects of parking systems in neighbourhoods of the study area. The study adopted a quantitative approach using a descriptive research design. The study employed stratified and simple random sampling techniques to select sampled neighbourhoods and respondents for the study. A stratified sampling technique was employed to group the neighbourhoods into 3 strata (high, medium and low densities). 3 neighbourhoods were selected to represent each stratum namely: PH Township (high density), Orominike-D/Line (medium density) and Orije Layout- Old GRA (low density) for the study. A total of 397 respondents were determined and interviewed using the Taro Yamane formula at a 5% precision level. The study revealed that there exist on-street and off-street parking systems with various parking types including parallel, perpendicular, echelon angled and double-parking types. These parking systems are both off-street and on-street types. The prospects of the parking systems parking spaces in the building premises, along the carriageway on the street, in front of the building, space in other premises, public places and open spaces within the neighbourhoods. These conditions have promoted orderliness, safety, and security of road users such as residents, businesses, and visitors. The study found measures to sustain the prospects are creating more parking spaces/lots and designate parking area in the neighbourhoods, building a paid-parking facility in the neighbourhoods, marking parking areas clearly, government should enforce provision of parking spaces on premises, avoiding parking in the front of buildings where the space is inadequate, stop using designated parking spaces for other purposes, parkers to stop double parking in the streets, and impound broken-down vehicles in the streets. Therefore, to further sustain and enhance the prospects of parking systems in the neighbourhoods, the study recommended all government agencies should synergise to prepare parking plans for neighbourhoods. identify vacant spaces at strategic locations in the neighbourhoods where off-street parking facilities will be provided, clearly mark out designated parking spaces and parking lots along the streets, introduce a paid-parking system in the neighbourhoods, introduce one-side (parallel or perpendicular) parking along streets that are narrow in width, regulate and enforce the elimination of street trading, indiscriminate parking, removal of bad vehicles and discourage double parking in the neighbourhoods.

Real-time anomaly detection of short-term traffic disruptions in urban areas through adaptive isolation forest

The escalating congestion impacts of short-term traffic disruptions, such as double parking or short-duration work zones, are gaining increased attention. This study introduces an enhanced isolation forest-based unsupervised anomaly detection algorithm to detect short-term traffic disruptions in urban areas. To enable the detection in real-time, a sliding window approach is introduced to allow the streaming data to be read and processed according to the window size. An adaptive threshold that automatically adjusts itself to overcome the limitations of the miss rate on local anomalies is shown to further enhance the model predictions. The proposed algorithm is empirically validated on four study sites in Manhattan, New York City. The experimental results demonstrate that the proposed unsupervised algorithm can effectively detect different types of traffic anomalies including accidents, work zones/road closures, traffic jams, double parking events and police activities. On all sites, the average detection rate is 81.1% for traffic jams and 89.6% for police activities, respectively. For three out of the four sites, the detection rate ranges from 71.4% to 100% for accidents, work zones and double parking. An optimizer using high-pass filter is also presented to further improve off-line detection. The primary advantages of this proposed computationally-efficient method are that its only required data input is travel time information and that it does not need labeled data for training, which make it highly deployable for real-time operational applications and can be easily adopted by other cities.

Effects of mobile phone using on driving behavior and risk of traffic accidents

In this study, a questionnaire was made to find out the behavior of drivers towards the use of the mobile phone while driving, therefore representative samples were taken from different regions of Irbid Governorate, which included the Department of Vehicle Licensing, universities and commercial centers. As a result of the research, it was found that the most important factor that affects driver's behavior is the purpose of their mobile phone use whether making calls, sending text messages, or even browsing social media applications, secondly, the drivers' reaction to incoming calls whether receiving or ignoring calls. Or parking aside to respond, third comes the driver's history of traffic violations or previous traffic accidents. It was also concluded that about 22% of respondents who frequently use cellphones while driving, take calls while they drive, in comparison with just 1% of them who rarely use mobile phones while driving or just take calls for emergency, on the other hand a large percentage of 89% of respondents who always use their cellphones while driving use all of the means of taking or making calls, texting or browsing social media while driving, in comparison with 1% and 5% of them who never or rarely use cellphone while driving respectively. Furthermore, and according to the results of respondents with previous violations or tickets, it was found that people who never use cellphones while driving contribute in nearly no violations if compared to people who always use their phones who seem to commit many types of violations such as speed violations, red light crossing, double parking, cellphone using while driving tickets or even traffic accidents.

