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New Orleans MetropolitanBicycle and Pedestrian Plan

Regional Planning Commission

2005

Jefferson, Orleans, Plaquemines, St. Bernard and St. Tammany Parishes

September, 2006


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2005New Orleans Metropolitan Bicycle and Pedestrian Plan

Prepared by

Regional Planning Commission1340 Poydras Street, Suite 2100New Orleans, Louisiana 70112

email: [email protected] site: www.norpc.org

FHWA Contrect No. PL-0011 (025)State Project No. 736-36-0025

The preparation of this document was financed in part through grantsfrom the U.S. Department of Transportation, Federal Highway Administration

in accordance with the Transportation Equity Act for the 21st Century


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Table of Contents

Chapter 10109Bicycle Networks

Chapter 11 161State Laws

Chapter 12 179Law Enforcement Practices

Chapter 13 189Education and Training

Chapter 14 201Safe Routes to School

Chapter 15 209Seting Priorities

Chapter 16 229Benchmarking

Chapter 17 237Public and Private Sector Roles

Chapter 1 5Preface and Acknowledgements

Chapter 2 13Introduction

Chapter 3 19Existing Studies

Chapter 4 29Best Practices in Bicycle and PedestrianPlanning

Chapter 5 47Rider Classification

Chapter 6 53

Overview of Existing Conditions

Chapter 7 71Identifying Statistical Hot Spots

Chapter 8 93Transit Stop Pedestrian Survey

Chapter 9 99Bicycle Parking and Bike on Bus

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Figure 1 14Gulf South Comparison: Percentage ofMSA Households without Vehicles (2000)

Figure 2 26Alignment for the Bikeways in St. BernardParish

Figure 3 31

TRBs Guide for Reducing PedestrianCollisions

Figure 4 54Percentage of Pedestrian Crashes byParish

Figure 5 54Percentage of Bicycle Crashes by Parish

Figure 6 56Jefferson Parish High Poverty BlockGroups

Figure 7 56Orleans Parish High Poverty BlockGroups

Figure 8 58Bicycle Crashes per Year

Figure 9 59Percentage of Bicycle Crashes by Severity

Figure 10 59Percent of Severity of Bicycle Crashes by Year

Figure 11 59Percentage of Bicycle Crashes by Month

List of Figures

Figure 12 60Percentage of Bicycle Crashes Per Day ofthe Week

Figure 13 60Number of Bicycle Crashes by Hour

Figure 14 60Age of Cyclists by Crash Frequency

Figure 15 61Cyclists Crashes: Juvenile vs Adult

Figure 16 61Percentage of Bicycle Crashes by Life-Stage

Figure 17 61Percentage of Bicycle Crashes by LightingCondition

Figure 18 62Number of Pedestrian Crashes Per Year

Figure 19 62Percentage of Pedestrian Crashes bySeverity

Figure 20 62Percent of Severity of Pedestrian Crashes

Figure 21 63Percentage of Pedestrian Crashes byMonth

Figure 22 63Pedestrian Crashes by Day of the Week

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Figure 23 63Number of Pedestrian Crashes by Hour

Figure 24 64Age of Pedestrian by Crash Frequency

Figure 25 64Percentage of Pedestrian Crashes by Age

Figure 26 64Percentage of Pedestrian Crashes by LifeStage

Figure 27 65Gender and Pedestrian Crashes

Figure 28 65Percentage of Pedestrian Crashes by Lighting

Conditions

Figure 29 66French Quarter Street Patern

Figure 30 67Wagon-Wheel Street Profile

Figure 31 67Eastbank Jefferson Major ConnectivityBarriers

Figure 32 76Pedestrian Crashes 1999-2002 East BankCore

Figure 33 79

Pedestrian Fuzzy Mode Tolerance QuarterMile

Figure 34 79Kmeans Pedestrian Cluster 5 Separation 3

Figure 35 80STAC Quarter Mile Cluster 5 Triangular

Figure 36 82Multiple Pedestrian Crash Locations1999-2000 (East Bank Core)

Figure 37 84Spatial and Temporal Analysis of Crime

Figure 38 85Statistically Significant Pedestrian Clusters,Orleans Parish

Figure 39 86Statistically Significant Bicycle Crash Clusters,Orleans and Jefferson Parishes

Figure 40 87Spatial and Temporal Analysis of Crime

Figure 41 89Multiple Bicycle Crash Locations 1999-2002(East Bank Core)

Figure 42 93Metro Area Bus Routes

Figure 43 94Transit Operator Identified Problem Stops:Orleans Parish

Figure 44 94Transit Operator Identified Problem Stops:Jefferson Parish

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Figure 45 103Downtown Bike Rack Plan, Phase 1

Figure 46 104Downtown Bike Rack Plan, Phase 2

Figure 47 105Jefferson Transit Bike-on-Bus Users 2000-2004

Figure 48 110Central New Orleans Routes

Figure 49 111Jefferson/St. Charles Corridor North

Figure 50 112Jefferson/St. Charles Corridor Airport Area

Figure 51 113Jefferson/St. Charles Corridor South

Figure 52 115Central Avenue Corridor North

Figure 53 117Central Avenue Corridor South

Figure 54 125Jefferson/Orleans Corridor North

Figure 55 125Jefferson/Orleans Corridor South

Figure 56 126

Wisner Corridor North

Figure 57 129Wisner Corridor Mid-City

Figure 58 131Wisner Corridor South (Nashville Area)

Figure 59 133Esplanade Corridor

Figure 60 135St. Bernard Corridor North

Figure 61 137St. Bernard Corridor South

Figure 62 138Lakefront Corridor West

Figure 63 139Lakefront Corridor East

Figure 64 203Statistically Significant Children 6 andUnder

Figure 65 204High Poverty Block Groups and StatisticallySignificant Child Pedestrian Crash Clusters

Figure 66 205Statistically Significant Youth PedestrianClusters, Orleans and Jefferson Parishes

Figure 67 205Statistically Significant Pedestrian CrashClusters and Crashes within 1 Mile ofProgram Schools

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Table 1 53Louisiana Pedestrian Fatalities

Table 2 53Louisiana Bicycle Fatalities

Table 3 57Orleans Parish Pedestrian Crashes andPoverty

Table 4 57Jefferson Parish Pedestrian Crashes andPoverty

Table 5 57Orleans Parish Bicycle Crashes and Poverty

Table 6 58Jefferson Parish Bicycle Crashes and Poverty

Table 7 72Pedestrian Crashes Involving Youth under18, Orleans Parish

Table 8 73Proximity of Transit Routes to PedestrianCrashes, Orleans Parish

Table 9 74Proximity of Pedestrian Crashes to HousingDevelopments, Orleans Parish

Table 10 74Percentage of Pedestrian Crashes in theCBD and French Quarter

Table 11 81Top 15 Pedestrian Crash Locations

List of Tables

Table 12 85Statistically Significant Pedestrian CrashClusters, Orleans Parish

Table 13 86Statistically Significant Bicycle CrashClusters, Orleans and Jefferson Parishes

Table 14 88

Top 15 Bicycle Crash Locations

Table 15 95Orleans Parish Transit Survey Responses

Table 16 95Jefferson Parish Transit Survey Responses

Table 17 155Minimum Street Width Needed forRetrofiting with Bicycle Lane

Table 18 155Speed Limits

Table 19 157New Orleans Street Classifications

Table 20 167Multi-Jurisdictional Comparison of Bicycleand Pedestrian Laws

Table 21 167Required Bicycle Equipment

Table 22 180

2001 Bike Injuries by Race, Age and Gender

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Table 23 184Information Requests on Bicycle Enforcementto Local Police, Spring 2002

Table 24 214Programmed Transportation ImprovementProjects (1994-2004)

Table 25 225

Bike / Pedestrian Policies

Table 26 231Safety, 2002

Table 27 231Safe Routes to School Programs, 2005

Table 28 232Modal Share, 2000

Table 29 232Miles of Existing On-Street Bicycle Lanes,2005

Table 30 232Miles of Existing Off-Street Shared-Use Paths,2005

Table 31 233Facilities, 2003

Table 32 233Facilities, 2005

Table 33 233

Funding, 1994-2003

Table 34 233Funding thru 2004

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Table 35 234Organizational Adopted Bike/PedestrianPlan

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Preface and Acknowledgements


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Special thanks go to Brian Bowman, New Orleans CityPlanning Commission, for his work standardizing thewrite-ups done by advocates on the routes of regional

significance when working for the Regional PlanningCommission. Brian subsequently used his knowledgeand experience to accomplish a phased bicycle routemap for the city of New Orleans Transportation Elementof the Master Plan. For that, we are especially apprecia-tive. Billy Fields, PhD also contributed by finalizing andmapping this chapter.

