Non-Connective Linear Cartograms for Mapping Traffic Conditions

2010 ◽  
pp. 33-50 ◽  
Author(s):  
Yi-Hwa Wu ◽  
Ming-Chih Hung
Keyword(s):  
Travel Time ◽  
Line Segment ◽  
Travel Speed ◽  
Visual Effects ◽  
Line Segments ◽  
Traffic Conditions ◽  
Visual Variables ◽  
Visual Variable ◽  
Visual Impact ◽  
Road Segments

Cartograms have the advantage of bringing a greater visual impact to map readers. Geographic locations or spatial relationships of objects are intentionally modified to suit the attributes pertaining to objects. In area cartograms, it is the size of the object that is intentionally modified, while in linear cartograms it is the length or direction that is intentionally modified. Traffic conditions in urban transportation networks are very dynamic phenomenon as they change through time. During highly congested hours, travel speeds are low, and travel times are long, and vice versa. In previous studies, traffic conditions were visualized by color and width of road segments. In this paper, non-connective linear cartograms are introduced as a way to represent traffic conditions. Non-connective linear cartograms are linear cartograms that do not show the connectivity between line segments. Lengths of road segments are modified to represent a specific theme in traffic conditions. When the length of road segments represents the congestion level, longer segments indicate higher congestion levels, meaning near road maximum capacity. When the length of the segments represents the travel speed, longer segments indicate higher travel speed and, therefore, shorter travel time. When the length of the segments represents the travel time, longer segments indicate longer travel time, and therefore lower travel speed. In the non-connective linear cartograms, lengths of line segments are not limited to the physical length of represented road segments. The flexibility of adjusting it makes length of line segment a visual variable just like color and width of line segment. All three visual variables work together to create dramatic visual effects and attract greater attention from readers.

Less is more: Simple stimuli provoke more variable search strategies.

2020 ◽  
Author(s):  
Anna Nowakowska ◽  
Alasdair D F Clarke ◽  
Jessica Christie ◽  
Josephine Reuther ◽  
Amelia R. Hunt
Keyword(s):  
Line Segment ◽  
Search Strategies ◽  
Complex Objects ◽  
Search Behaviour ◽  
Line Segments ◽  
Surface Level ◽  
Efficient Search ◽  
Less Is More ◽  
Dramatic Shift

We measured the efficiency of 30 participants as they searched through simple line segment stimuli and through a set of complex icons. We observed a dramatic shift from highly variable, and mostly inefficient, strategies with the line segments, to uniformly efficient search behaviour with the icons. These results demonstrate that changing what may initially appear to be irrelevant, surface-level details of the task can lead to large changes in measured behaviour, and that visual primitives are not always representative of more complex objects.

Study on Application of CAD Used in Visual Advertising Design

2014 ◽  
Vol 571-572 ◽  
pp. 768-771
Author(s):  
Jun Liu
Keyword(s):  
Computer Aided Design ◽  
Television Advertising ◽  
Paper Study ◽  
Application Technology ◽  
Visual Effects ◽  
3D Technology ◽  
Wide Range ◽  
Computer Aided ◽  
Visual Impact ◽  
Aided Design

The 3D technology currently has in various engineering fields have a wide range of applications, all the 3D visual effects technology can bring us visual impact, the use of 3D technology produced by the television advertising more easily accepted by the audience, this paper study on the 3D computer-aided design advertising design application technology.

Explanation for Neon Color Effect in Achromatic Line Segments on Chromatic Inducers Based on the Multiple Interpretation Hypothesis

2005 ◽  
Vol 101 (1) ◽  
pp. 267-282
Author(s):  
Seiyu Sohmiya
Keyword(s):  
Visual System ◽  
Line Segment ◽  
Color Contrast ◽  
Achromatic Color ◽  
Line Segments ◽  
Color Effect ◽  
Complementary Color ◽  
Multiple Interpretation ◽  
Color Induction ◽  
Simultaneous Color Contrast

In van Tuijl's neon configurations, an achromatic line segment on a blue inducer produces yellowish illusory color in the illusory area. This illusion has been explained based on the idea of the complementary color induced by the blue inducer. However, it is proposed here that this illusion can be also explained by introducing the assumption that the visual system unconsciously interprets an achromatic color as information that is constituted by transparent and nontransparent colors. If this explanation is correct, not only this illusion, but also the simultaneous color contrast illusion can be explained without using the idea of the complementary color induction.

ALPHA-REGULAR STICK UNKNOTS

2012 ◽  
Vol 21 (06) ◽  
pp. 1250059 ◽  
Author(s):  
CHRISTOPHER FRAYER ◽  
CHRISTOPHER SCHAFHAUSER
Keyword(s):  
Line Segment ◽  
Line Segments

Suppose Pn is a regular n-gon in ℝ2. An embedding f : Pn ↪ ℝ3 is called an α-regular stick knot provided the image of each side of Pn under f is a line segment of length 1 and any two consecutive line segments meet at an angle of α. The main result of this paper proves the existence of α-regular stick unknots for odd n ≥ 7 with α in the range [Formula: see text]. All knots constructed will have trivial knot type, and we will show that any non-trivial α-regular stick knot must have [Formula: see text].