Prediction model for drivers' tendency to perpetrate a double parking violation on urban trips

Illegal parking during peak hours and on heavily traveled streets can significantly impact the severity of traffic congestion and related problems. A double parking violation is among the most significant instances of illegal parking. Double parking violations reduce road capacity and increase traffic congestion. Intensified traffic congestion also increases travel time and reduces road user satisfaction. Thus, the management of double parking violations is critical to managing traffic congestion in urban streets. In this study, the factors influencing the drivers' tendency to perpetrate a double parking violation were identified using the ordinal logistic regression model in the central area of Mashhad. Then, by redesigning the ordinal logistic regression model and utilizing the identified effective factors, a model was developed to predict the level of drivers' propensity to perpetrate a double parking violation during urban trips. Mashhad is one of the largest cities in Iran, and its central district experiences a high volume of daily traffic. The results indicated that parking duration is the main factor affecting drivers' propensity to perpetrate a double parking violation. Driver education level and driver presence in the vehicle ranked second and third, respectively. The P-value in the goodness-of-fit test was obtained at less than 0.05, indicating the designed model's acceptable accuracy.

Authorized Vehicles Only: Police, parking, and pedestrian access in New York City

Sidewalks and crosswalks do not benefit pedestrians if they are blocked by automobiles. In New York City, local media have documented that cars outside of law-enforcement offices routinely park on sidewalks and in crosswalks. This study systematically and longitudinally pursues this topic by tracking the geographic extent of this obstructive parking via in-person observation of the streets surrounding all 77 New York Police Department (NYPD) station houses, across all five boroughs. Combined with review of historical street imagery, this approach reveals widespread and longstanding parking on sidewalks, and to a lesser extent, in crosswalks. Of 77 NYPD station houses, 70 (91%) exhibited parking of at least one of these kinds, with sidewalk parking often extending along the entire block (and not simply in front of station houses), on adjacent blocks, and on both sides of the street. This renders many sidewalks impassable – forcing pedestrians into traffic – and in many cases directly abuts residences and businesses, curtailing access to such destinations. Longitudinally, such obstructive parking was present across 82% of 703 street-imagery data points, indicating this has largely become the default (and not occasional) use of adjacent sidewalks. In-person observation also demonstrated other ways this parking has had negative effects surrounding NYPD station houses, including double parking, obstruction of bus and bike lanes, and blocking of fire hydrants. These findings broaden the study of pedestrian accessibility and safety beyond the quality and design of sidewalks and intersections, to include chronic automotive obstruction, and indicate that parking behavior surrounding public-sector offices, if left unchecked, significantly degrades walkability.

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Orderly Britain: How Britain has resolved everyday problems, from dog fouling to double parking, By TimNewburn and AndrewWard, Robinson. 2022. pp. 360. £18.99 (hbk). ISBN: 978‐1472137968. £8.99 (ebk). ISBN: 978‐1472137975

Orderly Britain: How Britain has resolved everyday problems, from dog fouling to double parking, By TimNewburn and AndrewWard, Robinson. 2022. pp. 360. £18.99 (hbk). ISBN: 978‐1472137968. £8.99 (ebk). ISBN: 978‐1472137975

A methodology for assessing the urban supply of on-street delivery bays

The loading and unloading operations carried out by transport and logistics operators have a strong impact on city mobility if they are not performed correctly. If loading/unloading bays, i.e., delivery bays (DB), are not available for freight vehicle operations, operators may opt to double park or park on the sidewalk where there is no strong enforcement of these laws, with significant impact on congestion. This paper proposes a methodology for verifying and designing the number of delivery bays needed for freight vehicles for not interfere with cars or pedestrians. The methodology consists of two stages: in the first stage, an initial estimation is made using queueing theory. Subsequently, in the second stage, using such tentative scenario, in order to take into account the system stochasticity involving different entities, a discrete event simulation is performed to more realistically verify and upgrade (if necessary) the number of delivery bays to obtain the expected outcomes. The methodology was applied in the inner area of Santander (Spain). The study area was subdivided into 29 zones where the methodology was applied individually. The results indicated that none of these zones currently have an optimal number of delivery bays to satisfy demand. In some zones, there is an excess of delivery bays, although in most of them, there is a deficit which can cause significant impacts on traffic. The method proposed can be an effective tool to be used by city planners for improving freight operations in urban areas limiting the negative impacts produced in terms of internal and external costs.