Many thanks to Audrey Warren for her work to estab-

lish and pilot the first Safe Routes to School program inthe city of New Orleans and the state of Louisiana. Au-drey contributed to the section reporting on Safe Routesto School programmatic advancements.

Finally, the staffof the Regional Planning Commissionwould like to thank the elected and citizen members ofthe Commission for allowing this study to proceed un-hindered. Only fearless and resolute leadership looksdeeply at their regional shortcomings so appropriateand equitable steps can be taken to improve the condi-tions for its citizens.

Karen Parsons, AICPRegional Bicycle and Pedestrian Coordinator

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Introduction


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5

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work for addressing how policy efforts are working toimprove bicycling and walking.

This Master Plan provides a clear overall direction forpolicy decisions affecting bicycling and walking. It doesnot, however, lay out a fully formulated set of specificpolicies for achieving these goals. This Master Plan has

been thefirst full-fledged effort to address bicycling andwalking in the New Orleans region. As such, the firsttask in the process has been to build awareness and con-sensus about the importance of bicycling and walkingto the region. Translating this awareness into a system-atic set of policy actions is the next important step inthe transformation process. While the region has seen anumber of good ad-hoc projects, these efforts have tra-ditionally not been tied to an overarching policy docu-ment seting out specific goals, policies, objectives, andaction items. This should be the next step in working toimprove bicycling and walking conditions in our region.This important step will require a concerted effort to co-ordinate regional policies for bicycling and walking.

The Regional Planning Commission is commited toexpanding the constructive framework set out in thisMaster Plan to help improve bicycling and walking con-ditions in the New Orleans region. This Master Plan has

begun to build a strong base of commited local officialswho are working to improve conditions in our area. TheRPC will work to keep this strong momentum going tohelp improve bicycling and walking conditions in theregion.


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Existing Studies


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Figure2

Segment Alignment

1Orleans/St. Bernard Parish line to Center StreetCenter Street to LA 47 (Paris Road)

2 LA 47 to Lake Borgne Levee Administration Building

3Lake Borgne Levee District Administration building

to Montenlongo LaneMontelongo Lane to St. Bernard Parish/Plaquemines

Parish line

2 Main north-south route from Oak Harbor tothe Interstate (6.4 miles)

Interim links between Pontchartrain Trace

and Tammany Trace (about 4 miles inlength)

Neighborhood routes (5 routes about 25miles in length).

Other general topics covered included types of bike-ways and bike path ratings based on safety and driverskill. (Major bicycle routes are classified as A whileneighborhood routes are designated C. When C

routes are linked with A they are considered upgrad-ed to B).

Proposed Bicycle Plan forSt. Bernard(2001)

The study focused on St. Bernard Parish and proposedthat a 10-mile stretch of river levee in St. Bernard Parish

be used for a bike path that would join the levees in Or-leans and Jefferson parishes thus connecting the parishwith other parts of the New Orleans metro area. Thisstudy proposed the following alignment for the bike-ways in St. Bernard Parish:

Other issues discussed in the study included:

(a) Entities that can play a role in the St. Bernard

Parishbike path development: American Heritage Rivers Initiative (AHRI)

Mississippi River Trail (MRT)

(b) Legal issues related to use of levees and re-strictions imposed by private landowners

(c) Operation and maintenance costs & responsi-bilities

(d) Funding Options TEA-21, reserve funds, revenue bonds,

lease purchase, special assessments, stateand ederal grants

(e) Phasing

Proposed phasing priority was segment 2, 3and finally 1.


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Best Practices in Bicycle and Pedestrial Planning


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Rider Classification


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Overview of Existing Conditions


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A closer look at the patern of crashes in the New Or-leans metropolitan region shows more clearly how the

5 Figure 6Jefferson Parish High Poverty Block Groups


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p g ynegative connection between poverty and pedestrianand cyclist safety functions. Tables 3 and 4 present the

percentage of pedestrian crashes within and adjacentto high poverty block groups in Orleans and Jeffersonparishes.

These data show that within high poverty block groupsthere is an over representation of pedestrian crashescompared to the population of these areas. For exam-ple, in 2002, 42% of pedestrian crashes occurred in highpoverty block groups in Orleans and 10% of these same

type of crashes occurred in Jefferson high poverty ar-eas. (Remember that Orleans high poverty block groupscontained 28% of the population and Jeffersons highpoverty block groups contained 3% of the population).

When walking trips adjacent to the high poverty blockgroups are taken into account, the extent of the problemis further accentuated. It is important to include tripsnear or adjacent to high poverty areas because manystores and transit stops lie just beyond the edges of these

areas. When mile and mile delineations are used toanalyze these data, the percentage of pedestrian crashesclimbs dramatically. While it is difficult to untangle allof the demographic and spatial interactions that arehelping to produce these results, the high percentage ofpedestrian incidents occurring in and adjacent to highpoverty areas should be seriously examined by thoseinvolved with safety and transportation policy.

The analysis of bicycle data in relation to poverty pro-duced similar results to the pedestrian analysis. Thedisparity between Orleans and Jefferson, however, waseven more pronounced. Within a mile of high pov-erty block groups in Orleans, up to 91% of all bicyclecrashes were recorded. In Jefferson, however, the per-centage only ranged as high as 28% for recorded bicyclecrashes within a mile of high poverty block groups.Tables 5 and 6 show these results.

When walking trips adjacent to the high poverty blockgroups are taken into account, the extent of the problem

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Orleans Parish High Poverty Block Groups

Jefferson Parish High Poverty Block Groups


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SummaryStatisticsofRegionalBicycle and Pedestrian Crashes

9Figure 9Percentage of Bicycle Crashes by Severity


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BicycleandPedestrianCrashes

Regional data for the New Orleans metropolitan areahave been examined for both bicycle and pedestriancrashes. The data have been examined to determinehow many people are involved in crashes, the severityof injuries sustained in those crashes, when these inci-dents are occurring, and who is involved in the colli-sions. The analysis in this chapter is descriptive, but ithelps to shed light on some interesting paterns. The

bicycle data is examined first.

The number of bicycle crashes in the New Orleans met-ropolitan area was examined for the 4 years of data from1999 to 2002 (Figure 8). The highest number of crasheswas recorded in 1999 (over 500). Afer a sharp drop tothe mid-300s in 2001, the number shot up again to over400 in 2002. The direction of the trend in these numbersis difficult to determine with the up and down yearlytotals.

In order to make these data more meaningful, it wouldbe useful to atach a rate of crashes per number of bi-cyclists in order to determine relative risk. This tech-nique helps to show whether yearly crash total declinesor increases are due to increases or decreases in rider-ship numbers. Future data collection efforts should begeared towards creating a baseline exposure estimate(City of Toronto 2003) of current riders to establish thismeaningful rate. In addition, the analysis of these datashould be undertaken yearly in order to determine both

the direction of the trend in crashes as well as the extentof success in safety programs.

The severity of injuries sustained by cyclists is anotherimportant component of the dataset. Figure 9 shows thepercentage of crashes for the different severity typeslisted in the crash reports. Figure 10 shows the percent-ages for each of these crash types by year. While the ma-

jority of cyclists sustained either minimal or no injury,

the moderate, severe, and fatal categories still accountfor 30 to 40% of all crashes. The trend in these crashesappears to be fairly consistent from year to year.