Multi-itinerary optimization as cloud service

2021 ◽  
Vol 64 (11) ◽  
pp. 121-129
Author(s):  
Alexandru Cristian ◽  
Luke Marshall ◽  
Mihai Negrea ◽  
Flavius Stoichescu ◽  
Peiwei Cao ◽  
...  
Keyword(s):  
Travel Time ◽  
Time Windows ◽  
Algorithm Design ◽  
Cloud Service ◽  
Multiple Agents ◽  
Solution Quality ◽  
Traffic Conditions ◽  
Time Distance ◽  
And Performance ◽  
Vehicle Capacity

In this paper, we describe multi-itinerary optimization (MIO)---a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances.

scholarly journals Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions

2021 ◽  
Author(s):  
Swapneel R. Kodupuganti ◽  
Sonu Mathew ◽  
Srinivas S. Pulugurtha
Keyword(s):  
North Carolina ◽  
Travel Time ◽  
Queue Length ◽  
Simulation Software ◽  
Heterogeneous Traffic ◽  
Operational Performance ◽  
Travel Time Reliability ◽  
Traffic Conditions ◽  
Vehicle Delay ◽  
Blue Line

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.

Taxi Global Positioning System Data in Urban Road Network: A Methodology to Identify Key Road Clusters Based on Travel Speed–Traffic Volume Correlation

2021 ◽  
pp. 036119812110366
Author(s):  
Yi Li ◽  
Weifeng Li ◽  
Qing Yu ◽  
Han Yang
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Travel Speed ◽  
Detection Algorithm ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Mitigation Strategies ◽  
Operating Characteristics ◽  
The Road ◽  
Road Segments

Urban traffic congestion is one of the urban diseases that needs to be solved urgently. Research has already found that a few road segments can significantly influence the overall operation of the road network. Traditional congestion mitigation strategies mainly focus on the topological structure and the transport performance of each single key road segment. However, the propagation characteristics of congestion indicate that the interaction between road segments and the correlation between travel speed and traffic volume should also be considered. The definition is proposed for “key road cluster” as a group of road segments with strong correlation and spatial compactness. A methodology is proposed to identify key road clusters in the network and understand the operating characteristics of key road clusters. Considering the correlation between travel speed and traffic volume, a unidirectional-weighted correlation network is constructed. The community detection algorithm is applied to partition road segments into key road clusters. Three indexes are used to evaluate and describe the characteristic of these road clusters, including sensitivity, importance, and IS. A case study is carried out using taxi GPS data of Shanghai, China, from May 1 to 17, 2019. A total of 44 key road clusters are identified in the road network. According to their spatial distribution patterns, these key road clusters can be classified into three types—along with network skeletons, around transportation hubs, and near bridges. The methodology unveils the mechanism of congestion formation and propagation, which can offer significant support for traffic management.

A Duplicate Chinese Document Image Retrieval System Based on Line Segment Feature in Character Image Block

2011 ◽  
pp. 14-23
Author(s):  
Yung-Kuan Chan ◽  
Tung-Shou Chen ◽  
Yu-An Ho
Keyword(s):  
Image Retrieval ◽  
Line Segment ◽  
Document Image ◽  
Experimental Results ◽  
Document Images ◽  
Rapid Progress ◽  
Image Block ◽  
Line Segments ◽  
Image Retrieval System ◽  
On Line

With the rapid progress of digital image technology, the management of duplicate document images is also emphasized widely. As a result, this paper suggests a duplicate Chinese document image retrieval (DCDIR) system, which uses the ratio of the number of black pixels to that of white pixels on the scanned line segments in a character image block as the feature of the character image block. Experimental results indicate that the system can indeed effectively and quickly retrieve the desired duplicate Chinese document image from a database.

scholarly journals Travel Time Differences between Cargo Cycles and Cars in Commercial Transport Operations

2019 ◽  
Vol 2673 (8) ◽  
pp. 623-637 ◽  
Author(s):  
Johannes Gruber ◽  
Santhanakrishnan Narayanan
Keyword(s):  
Travel Time ◽  
Real Life ◽  
Time Difference ◽  
Significant Variable ◽  
Factors Affecting ◽  
Traffic Conditions ◽  
Time Performance ◽  
Trip Distance ◽  
Business Sectors ◽  
Lack Of Knowledge

Cargo cycles are gaining more interest among commercial users from different business sectors, and they compete with cars in urban commercial transport. Though many studies show the potential of cargo cycles, there is still a reluctance to deploy them. One possible reason for this is the lack of knowledge regarding their suitability in relation to travel time. Therefore, this study aims to explore cargo cycles’ travel time performance by quantifying the travel time differences between them and conventional vehicles for commercial trips. The authors compare real-life trip data from cargo cycles with Google’s routed data for cars. By doing this, the authors explore the factors affecting the travel time difference and propose a model to estimate this difference. The attributes for the model were selected keeping in mind the ease of obtaining values for the variables. Results indicate cycling trip distance to be the most significant variable. The study shows that expected travel time difference for trips with distances between 0 and 20 km (12.4 mi) ranges from -5 min (cargo cycle 5 min faster) to 40 min with a median of 6 min. This value can decrease if users take the optimal cycling route and the traffic conditions are worse for cars. Although what is an acceptable amount of travel time difference depends on the user, practitioners can be certain of the travel time difference they can expect, which enables them to assess the suitability of cargo cycles for their commercial operations.

Plate and line segment processes

1978 ◽  
Vol 15 (03) ◽  
pp. 494-501 ◽  
Author(s):  
N. A. Fava ◽  
L. A. Santaló
Keyword(s):  
Line Segment ◽  
Integral Geometry ◽  
Random Variables ◽  
Random Processes ◽  
Line Segments ◽  
Expected Values

Random processes of convex plates and line segments imbedded in R 3 are considered in this paper, and the expected values of certain random variables associated with such processes are computed under a mean stationarity assumption, by resorting to some general formulas of integral geometry.

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