Affecting factors of double parking violations on urban trips

Double parking has many negative effects on the traffic indicators, such as travel time, road capacity, traffic congestion, traffic flow speed, and safety of traffic flow. Double parking activities are considered as drivers' driving behaviour. This study defines an index for estimating the likelihood of committing double parking called the NPC index. This parameter indicates a driver's visual search distance to find a vacant on-street parking space based on the number of cars parked on the curbside of the street. The metropolis of Mashhad has been selected as the case study of this research. The selected statistical sample consisted of 275 drivers who had violated the traffic rules by committing double parking in the central areas of Mashhad. The recorded values of the NPC index were clustered using the K-means clustering method, and also, other variables were classified. The factors affecting the NPC parameter were identified using the Mann-Whitney U and the Kruskal-Wallis statistical tests. Based on the results, the variables of educational degree, trip purpose, presence or absence of the driver, and parking duration were identified as the factors affecting the visual search distance to find a vacant on-street parking space. The categories of each of these factors were also ranked using the Mann-Whitney U and the Kruskal-Wallis statistical tests.

Double parking in New York city: a comparison between commercial vehicles and passenger vehicles

Double parking in New York city: a comparison between commercial vehicles and passenger vehicles

Freight Loading Space Provision: Evidence from the US

Abstract Limited freight loading space provision in city centers increases illegal loading behaviors such as double parking or parking in bicycle lanes or sidewalks. Such traffic violations have ca...

Effects of Road Traffic Congestion on Economic Activities of Dar es Salaam Region in Tanzania

The general objective of this study was to examine the effects of road traffic congestion on economic activities of Dar es Salaam Region in Tanzania. The findings show that congestion is caused by narrow roads, bad road conditions, rainfall, non-operating traffic lights, double parking, inadequate feeder-roads, road accidents, road work, many pedestrians crossing the road and many bumps in the roads. Also, congestion on average increases costs of fuel by Tsh. 32,167.00 paid from bus drivers’ pocket and reduces productive time of workers by 2.5 hours. Similarly, employees with formal employment got up between 3:00am and 4:00am early in the morning to avoid road congestion but due to unreliable transport services employee with income of Tsh. 90,000.00 spend 39% of the income as fare because they pay twice in a single journey. However, during their return home they are easily caught in congestion as they get home late at 22:00pm. Therefore, congestion affects the economy by reducing the turnover, profit margin and sales of individuals and in aggregates the economic activities of Dar es Salaam region. This study recommends that, roads be enlarged and pedestrian bridges, feeder-roads and bumps be constructed in a way that reduces congestion. Keywords: Road Traffic Congestion and Economic Activities DOI: 10.7176/JESD/12-6-05 Publication date: March 31 st 2021

Efficient loading and unloading operations via a booking system

Urban distribution of parcels and goods usually requires vehicles to temporarily stop at roadside to allow for the driver to perform the last leg of the delivery by foot. The stops take place in designated areas, called loading/unloading (L/U) areas, composed of one or more parking spots. In this paper the introduction of a booking system for the management of the L/U areas in a city center is studied as a way to eliminate, or at least substantially reduce, double parking. A booking management system and the related routing problem are presented. In this system, distributors book in sequence according to their preferences and routing constraints, but subject to the bookings that have already been placed. The solution provided by the booking system is discussed and compared with the current use of the L/U areas, where the distributors do not consider the availability of a parking spot and resort to double parking if none is available.