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Figure 10Percent of Severity of Bicycle Crashes By Year

Figure 11

Percentage of Bicycle Crashes by Month

Another way to look at these data is to compare month-to-month crash data. Figure 11 shows that the number ofbicycle crashes peaks in July with over 10% and drops to

6Figure 12

Percentage of Bicycle Crashes


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Figure 13Number of Bicycle Crashes by Hour

bicycle crashes peaks in July with over 10% and drops tounder 6% in November. This patern of a high number of

summer crashes probably has to do with increased ridernumbers during this period.

Figure 12 shows the distribution of crashes by day of theweek. Aside from a small spike on Fridays, the data arefairly evenly distributed.

The crashes per hour of the day represented in Figure 13show a spike in the afernoon hours between 4 and 7 PM.Again, this is probably due to the increased numbersof riders and increased congestion during this period.Detailed data on ridership paterns and volume would

be extremely useful here to help create a more focusedanalysis of these data.

The age of cyclists involved in crashes (Figure 14) showstwo peaks. The first and largest peak is for 13 year olds.The second peak is for 41 year olds. According to officialsat Charity Hospital, the average age of emergency room

admissions for bicycling crashes is 43. This second peakcould relate to the higher number of older residents thatdo not own a car and rely on the bicycle to move aroundthe community.

The age distribution of the New Orleans crashes is verydifferent from the patern seen in some other areas. Ina comprehensive study of Toronto cyclists, the peak inincidents occurred for mid- to late-twenty year olds.

Because of the higher levels of bicycle commuting andridership in this age group, they were more likely to beinvolved in crashes. The relatively low number of mid-twenty year olds seen the New Orleans metropolitan da-taset could be seen as an indication of a relatively lownumber of commuting and recreational cyclists in thisage group. Again, a detailed analysis of the rate of in-

jury would help to beter understand the implicationsof these data.

Another way to slice these data is to look at the per-centage of adults versus juveniles involved in bicycle

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Percentage of Bicycle CrashesPer Day of the Week

Figure 14Age of Cyclists by Crash Frequency

Figure 15Cyclist Crashes: Juvenile vs Adult

crashes. Figure 15 shows that despite the large peak ofyoung cyclists involved in crashes seen in Figure 11, theoverwhelming majority of crashes actually occur with

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y i a e Ju e i e A uoverwhelming majority of crashes actually occur withadults.

Another technique for analyzing the age of cyclists in-volved in crashes is by looking at life stages for those in-volved in crashes (Figure 16). This technique was used

by Tan (1996) for use in the FHWAs crash type manual.This technique splits age data into groups accordingto established life stages. This approach can be usedto help target safety messages to particular age groupswithin the population.

The data examined here, once again, show that the adultpopulation is involved in the highest number of crashes,followed by youth and mature adults. It is interesting tonote that this life stage histogram fails to pick up thespike of early-forty year olds and the relatively smallernumber of mid-twenty year olds involved in bike crash-es. Because of its large grouping of adults 25 to 44 in onegroup, the life stages histogram probably understatesthe significance of crashes to the older segment of the

adult life stage and overstates the significance to theyounger component of the adult category.

Finally, lighting conditions are another way to examinethe temporal aspect of crashes (Figure 17). The over-whelming majority of crashes occurred during daylighthours. Again, the rate of crashes would be useful to ex-amine here. The large number of crashes during day-light hours probably emphasizes the greater number of

cyclists active during this period.

PedestrianRegionalData

While there are several significant differences betweenthe bicycling and pedestrian data, the basic trends ofthe two are remarkably similar. These similarities anddifferences are highlighted in this section.

A A fairly stable trend in pedestrian crashes was ob-served from 1999 to 2002 (Figure 18). Despite a dip in

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Figure 16Percentage of Bicycle Crashes by Life Stage

Figure 17Percentage of Bicycle Crashes

by Lighting Condition

2000, pedestrian crashes have averaged around 650 to750 crashes per year.

6Figure 18

Number of Pedestrian Crashes Per Year


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An examination of the severity in pedestrian crashes

(Figure 19) shows a slightly lower percentage of crash-es reported as no injury and a higher percentage ofmoderate and severe injuries compared to the bicyclingdata. The difference in the basic dynamics of the twotypes of crashes could result in these differences withpedestrians taking a much more direct impact from thecollisions. Figure 20 shows the fairly stable patern ofthe severity of crashes over the study period.

The percentage of pedestrian crashes by month (Figure21) shows an interesting peak of crashes in March andApril. The good weather of these months may result inhigher pedestrian numbers. Because the rate of pedes-trian crashes is unavailable, it is difficult to determineexactly what to make of these differences. Just as in the

bicycling analysis, a study to determine the rate of pe-destrian crashes by population would provide muchneeded insight into the dynamics of pedestrian crashes.

Figure 22 shows the percentage of pedestrian crashes byday of the week. Just as in the bicycling data, there is asmall increase in crashes on Friday.

Figure 23 shows the number of pedestrian crashes byhour. Again, just as in the bicycling data, there is an af-ternoon peak between 3 and 7 P.M. with a small morn-ing peak.

While much of the pedestrian and bicycling crash dataappears to be a mirror image of one another, the age datashows some significant differences. The age of pedes-trian crashes shows two juvenile peaks at around ages 6and 13 (Figure 24). The highest peak is for the youngerset of children. This large peak in the pedestrian data ismuch more pronounced than in the bicycling data.

Because younger children are still developing the cogni-tive skills necessary to safely move about their neigh-

borhoods, this younger age group is more likely to beinvolved in crashes. Rivara (1990) in his study of child

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Number of Pedestrian Crashes Per Year

Figure 19Percentage of Pedestrian Crashes by Severity

Figure 20

Percent of Sev

erity of Pedestrian Crashes

pedestrian injuries in the United States found that thisage group was particularly vulnerable. He says that,The early school-age child appears to represent a win-

3Figure 21

Percentage of Pedestrian Crashes by Month


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dow of vulnerability in which expectations and de-

mands of the child as a pedestrian exceed the skills heor she can bring to bear on the crossing task (p. 693).This tendency of adults to overestimate the actual cog-nitive development of their children might be addressedthrough a focused safety education program aimed ateducating adults.

While the largest spikes in pedestrian crashes appear inthe juvenile age category, the largest percentage of pe-destrian crashes occur with adults (Figure 25). This pat-

tern again matches the one established in the bicyclingcrash analysis.

Figure 26 shows the life stages for pedestrians involvedin crashes. The patern is nearly identical to the bicyclingdata except for a reversal in the incidence of crashes be-tween the child and youth categories. Rivaras analysis(1990) examined earlier helps to explain this difference.

One field of data that was available in the pedestriandata that was not available in the bicycling data is thegender of the pedestrian involved in the crash (Figure27). Males accounted for about 60% of all those involvedin crashes while females accounted for approximately40%.

The final histogram displays the percentage of pedes-trian crashes by lighting condition (Figure 28). Just as inthe bicycling analysis, the majority of crashes occurredin daylight hours. Again, this could be caused by thehigher number of pedestrians active during this period.

ImplicationsofSummaryStatistics

The analysis of pedestrian and bicycling crashes pre-sented thus far is intended to provide a descriptive por-

trait of how many people are involved in crashes, the se-verity of injuries sustained in those crashes, when theseincidents are occurring, and who is involved in the colli-


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Figure 22Pedestrian Crashes by Day of the Week

Figure 23Number of Pedestrian Crashes by Hour

sions. This descriptive analysis provides simple base-line data on these important characteristics. The analy-sis to this point has only cursorily examined how and

Figure 24Age of Pedestrian By Crash Frequency


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why these crash incidents have been occurring. While

a full-blown crash frequency analysis of collision typesis beyond the scope of this Master Plan, a more detailedgeographic analysis of where collisions occur has beenundertaken to help provide policy makers and the publicwith a more focused description of crash events. Chapter6 presents this detailed geographic analysis. Before delv-ing into this detailed geographic analysis, the importantelements of the urban landscape must be examined. Thisanalysis focuses on both the importance of climate onnon-motorized transportation as well as the underlying

patern of the urban transportation system.

DescriptionoftheAdvantagesandConstraintsoftheLandscapeofSoutheastLouisiana

The New Orleans metropolitan region is made up ofseven parishes around southeast Louisiana that stretch

from the marshland of the Gulf of Mexico to the roll-ing pine forests of the northshore of Lake Pontchartrain.The diversity of landscapes is matched by a wide vari-ety of townscape profiles that ranges from the dense,nineteenth century street networks of New Orleans totwentieth century suburban forms of many of the sur-rounding parishes to rural hamlets that dot the outskirtsof the region. In order to effectively plan for pedestrianand bicycling in this region, the unique characteristics of

these diverse landscapes must be addressed. This sec-tion provides an overview of some of the pertinent ele-ments that help to create the planning environment ofsoutheast Louisiana.

Climate

Walking and bicycle riding are activities that are highlydependent on the climate of a region. The New Orleansmetropolitan area lies in a semi-tropical belt character-ized by short, mild winters and steamy, long summers.While the tropical rains and heat of the summer have be-

Figure 25Percentage of Pedestrian Crashes by Age

Figure 26Percentage of Pedestrian Crashes by Life Stage


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7Figure 30

Wagon-Wheel Street Profile

large-scale movement of the automobile. This suburbanpatern helps to create enclaves of low-intensity traf-fic linked to high-intensity commercial areas via large,single purpose automotive traffic arteries This system


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single purpose automotive traffi c arteries. This system

creates signifi

cant connectivity problems for pedestriansand bicyclists that are characteristic of other suburbanareas around the country.

While this basic patern has been repeated in countlesscommunities around the country, Jefferson Parishs land-scape constraints have helped to create several uniquechallenges. The East Bank of Jefferson is divided by a se-ries of large-scale transportation corridors. The east-westdividers include Jefferson Highway, Earhart Express-

way, Airline Drive, West Metairie, West Napoleon, Inter-state-10, Veterans Boulevard, and West Esplanade. Thesemajor, multi-lane arteries create significant impedimentsto movement of bicycles and pedestrians in the parish.The situation is compounded by the relative scarcity ofat-grade, north-south routes that breach the Interstate.The older urbanized portion of the parish from Bon-nabel Boulevard to the parish line has several at-graderoads that create decent pedestrian and bicycling access

to the lake side of the parish. The newer suburbanizedportion of the parish moving towards Kenner, howev-er, is connected to the lake side by elevated roadwaysat Causeway, Cleary, Clearview, and David Drive, withonly the heavily traffi cked Williams and Loyola cross-ings at grade. Only Transcontinental provides a decentconnection for pedestrian and cyclists on this side of theparish. The numerous drainage canals and railroads thatcross the area further accentuate the connectivity prob-lems of the parish (Figure 31). Jefferson Parishs paternof pedestrian and bicyclist crashes shows the impact ofthese connectivity barriers. Understanding the specificimplications of these connectivity problems is the taskof Chapter 7.


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Figure 31Eastbank Jefferson Major Connectivity Barriers

6 WorksCitedCity of Toronto. 2003. City of Toronto Bicycle/Motor-Vehicle Collision Study. Works and Emergency Service


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Vehicle Collision Study. Works and Emergency Service

Department.

Fields, Willard. 2004. Cite Dissertation

Jargowsky, Paul. 1997. Poverty and Place: Ghetos, Bar-rios, and the American City. New York: Russell SageFoundation.

Lewis, Peirce. 2003. The Making of an Urban Land-scape

National Safe Kids Campaign. 2004. Injury Facts: Chil-dren at Risk. Website. www.saids.org.

Pless, I. Bary and Rennee Verreault, Louise Arsenault,Jean-Yves Frappier, Joan Stulginskas. 1987. The Epide-miology of Road Accidents in Childhood. American

Journal of Public Health. 77: 358-360.

Pucher, John and John Renee. 2003. Socioeconomics ofUrban Travel: Evidence from the 2001 NHTS. Transpor-tation Quarterly 57 (3): 49-77.

Rivara, Frederick. 1990. Child Pedestrian Injuries in theUnited States: Current Status of the Problem, PotentialIntervent0ions, and Future Research Needs. AJDC. 144:692-752.

Tan, Carol. 1996. Crash-Type Manual for Bicyclists. U.S.

Department of Transportation, Pub. No. FHWA-RD-96-104 (available at htp://www.trc.gov/safety/pedbike/ctanbike/ctanbike.htm).


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While this can be a serious problem for anyone atempt-ing to cross the street, it is particularly dangerous fortourists or children who expect that cars will yield. Thepicture at the right was taken the day afer JazzFest onSouth Peters Street near the Tower Records store During

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South Peters Street near the Tower Records store. Duringthis time, many out-of-town tourists (and locals alike)walk back and forth between the live music events atTower Records and the near-by Louisiana Music Factoryin the French Quarter. Many of these tourists expect thatthe painted crosswalks will offer them some protectionas they atempt to cross the street. Unfortunately, manyNew Orleans drivers are not accustomed to yielding topedestrians in crosswalks. The gentleman in the pictureentered the crosswalk when traffi c was about a block

away expecting that traffi c would slow to allow himto cross. As the picture shows, this was a mistaken as-sumption. The car on the right is entering the crosswalkwhile a bus is bearing down on the man from the otherlane. Just afer this picture was taken, the man beganrunning across the crosswalk as the bus continued onits path toward him. Luckily, he was not struck on his

journey across the street in the crosswalk.

In the next picture, a couple is atempting to cross thesame intersection a minute or two later. A car (shown inthe botom lefof the frame) actually continues towardthem while they are in the crosswalk. Again, the couplescurried away across the intersection.

In less than five minutes these and several other nearmisses were observed at this intersection (South Petersand Conti streets). This intersection is ranked number7 in the region for pedestrian crashes with 7-recorded

crashes from 1999 to 2002.

Overall, twelve of the top fifeen pedestrian crash loca-tions are in the French Quarter and surrounding CBDarea (See Table 11 later in this chapter). Because of thecombination of a large amount of foot traffic in the Quar-ter, the large portion of tourists with different expecta-tions about crosswalk protection, and a local populationthat ignores pedestrians rights to crosswalks, the French

Quarter and the surrounding CBD were the location of21% of pedestrian crashes in the region in 2002. A more

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detailed study of this area should be considered to helpunravel the combination of issues that is driving the pe-destrian crash problem in this, the traditional heart, ofthe New Orleans area.

is to determine exact paterns from a simple visual in-spection of the data. While some apparent paterns can

be seen, a distinct, specific set of hot spots is impossibleto define from this visual inspection.

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HotSpotAnalysis

The above geographic analysis helps to single out someof the general areas of the city in need of special aten-tion. It provides important data on where crashes areoccurring generally and on some of the likely causesof those crashes. While the analysis creates this gener-alized description of where crashes are occurring, thisform of analysis is limited in its ability to pinpoint more

specific areas in need of atention. For example, Figure32 shows the base pedestrian data unfiltered by spatialstatistics. This unfiltered graphic shows how difficult it

While the visual analysis to extract information frompoint data utilized in the above section is a crucial firststep in analyzing data, it can be augmented by computer-ized hot spot analysis that can help to sort through thesedata much more systematically. This section provides adetailed examination of the specific mechanisms of hotspot analysis and applies this important technologicaltool to crash data in Orleans and Jefferson parishes. Suf-ficient data points were not available for Plaquemines,

St. Bernard, St. Charles and St. Tammany parishes in or-der to conduct a statistical analysis of hot spots in thoseparishes.

Figure 32Pedestrian Crashes 1999-2002 East Bank Core

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9Figure 33

Pedestrian Fuzzy Mode Tolerance Quarter Mile


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Parish. The kmeans routine is less useful for comparingthe significance of these multurisdictional groupingshowever. Levine (2002) points to this weakness when heargues By definition, the technique is somewhat arbi-trary since the user defines how many clusters are to beexpected. Whether a cluster could be a hot spot or notwould depend on the extent to which a user wanted toreplicate hot spots or not (p. 275).

Figure 34 shows the results of one of the most focusedruns of the kmeans routine for the same pedestrian dataset. The tolerances are set with 5 hot spot clusters and aseparation value of 3.