Illegal Use of Loading Bays and Its Impact on the Use of Public Space

Loading bays are public spaces reserved for the operation of freight vehicles, and it is well known that there are significant problems concerning their use due to non-compliance with existing regulations. Unlawful use of loading bays leads to double parking, or to parking on the pavement or in restricted areas. This article has two objectives: Firstly, the study and analysis of the use of loading bays (type of demand, parking duration, illegal use, etc.), as well as their use according to their morphology. Secondly, the quantitative assessment of the influence of illegal use with regard to the efficient use of public urban space. Illegal use is quantitatively assessed by calculating the number of loading bays that are used inappropriately and the surface area (m2) of public space used incorrectly. In the analysis carried out in the city of Santander (Spain), it can be observed that the urban morphology of loading zones influences their use: The greater the capacity of the loading zone, the less efficient is its use. Moreover, it is observed that the degree of illegal use within loading zones is very high and that illegally excessive parking durations have a greater impact on the use of the ground space than vehicle type.

Impeding access: The frequency and characteristics of improper scooter, bike, and car parking

Many cities are grappling with how to regulate new shared mobility modes, including dockless e-scooters and bikes (i.e., “micromobility”). Transportation planners in these cities are particularly concerned about micromobility parking regulations, which have implications for the safety and mobility of riders and the general public. In this research, we investigate the parking practices as well as the frequency and types of parking violations of three types of vehicles operating on city sidewalks and streets: e-scooters, bikes, and motor vehicles. We collected original data on 3666 e-scooters, bikes, motor vehicles, and sidewalk objects in Austin, TX, Portland, OR, San Francisco, CA, Santa Monica, CA, and Washington, DC, to examine micromobility and motor vehicle parking practices. We find that motor vehicles impede access far more (24.7%) than bikes (0.3%) and e-scooters (1.7%). Ride-hail and food delivery drivers disproportionately impede access. Motor vehicles often impeded other travelers' access when dropping off or picking up people or food while double parking, parking in “No Parking” areas, or blocking driveways. Our findings suggest that micromobility companies are just one of several technology-enabled transportation services that should motivate cities to rethink parking policies.

Machine vision based smart parking system using Internet of Things

It is expected that in the next decade, majority of world population will be living in cities. Better public services and infrastructures in the city are needed to cope with the booming population. City vehicles that cruising for parking have indirectly causing traffic, making one harder to travel around the city. Thus, a smart parking system can certainly lays the foundation to build a smart city. This paper proposed a cost-effective IoT smart parking system to monitor city parking space and provide real-time parking information to drivers. Moreover, instead of the conventional approach that uses embedded sensors to detect vehicles in the parking area, camera image and machine vision technology are used to obtain the parking status. In the prototype, twenty outdoor parking lots are covered using a 5 megapixel camera connected to Raspberry Pi 3 installed at the 5th floor of the nearby building. Machine vision in this project that involved motion tracking and Canny edge detection are programmed in Python 2 using OpenCV technology. Corresponding data is uploaded to an IoT platform called Ubidots for possible monitoring activity. An Android mobile application is designed for user to download real-time data of parking information. This paper introduces a low cost smart parking system with the overall detection accuracy of 96.40%. Also, the mobile application allows users to alert other car owners for any emergency incidents and double parking blockage. The developed system can provide a platform for users to search for empty car parking with ease and reduce the traffic issues such as illegal double parking especially in the urban area.

Demystifying Urban Curbside Freight Management: Strategic Incremental Approach from Washington, D.C.

Loading zones and commercial vehicle activity are issues in cities across the country including the District of Columbia. Like other major U.S. cities, the District Department of Transportation (DDOT) has tried a variety of initiatives to alleviate the strain commercial vehicle activity places on the overall transportation system. These include metering or otherwise pricing loading zones and parking, expanding the size and increasing the number of loading zones, increasing the number of metered parking spaces, extending loading and metering time periods, simplifying and standardizing truck parking rules, and encouraging nighttime or off-peak goods delivery. These initiatives have had some success but a more targeted approach was needed, especially to address non-commercial vehicles parking in loading zones and thus pushing delivery vehicles to double park while loading and unloading. As part of the parkDC: Penn Quarter/Chinatown performance parking pilot, DDOT attempted to reduce the number of illegally parked cars blocking loading zones by raising prices to the highest prevailing rate on the blockface and increasing loading zone availability by extending the hours of operation of loading zones. Moving forward, DDOT has identified several next steps including: oversize/overweight vehicle routing, increased and targeted loading zone enforcement, increased disincentives for violations, data-driven modifications to the loading zone program, and modifications to the pay-by-cell program to mitigate non-trucks paying to park in loading zones. As gaps in understanding curbside movement close with increased data availability, the District expects the programs associated with curbside management to evolve to reflect smarter policy, program, and management practices.