The resulting five clusters shown in brown in the graph-ic are probably too broadly defined to be useful in iden-tifying specific intersections or even neighborhoods inneed of crash intervention. The kmeans routine, how-ever, could be used as a first step in broadly definingareas in need of intervention.

Figure 34Kmeans Pedestrian Cluster 5 Separation 3

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8Figure 35

STAC Quarter Mile Cluster 5 Triangular


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The Spatial and Temporal Analysis of Crime (STAC)routine is another technique for identifying hot spots.STACdefines the density of clusters of any point data fora specified area by defining the best fiting standard de-viational ellipse or circle for the point data. STACcom-

bines this circle clustering technique with hierarchicalclustering techniques that aggregate small clusters intolarger clusters (Block and Block 2002, p. 257). It func-tions best when there is a large data set from which toidentify clusters.

The result is a technique that allows the user to atain theadvantages of the fuzzy mode technique of scanning forsmall cluster areas, but avoids the disadvantage of thefuzzy mode by not double counting the point data. Fig-ure 35 shows the STACrun for the same pedestrian dataset. The tolerances are set at a quarter mile, minimum of5 clusters and triangular orientation.

Unlike the kmeans technique, the number of clusters isnot entirely predefined. While a minimum number of

clusters initiate the search (in this case five), more clus-ters can in fact be identified by the routine. In the ex-ample, 20 clusters (shown in light blue) were eventuallyidentified. Another advantage of the STACtechnique isthat it allows the analyst to perform a Monte Carlo testto help determine the statistical validity of the clustersthemselves. The numerical results of this test help to de-termine the degree to which the clusters that are returned

by the technique are statistically significant. Overall, theSTACtechnique offers probably the most accessible andaccurate statistical routine currently available for identi-fication of small, focused hot spot areas.

PedestrianCrashHotSpots1999 to 2002

With this basic overview of spatial statistical techniquesin mind, pedestrian data can now be examined in great-er depth. Multiple runs of the four different statisticalroutines (mode, fuzzy mode, kmeans, and STAC) were

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8Figure 36

Multiple Pedestrian Crash Locations1999-2002 (East Bank Core)


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tailed analyses of the locations with the highest numberof crash events. This is particularly true for the FrenchQuarter/Central Business District area where 83 loca-tions recorded multiple crash events.

Fuzzy Mode

The fuzzy mode routine was run with quarter-mile,half-mile, and one-mile tolerances set for the Jefferson/Orleans core area. The three runs produced very simi-lar results with the identified clusters of highest inten-sity focused on the French Quarter/CBD area. Figure 33(shown previously) shows the most focused quarter-mile run. Increasing the tolerances merely widened thezone of highest intensity; the zones remained centeredaround the French Quarter/CBD area.

The highly clustered zone in the French Quarter/CBDarea identified by the fuzzy mode analysis matches the

zone identified previously by the mode analysis. Themode analysis further strengthens the need for counter-measures in this area.

Kmeans

The next test performed was the kmeans test. Two toler-

ances enable the user to alter the run of this test: clustertolerance and separation tolerance. The Jefferson/Or-leans core area pedestrian data were run with tolerancesset at cluster 5 separation 4, cluster 5 separation 3, clus-ter 6 separation 3, and cluster 5 separation 8. The runsproduced a series of geographic ellipses that identifiedclusters of high crash areas. Figure 34 (shown previous-ly) shows the results of the cluster 5 separation 3 run.

While this run produced the most focused results, the

ellipses are probably too broad to be utilized to produce

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5While individual countermeasure treatments should beconsidered for the highest incident locations, the statis-tically significant hot spot zones identified through theuse of the STAC routine should be considered for areawide treatment. These special areas have particularly

high incident counts and creating an effective counter-

While the 1,042 crash events testify to the significanceof the bicycle crash problem in the core area of Jeffersonand Orleans parishes, the geographic patern of bicyclecrashes presents a more complex problem for counter-measure implementation than that suggested for pedes-

trian crashes. In general, cyclists travel longer distances


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Figure 38Statistically Significant Pedestrian Clusters, Orleans Parish

Table 12

Statistically Significant (95%) Pedes-trian Crash Clusters, Orleans Parish

1 Broad and Banks

2 Broad and Orleans

3 Canal and Bourbon

4 Claiborne and Elysian Fields

5 Claiborne and Martin LutherKing

6 Esplanade and Chartres

7 Franklin and Villere

8 Nashville and Freret

9 St. Charles and Jackson

10 Rampart and St. Peter

g gmeasure program could help to create a significant im-provement in pedestrian safety.

BicyclingCrashAnalysis

Compared to pedestrian crashes, bicycle crashes wereless frequent and more dispersed. The number of bi-cycle crashes identified in the core east bank of Orleans

and Jefferson parishes was 1,042 compared to 1,854 forthe pedestrian crashes in the same area. The patern of

bicycle crashes was more dispersed than the pedestriancrashes with 135 multiple crash locations identified com-pared to 314 multiple crash locations for the pedestriancrash dataset.

g , y gthrough corridors. They, thus, travel through many moreintersections on their journeys than would a pedestrianon a similar trip. This may explain the more dispersednature of bicycling crashes. This suggests that corridor-wide improvements may be an important element in a

bicycling safety improvement campaign.

Despite this difference in the distribution of bicycling

crashes, significant geographic paterns could still beidentified. The STAC analysis results are presented first.This is followed by the results of Kmeans, mode, andfuzzy mode routines.


8 STACThe STAC routine was run with a quarter mile tolerancefor the bicycle crash data for the Eastbank core of the

Jefferson/Orleans area. The routine was able to identify

with 95% confidence 9 statistically significant clustersb d d i J i h h d i d d

KmeansandSTAC

While the kmeans routine was used to analyze the data,it did not prove nearly as effective with the smaller, moredispersed dataset. The kmeans routine returned results

that were not particularly useful for developing effectiveh k


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y gbased on density. Just as with the pedestrian data, den-sity and not area was found to be significant. Becausethe density of points is the most important characteris-tic of a hot spot, finding statistically significant densityspots is very valuable. Figure 39 and Table 13 show thestatistically significant bicycle clusters. Figure 40 showsthe results of the Monte Carlo test to determine statisticalsignificance.

Figure 39Statistically Significant Bicycle Crash Clusters

Orleans and Jefferson Parishes

p y p gcountermeasure programs. The kmeans routine was runmultiple times at different tolerance scales, but the rou-tine consistently could only produce one very large iden-tified cluster. The cluster covered nearly the entire Met-ropolitan area and was, therefore, not usable as a toolto identify particular locations ideal for countermeasureimplementation.

Mode

The mode routine, once again, provides a simple,straightforward technique for determining the locationswith largest number of crashes. Table 14 shows the top15 bicycle crash locations in the Jefferson/Orleans east

bank core area.

Unlike the pedestrian data, the bicycling crash datashow that the two highest concentrations of crashes oc-

curred in Jefferson Parish. With 22 crashes being loggedcumulatively, the corners of Loyola and Veterans and

Table 13

Statistically Significant (95%)Bicycle Crash Clusters, Orleans and

Jefferson Parishes

1 Broad and Tulane

2 Esplanade and Charters

3 Esplanade and Claiborne

4 St. Charles and Canal

5 St. Charles and Jackson

6 St. Charles and Louisiana

7 St. Clauce and Lizardi

8 St. Claude and Tupelo

9 Williams and Veterans

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9treatments should be considered especially for the loca-tions with the highest number of multiple crashes.

BicycleCrashDataSummary

While bicycle crashes are spread more broadly than pe-d i h d fi i i hi ill

locations are concentrated primarily in the two identi-fied broad zones of crashes. Planners should consult themultiple crash list when planning bicycle corridors tohelp either route around these locations or to help im-prove safety conditions in these places.

Planning for bicycling safety involves a broader agenda


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destrian crashes, definitive geographic paterns are stillevident from the analysis. The STAC analysis identified9 statistically significant hot spot clusters. The local char-acteristics of these zones should be studied in greaterdepth to help determine the specific safety problems inthese areas. The mode and fuzzy mode helped identifytwo, broader zones of high concentration of crashes.These areas are: the Loyola/Williams area in Jefferson

Parish and the zone in and around the CBD/FrenchQuarter area in Orleans Parish. Routes to help bicycliststo traverse these zones should be a priority in planningto improve bicycling safety.

Individual locations that recorded multiple crashes havealso been examined. Not surprisingly, these individual

Figure 41Multiple Bicycle Crash Locations 1999-2002 (East Bank Core)

Planning for bicycling safety involves a broader agendathan simply implementing engineering countermeasureprograms at individual locations, however. While it isimportant to improve high incident locations, it is alsocrucial to implement system wide changes that help tomake the broader transportation system more accessibleto bicyclists. Bicyclists are legal vehicles on city streetsand should be accommodated with streets that allow for

full multi-modal participation.



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Transit Stop Pedestrian Survey


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9Figure 43

Transit Operator Identified Problem Stops: Orleans Parish


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Figure 44Transit Operator Identified Problem Stops: Jefferson Parish

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5The results from both Orleans and Jefferson parishessuggest that atention should be paid to the problemtransit stops. As Chapter 5 pointed out, transit routesare the site of 85% of recorded pedestrian crashes in Or-leans in 2002. The transit stop survey further highlights

important locations that could be driving this phenom-enon. Transit corridors are significant locations for pe-destrian crashes and need systematic atention to help

signs, and the pedestrian signal phase. The possibleresponse categories included: adequate, some/not all,poor condition, and none (Table 15).

In Orleans Parish, transit employees ratings appeared

to swing from the extremes of adequate to none.Unfortunately, no response was also a dominant re-sponse with 24% of all survey fields returned blank It N


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destrian crashes and need systematic atention to helpimprove safety.

SurveyofPedestrianConditions

In addition to identifying perceived problem locationsfor pedestrians, the quality of the environment around

transit stops was also surveyed. In Orleans Parish, Lead-er and Associates asked transit employees to rate thequality of pedestrian striping, sidewalks, curb ramps,shelters and benches, trashcans, lighting, pedestrian

Table 15Orleans Parish Transit Survey Responses

PavementStriping

Side-walks

CurbRamps

Shelters/Benches

TrashCans

Lighting PedestrianSigns

PedestrianSignal Phase

No Response 19% 27% 15% 18% 23% 34% 28% 29%

None 23% 4% 34% 70% 39% 29% 35% 34%

Poor Condition 18% 16% 9% 0% 0% 1% 1% 1%

Some, Not All 15% 13% 12% 5% 11% 10% 4% 3%

Adequate 26% 39% 29% 7% 26% 25% 31% 33%

sponse with 24% of all survey fields returned blank. Itis difficult from these responses to create a meaningfulportrait of the overall conditions of transit stops thatcould be used to help direct resources.

In Jefferson Parish, GCR surveyed the condition of thepedestrian environment around the problem transitstops (Table 16). While nearly all fields in the surveywere populated, it was still diffi cult to assess the pol-icy implications of the findings in general. The side-walks, curb ramps, and lighting categories did not

Table 16

Jefferson Parish Transit Survey ResponsesPavementStriping

Side-walks

CurbRamps

Shelters/Benches

TrashCans Lighting

PedestrianSigns

PedestrianSignal Phase

No Response 4% 2% 4% % % 4% 2% 2%

None 44% 15% 24% % % 11% 93% 93%

Poor Condition 11% 7% 5% % % 24% 0% 0%

Some, Not All 20% 47% 42% % % 18% 4% 4%

Adequate 22% 29% 25% % % 44% 2% 2%

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Figure 45Downtown Bike Rack Plan, Phase 1

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The bridges over these bodies of water ofen do nothave suffi cient width to accommodate cyclists. These

bridges then act as significant breakages in the system,trapping cyclists to small areas. In addition to working

to make these bridges more cycling-friendly, one wayof overcoming bridges and roadways lacking adequate

bicycle access is to utilize transit as a way to transportbicycles through these choke points and hazardous cor-ridors. One widely used technique to accomplish this isto install bike racks on transit busses. This program isgenerally referred to as Bike-on-Bus.

In many ways Bike-on-Bus equipment helps to strength-

en the bicycle network by providing an accessible routethrough diffi cult choke points. This is particularly

important in areas of Jefferson Parish and New OrleansEast where roadways are the least conducive to bicy-cling. Bike-on-bus in effect allows an accommodationsafety zone that moves cyclists around difficult areas

while necessary changes are being made to the bicyclenetwork. These changes will take time as one of themost significant barriers to cycling is poor bridge de-sign. Bridges can only realistically be modified whenthe bridge is refurbished or replaced at the end of itslife-cycle. While it takes time to fund and retrofit bridgesover the numerous canals and waterways in the area,

bike-on-bus can act as a short-term remedy to breach themany difficult-to-access areas of the region.

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Figure 46Downtown Bike Rack Plan, Phase 2

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Bike-on-bus operates through a rack system that is in-stalled on the front, exterior of the bus. This places therack in a position that is clearly visible to the operator.The process of pulling the equipment open and seting

the bicycle into the carrier takes less than a minute. Allusers must watch a training video that provides themwith the appropriate technique for securing the bicycle.A certification card is then issued to the Bike-on-Bus userthat must be presented to the bus operator when utiliz-ing the system.

JeffersonParishTransit(JeT)

The Louisiana Transit Authority, through the work ofMike Seither, was instrumental in helping to spur de-

velopment of the bike-on-bus program in Jefferson Par-ish. In 1995, Jefferson Parish became the first area tran-sit agency to implement bike-on-bus with service onthree routes. By 1996, Jefferson Parish Transit (JeT) had

expanded the use of bike-on-bus service to their entireEast and Westbank fleets.

Full data on use of the bike on bus was first collectedin 2000. Data collected on use showed that there were15,757 uses of bike on bus in 2000. By 2001, this figurehad grown to 23,031. Subsequent years have shown amodest decrease from the 2001 figure. In 2002, 19,462people used bike-on-bus. In 2003, the figure fell againto 16,666. In 2004, however, the figures have begun torebound with 21,075 bike on bus users (Figure 47).

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Figure 47Jefferson Transit Bike-on-Bus Users 2000-2004

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One reason for the fluctuation of bike-on-bus figuresmay be the prevalence of several large-scale construc-tion projects on main transit arteries in 2002 and 2003.According to Karleene Smith of GCR, these projects

helped make access to the routes difficult. With the com-pletion of these projects, bike-on-bus usage has begunto rebound.

While these figures have shown improvement, there hasbeen litle active promotion of the bike-on-bus programafer a brief initial campaign. With the imminent startof the bike-on-bus program in Orleans Parish, the timemay be ripe for a new promotion campaign that can helpexpand the awareness and use of the system.

RegionalTransitAuthority(RTA)

The Regional Transit Authority has also begun a bike-on-bus program. The RTA authorized the purchase of375 stainless steel Bike-on-Bus racks in the spring of2003. The cost of each rack was $995 for a total purchaseprice of $373,125. Funding for the racks came from Sec-tion 5307 (formerly section 9) formula grant from the

Federal Transit Administration for capital and planning

projects. $139,000 was garnered from 2003 funding andthe remaining $234,125 came from previous years fund-ing. By October 2004, the bid process and installation ofall racks was complete. The RTA has been working to in-

stitute a certification process that will allow joint JeT andRTA Bike-on-Bus certification. One card will be accepted

by both transit agencies whenfinalized. Operator train-ing to ensure safe loading and unloading of the bicyclesis also underway. The seamless integration of bike-on-

bus service between the two parishes should help to sig-nificantly improve access to cyclists on transit.

St. BernardTransit

The small fleet of St. Bernard Transit busses does nothave Bike-on-Bus equipment to date.