Consolidation and coordination of routes in urban distribution

In this dissertation, two relevant aspects of routing in the urban environment are studied. In the first part of the thesis, the implications of considering release dates when planning for delivery from distribution centers are discussed. The routing problems with release dates are contextualized in the class of routing problems, and in particular, in the lass of routing problems in which timing decisions must be considered. The Traveling Salesman Problem with release dates and completion time minimization is studied. Properties are introduced for the problem and a formulation is proposed. Two variants of a heuristic algorithm are tested against the optimal solution and shown to provide high quality results. The benefits of considering release dates are assessed by comparing the results with those obtained disregarding the release dates and delivering the parcels as soon as they arrive to the distribution center. The study on routing problems with release dates is then expanded to consider the stochastic and dynamic nature of the release dates. A reoptimization technique is proposed to tackle the dynamic aspect of the problem. Three reoptimization policies are proposed, with increasing reoptimization frequency, together with two models for the solution of the problem. The first is a stochastic model, considering the entire probabilistic information available for the release dates, and the second is a deterministic model, where a point estimation is used. The stochastic model is shown to perform better than the deterministic model, at the expense of the computational time required to evaluate any of the solutions explored. The second part of the thesis is focused on the management of the loading and unloading areas in the city center. Urban distribution requires vehicles to temporarily stop to perform the last leg of the delivery by foot. If a spot is not available, vehicles resort to double parking which is a known cause of road congestion. Two booking management systems and the arising routing problems are presented. The solutions provided by the two systems are compared with the current state of the distribution.

Exploring the Spatial Dependence and Selection Bias of Double Parking Citations Data

Parking violation citations, often used to identify factors contributing to parking violation behavior, offer one of the most valuable datasets for traffic operation research. However, little has been done to examine their spatial dependence caused by location-specific differences in features such as traffic, land use, etc., and potential selection biases resulting from different effects of traffic enforcement. This study leveraged extensive data on double parking citations in Manhattan, New York City, in 2015, along with other relevant datasets including land use, transportation, and sociodemographic features. Moran’s I statistics confirmed that double parking tickets were spatially correlated so that spatial lag and spatial error models were proposed to account for the spatial dependence of parking tickets to avoid biased estimates. To investigate whether selection bias exists in issuing tickets, we estimated the effects of parking ticket density and police precinct distance, when controlling for variables such as commercial area, truck activity, taxi demand, population, hotels, and restaurants. Parking ticket density and police precinct distance were used as indicators of the enforcement levels and coverage and were found to be statistically significant. This indicated the existence of selection bias due to heterogeneity in enforcement levels or coverage across different regions. Moreover, patrol patterns of traffic enforcement officers revealed that the majority had less than three daily patterns. These findings can assist with proper usage of the citation data by recommending that researchers and agencies consider spatial dependence as well as selection bias, and provide insights for parking violation management strategies.

Embedded Automated Vision for Double Parking Identification System

<span>The aim of this work is to assist the city administration issue which involve the traffic flow disruption in an urban area. One of the causes of traffic flow disruption is double parking; thus, in this work, an automated double parking identification and alert system was developed using embedded vision system and internet of things. A camera was utilized to acquire the image of a parking area, and the image was processed using Beaglebone Black processor. A computer vision algorithm was developed to process the image using background subtraction, region of interest identification, and color analysis. When a double parked vehicle is detected, the data was sent into the cloud automatically to alert the city administrator for further action. The developed system achieved 91% accuracy in detecting the traffic violation of double parking.</span>