Conclusion

Both bike-on-bus and bicycle parking initiatives havebegun to gather momentum in the Metropolitan area inrecent years. These two initiatives help to make cycling

a more atractive commuting option by working to mini-mize some of the significant obstacles that have made

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cycling trips complicated events. By providing bicycleparking spaces in the CBD, the current initiative seeksto provide at least the minimum necessary condition forcommuting, a place to store the bicycle. In the future,efforts should be made to both expand the coverage of

racks to other parts of the city and, importantly, to iden-tify locker and shower facilities that address the full ex-tent of end of trip facilities necessary to make cycling anatractive commuting option. Bike-on-bus initiatives in

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g pJefferson and Orleans parishes show important progressin providing a seamless integration between the adja-cent parishes. These efforts should now make it possiblefor cyclists to breach some of the significant barriers thatcurrently limit the extent of bicycle travel. While bike-on-bus programs help to extend access to cyclists, they

should be coupled with efforts to improve the on-streetbicycling network. By working from multiple angles,bicycling improvements can help to create a fully inte-grated network.



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5Figure 52

Central Avenue Corridor North

that slow down motorists, but also cyclists. Constantstarting and stopping for bicycles is problematic. Somethought should be given to improving the flow of cy-clists through these multiple intersections. 37th Streetcrosses the Elmwood Canal via a pedestrian/bike bridge

between Wilson Drive and Academy Drive.

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37th Street

Pedestrian/Bike bridge over Elmwood Canal

Page Drive from 37th Page Street to Yale Street

This segment length is 1.2 miles. Page Drive has theright of way at most intersections. The crossing at WestEsplanade Avenue has a pedestrian/bike bridge acrossthe street and the canal and a traffic signal on the southside of West Esplanade Avenue. This bridge may need

to have beter access, as the curved ramp and lack of apedestrian/bike street crossing requires one to walk thebike across both the road and the bridge. Girard Play-ground is one block east of the corridor between IrvingStreet and West Esplanade Avenue.

Green Acres Road from Yale Street to Utica Street

This segment length is .5 miles. Page Drive ends at YaleStreet Turn east on Yale Street for one block, then south

on Green Acres Road The crossing at Veterans Boule-

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1 Utica Street from Green Acres Road toTranscontinental Drive

This segment length is .3 miles. Green Acres Road endsat Utica Street. Turn east on Utica Street. Utica Street is

just north of and parallels I-10, so there is no cross traf-

fic.

Transcontinental Drive from Utica Street to West Na-poleon Avenue

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vard is protected by a traffi c signal and intersects theJET bus route (E-1 Veterans). This intersection has a fairamount of traffic and could be difficult for less experi-enced cyclists. Signing the area as a bike route couldhelp alert lefor right turning vehicles to the presenceof cyclists.

Pedestrian/Bike bridge over West Esplanade Canal

Green Acres Rd. crossing Veterans Blvd.

This segment length is .7 miles. Turn south on Trans-continental Drive. Traffic on Transcontinental Drivecan be heavy at times. While there is no shoulder alongTranscontinental Drive, there is a sidewalk under theInterstate. Bicyclists that feel uncomfortable in traffic

could walk their bicycles under the Interstate and thentake a side street to avoid this corridor. For cyclists us-ing Transcontinental Drive, extreme care must be takenwhen turning lef at either end of this portion of theroute. There were four recorded bike crashes at the in-tersection of Transcontinental Drive and West NapoleonAvenue from 1999 to the first quarter of 2003. The routewould be greatly enhanced if extra width could be pro-vided along this area. Transcontinental Drive intersectsYork Street, which connects the corridor to Lafreniere

Park via a .9 mile ride.

Transcontinental at the I-10 underpass

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7Figure 53

Central Avenue Corridor South

West Napoleon Avenue from Transcontinental Drive toHouma Boulevard

This segment length is .9 miles. Turn east on West Na-poleon Avenue. At present, West Napoleon Avenue, dueto the width of the roadway and traffic density, is suit-

able for skill level A and B riders; however, future planscall for extending West Napoleon Avenue both east andwest. When this occurs, traffic volume will greatly in-crease. To accommodate all riders, extra width or other

bicycle facilities should be considered for this overlay

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project. The corridor passes by the Eastbank RegionalLibrary, which has a bike rack in front of it.

Houma Boulevard from West Napoleon Avenue toAirline Drive

This segment length is 1.3 miles. Turn south on Houma

Boulevard. This is a lightly traveled residential road thathas the right of way at most intersections. The crossing atWest Metairie Avenue is in need of improvement. Hou-ma Boulevard used to go directly through West MetairieAvenue and the canal in middle West Metairie Avenue.When the bridge was replaced, a double U-turn bridgewas placed just east of the intersection. At present, theonly way cyclists may legally cross West Metairie Av-enue (in a southern direction) is by riding/pushing their

bicycles through the grass for 200 feet. This intersection

West Napoleon

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1 the corridor once again intersects a JET bus route (E-2Airline/Airport). This segment is the most heavily trav-eled and challenging part of the corridor. It is, however,the only way to cross under the Earhart Expressway.Since traffic is so heavy on this segment, the addition ofshoulders is needed to accommodate even skill level A

and B riders.

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West Metairie and Houma Blvd.

poses a significant challenge for bicyclists. Because ofthe volume of traffic using West Metairie Avenue, sometype of bicycle facility, either a pedestrian/bicycle bridgeor extra width, should be considered for this area.

Central Avenue from Airline Drive toJefferson Highway

This segment length is 1.1 miles. At Airline Drive, Hou-ma Boulevard changes into Central Avenue (LA 48) and

Houma Blvd. and Airline Drive

South of Airline Drive, the corridor crosses over eightsets of railroad tracks. Although this makes for a fairlyrough ride, lights, bells and barricades protect all cross-ings. The entrance to the United Parcel Service Depotis in the middle of the rail crossings. At this point, di-rectly underneath the Earhart Expressway, water tendsto pool at times completely covering the southboundlane and part of the northbound lane. Increased drain-age is needed to eliminate this hazard to cyclists as well

as motorists.

Because this route is one of the only ways for cyclistsand motorists to move north/south in this area, futureroad projects should include provision of bicycle facili-ties to improve this vital linkage in the bicycle network.

Central Avenue from Jefferson Highway to River Road

This segment length is .6 miles. At Jefferson Highway,

the corridor once again intersects a JET bus route (E-3

Railroad tracks crossing Central Ave.

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which has intermitent V-shaped curb cuts, not suitablefor riding through. The cyclist must walk the bike across

the north Service Road to negotiate entering the path.Interstate 10 will be widened in the section between the17th Street Canal and Causeway Boulevard with soundwalls erected, possibly impending on the adjacent bikepaths on the north and south I-10 service roads. Cyclingaccommodations should be incorporated into thedesign.

The separate path continues upriver (westerly) and

turns lefunder Interstate 10 between Andrews and Rosa

Veterans Blvd. looking east to Orleans Parish

Veterans Blvd. west to Jefferson Parish

Crossing at Carrollton Blvd. and Veterals Blvd.

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3

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Northline Drive to Airline Blvd.

The route turns river bound from Northline Driveonto Monticello Road and the street condition andneighborhood characteristics change from good to poor.Monticello Road is a poorly marked 2-lane roadway.

Cyclists continue on Monticello Road to AirlineBoulevard, approximately 8 blocks. Airline Boulevard isa major impediment for two reasons: the boulevard is an8-lane corridor with 50 mph, high volume traffic and theNew Orleans Union Passenger Terminal railroad track


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gtraverse east-west on the riverside of Airline Boulevard.Both thoroughfares are highly dangerous to cyclistsand pedestrians. Yet cyclists and pedestrians routinelycross here to reach a bus stop located on the riverside

of Airline Boulevard at this location. In addition, onthe riverside of the track, Monticello Road continuesunimpeded to S. Claiborne Avenue. While the Regional

Planning Commission cannot advocate this as a saferoute, it is the route being used today for lack of anyother corridor.

A complete review of this critical crossing (road andrail) should be underway by the RPC to see if a designsolution is possible. A desire line over the railroad

tracks from the Holly Grove neighborhood (riverside

of the railroad track) to the bus stop is visible in aerialphotographs of the area. Cyclists carry their bicyclesover the track at this location to reach the street networkon the other side. The next closest roadway is the cur-rent extension of Dakin Street in Jefferson Parish. DakinStreet, however, will accommodate large numbers of carand truck traffic from Labarre Business Park, Earhart Ex-pressway and Jefferson Highway. There needs to be care-ful consideration of alternative routes or an improvedcrossing design to replace this unsafe and unofficialpedestrian and bicycle rail crossing with a linkage thatis safe and easy to use.

South Claiborne to the Mississippi River

Monticello Canal is on the upriver side of MonticelloStreet through the Holly Grove neighborhood. At SouthClaiborne the route turns upriver for a short blockcrossing into Jefferson Parish where South ClaiborneAvenue becomes Jefferson Highway.

The cyclist must cross three lanes of traffi c into themedian on Jefferson Highway to turn lefacross threemore lanes of traffi c onto Monticello, now located on

the upriver side of Monticello Canal in Jefferson Parish.

Monticello Ave. riverbound at Airline Blvd.

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Monticello Street is a recently repaved 2-lane roadwayhere, posted at 25 mph.

It is also state route LA 611-8. Today this route experiences

litle traffic but once the Dakin Street extension is

opened, traffi c will likely increase and the intersectionat Jefferson Highway and Monticello may become morecongested. Traffic signalization and careful planning toaccommodate cyclists at this intersection are needed.Monticello crosses the New Orleans Public Belt Railroadsingle track near River Road. The crossing has beenupgraded and is fairly smooth for cyclists although care

should always be taken to cross perpendicular to thetrack to avoid geting a bicycle tire caught in the trackslot. The railroad crossing is not signalized but becausethe number of trains is low, the crossing is manageable.

The final obstacle for the cyclist to enter the RiverfrontEast Bank Levee path from the Jefferson-Orleans routeis the intersection at River Road. A curve in the roadupriver one block impairs the ability to see oncoming

traffi c. A traffi c calming measure should be installedhere and a bicycle cross alert signal considered.

Wisner/Jefferson Davis/UptownCorridor

This route takes the cyclist from Lake Pontchartrain atBayou St. John to the Mississippi River near AudubonPark. While the route has several more difficult sections,

Monticello (LA 611-8) from Jefferson Hwy. looking riverbound

Monticello crossing of NOPB track near River RoadJefferson Hwy. at jog between Monticello Rd. in Orleansand Monticello in Jefferson, looking upriver (westerly)

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Figure 54Jefferson/Orleans Corridor North


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Figure 55Jefferson/Orleans Corridor South

it is, in general, a fairly good route to move north/southin Orleans Parish. There were 18 recorded crashes alongthis route from 1999 to the first quarter of 2003. Of thesecrashes, all but four occurred along the Jefferson DavisParkway portion of the route.

The route is divided into two basic sections: the Wis-ner Avenue/Jefferson Davis Parkway section and theUptown/Nashville Avenue section (Figures 56, 57, and58). The Wisner Boulevard section joins Uptown bicycletraffic to Mid-City and the Lakefront via relatively low-volume streets. This route is also a critical link for stu-dents and employees of the University of New Orleans,Southern University of New Orleans, and John F. Ken-nedy High School. Other points of interest or employ-ment centers near the route are the Agriculture ResearchCenter at Robert E. Lee and Wisner boulevards, themany amenities of City Park, the Fairgrounds, the NewOrleans Museum of Art, and the Pitot House. The route

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the Interstate on Wisner Boulevard. The service roadsthat enter and exit onto Zachary Taylor Drive near thePan Am Stadium provide access offof and onto WisnerBoulevard. These roads are in fairly poor condition andshould be candidates for resurfacing if possible. Theother City Park roadways named as the bike route, Golf

Drive and Dreyfus Avenue, are in fairly good condition

Beauregard Ave. between Robert E. Lee Blvd. andLakeshore Dr.

Wisner between Harrison and Mirabeau

I-10 and railroad underpass in City Park

aside from road debris that builds up along the shoul-der. The portion that passes under the Interstate, how-ever, is particularly dangerous. The drainage grates onthe downhill portion of the underpass are parallel to cy-clists wheels. This type of design can result in dramaticand dangerous crashes as the cyclists wheel becomeslodged in the grate resulting in an over the handlebars

crash. These grates should be immediately replacedwith a cycling-friendly design.On the south side of the Interstate, the narrow roadwayscarry a fairly high number of cars to the revenue pro-ducing venues of the museum, the tennis courts, and the

botanical gardens. At certain times, especially aroundthe museum, the amount of traffic and on-street park-ing can make cycling difficult. One solution that could

balance the need of the park to keep generating revenue

while at the same time accommodating cyclists and pe-destrians is a dedicated bike lane through the park. Thepossibility of signing and painting a bike lane throughthe park should be explored.

Moss St. at Carrollton Ave. to Jefferson Davis Park-way at Iberville St.

The crossing at Moss Street and Carrollton Avenue isheavily trafficked and potentially dangerous to the bi-

cycle and pedestrian. This intersection should be exam-


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In this segment, the paths end point deposits bicyclistson the street (and collects them offthe street) into/fromthe leflane of traffic mid-block. This may be dangerous,as bicycles have to leave and enter the neutral groundpath in a surprising, unsigned and uncontrolled point.

Riverbound: Vendome between Earhart and Fountain-bleau

Lakebound: Octavia between Earhart and Fountainb-leau

In this segment, the lanes of Jefferson Davis Parkway,e iou ly e a ated by a ide eut al ou d lit

roadwork involves replacing a bridge, the work couldgo on for some time. Efforts should be made to mediatethis situation with signage and regular street sweepingof the minimal cyclable area.


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tanBicycleandPedestrian previously separated by a wide neutral ground, split

around a city block and become two-way streets. Rather

than keep the corridor on one street, it seems safer todivide the corridor by direction and to keep bicyclestraveling with the flow of traffic on separate streets forseveral blocks.

The intersection area in the vicinity of Washington Ave-nue and Earhart Boulevard has become a major problemfor cyclists. Recent roadwork has turned what used to bea difficult crossing with higher traffic volume into a con-

fused, high volume intersection crossing. Because the

Traveling riverbound, Vendome Place is a wide streetwith low traffic. In the past, the pavement on this sec-tion was in terrible condition, acting as a traffic-calmingdevice. The pavement surface has been improved in thisarea, however. Speeds have increased and the ridingconditions have become more challenging. Residentsand bicyclists may desire intentional traffic calming de-vices to keep the residential character of the street.

Traveling lakebound, Octavia Street is a wide street withexcellent pavement over most of the segment. There area few big cracks at the lake end of the street that wouldrequire improving.

Nashville between Fountainbleau and Claiborne

Nashville Avenue in this segment has a neutral ground,four travel lanes, and on street parking on both sides.It has an 18-foot curb lane including on-street parking.

The pavement condition is good.

Neutral Ground Path on Jefferson Davis Parkway be-tween Bienville and Iberville streets

Jefferson Davis neutral ground at Tulane Avenue, I-10Overpass in the background

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Figure 58Wisner Corridor South (Nashville Area)


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Nashville between Claiborne and Willow

Nashville Avenue in this segment has no neutral groundand two travel lanes. It has a narrow curb lane. School

buses, service vehicles, and school drop-offs make use ofthe curbside space. This creates a difficult and danger-ous situation for cyclists during the heavily traffickedafernoon and morning rushes. This section is particu-

larly important because it provides a linkage for Tulane/Loyola university students (as well as Ursuline and Mc-Main students) to campuses along Willow Street.

In addition, this segment has extremely poor pavementcondition. It has a dangerous pavement change/crackthat is parallel to the flow of traffic and in an area where

bicycles travel. The street bulges--it has a significantslope between the centerline and curb. All of these fac-

tors make this section extraordinarily difficult to traverse

Jefferson Davis intersection with Earhart andWashington Avenue

during a traffic times. Consideration should be given toplacing a bike lane on Nashville Avenue to improve thesituation.

Nashville between Willow and St. Charles

The pavement is slightly beter in this segment. The curblane is about 16 feet. On-street parking significantly r

new orleans metropolitan bicycle and pedestrian plan

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