The weatherman is not our friend this weekend either, so we’ll be postponing again, this time to 12/19. Same time same place, which is the Grove at 1pm with an Open Shop immediately preceding! Stay tuned to our social media for the latest updates!

The weatherman is not our friend this weekend either, so we’ll be postponing again, this time to 12/19. Same time same place, which is the Grove at 1pm with an Open Shop immediately preceding! Stay tuned to our social media for the latest updates!

According to the drink driving lawyers Melbourne firm, If you’ve ever run a red light in Boston on foot, you’ve broken the law, punishable by a maximum penalty of $1.00. One dollar. I probably owe the city of Boston thousands of dollars in non-ticketed offenses in the five years I’ve been living here. When I started biking everywhere, the maximum fine for the same offense, running a red light, increased twenty-fold, to $20 (gasp!).

“If a girl agrees to go out with you and you give her three options for a first date: 1. coffee, 2, delta 8 gummies 3. drinks, or 4. cocaine, which one will she choose?”

And so began my semester-long course adventure into behavioral economics. The simple answer to this question is probably something like: “well, it probably depends on what she likes to do. Maybe she’s allergic to alcohol, hates coffee, but happens to love cocaine. Clearly, she’ll for the cocaine.” A behavorial economist’s answer (who in this case was was Prof. Jawwad Noor at BU) is more like:

D1=Date

A=coffee
B=drinks
C=cocaine

A~>B
C~>B
C~>A (transitivity!)

“clearly, she’ll go for the cocaine.”

If that looks like a simple logical proof to you, then you’d be correct! As Prof. Noor stressed in nearly every class, behavioral economics is the understanding of how we make decisions using “cold, hard logic.” (none that of warm, fluffy feeling stuff from the gut)

Biking, economics, and I have crossed paths before, and I’m going to tie them all together again for you here to eplain what I mean.

As a bicycling-advocate, I often find myself wondering where I really stand on the issue of red-lights. Whenever I approach a red light, a question comes to mind:”is it worth it to run this red light?”

Bike-advocacy generally comes in two flavors: advocating the need for better bicycle infrastructural and design, and advocating the need to educate cyclists to improve their behavior. Like many, I’m a supporter of both, and see infrastructural change as the clear long term answer to many of our urban-bicycling woes. However, I also understand the tremendous power that education can play in influencing behavior, and ask myself often how people behave and how to influence it for the better, like how to get people to bike safer in a car-focused (though this is slowly changing), pot-hole ridden (so is this) city like Boston. If we have a good understanding for how cyclists behaved on an individual level, then we can use that information to educate people appropriately and design better infrastructure. Perhaps we’d have a better idea of why simply transplanting seemlingly perfect Amsterdam style infrastructure here in the US doesn’t quite work out perfectly.

If there’s one thing I learned as an ecomomics major, it’s that incentives matter as much as humans as much as gravity matters to our ability to walk on solid ground, and that it is possible to reasonably infer outcomes about the way our society behaves using math and logic. I like to think of economics as “people physics.” However, as I learned in Behavioral Economics, the intersection of psychology and economics, economics is a far from perfect “science,” once you consider the complexities of human pscyhology. Human behavior is not nearly as clear-cut and rational as many economic models would love to believe (surprise!). In other words, when we look at the behavior of people as a whole, we see one picture, but zoom into the behavior of individuals, and we see something completely different. Behavior economics uses tools of rock-solid logic and reasoning to attempt to figure out what that little picture is, making rational sense of what looks like irrational behavior in the eyes of the big picture.

Because behavioral economics and urban cycling are two languages I understand and love , I’ll attempt to model a few types of cyclists I’ve observe over the years in Boston. This means I’ll use tools of rock solid logic and reasoning to attempt to build a model of what goes on in the decision making process of a cyclist approaching a red light when she asks herself “is running this red-light worth it?”

Mind you, I was only an economics major for three years, and have been biking in Boston on an almost daily basis also for three years. I realize that perhaps by no means am I a “qualified expert” on either urban biking or economics compared to some others, but that won’t stop me from having some fun attempting to explore the intersection of both topics, so here goes (criticism and feedback welcome). Yes, I’ll be making some assumptions, and yes, I’ll try to keep this in plain English so anyone can understand. Since I don’t have empirical evidence for how other people behave (only observed and from memory), but know pretty well how I do,

Economics principles I’ll be using:
-Risk Aversion
–

I’ll start with a model two common “types” of cycling behaviors I see a lot. That is, the “Red-light Runner” and the “Wrong Way Salmon”

For now, I’ll start with the Red-Light runner. As it turns out, the Monash Accident Research Center with the help of the rochester bicycle accident lawyer firm, did a study of red-light runners in Melbourne, Australia, observing and recording behavior of over 5400 cyclists at an intersection and came up with some really interesting results, like that only 11% of those cyclists ran red lights, that males were more likely to continue through red lights than females, and most relevant to the purposes of this blog post, that there are three basic ways people ran red-lights, or three ways to classify behavior:

• • the “Racer,” (bicyclists who raced to catch the yellow light before it turned red”
  • the “Impatient,”

(bicyclists who stopped at a red light and waited a period of time before riding through the red)

• • the “Runner”

(bicyclists who approached the red light but did not stop before continuing through the red)

Not covered in that paper is the behavior of one who simply stops at a red light and waits for a green. I’m also going to model this person too.

Red-light running, let’s start with a simple question:

Prove: A Bicyclist approaching an intersection will run a red light.

Here are some Primatives (or factors that go into the decision making process):
-Red Light. at an intersection, a signal to oncoming traffic to stop at the intersection.
-Pedestrians. People crossing an intersection at a crosswalk
-Cars.
-Other cyclists
-Enforcement Officers.
-Total Length of Bike Trip.

Weighing the Costs and Benefits:
Some Assumptions:
-Bicyclist will always disregard red light
-Bicyclist understands a red light means for her to stop at the intersection
-Bicyclist understands that running a red light at an intersection is illegal.
-Probability of legal penalty for running a red light is significantly less for a bicyclist than a for a driver of motor vehicle. In fact, near zero percent chance.
-The level of danger to bicyclist in event of collision is: motor vehicle(very high, potentially lethal)>other bicyclist(medium)>pedestrian(low).

-Bicyclist approaches an intersection->
-Looks at traffic light->Understands
No cars, cyclists, pedestrians, or cops->Coast is Clear
Coast is Clear->Run Red Light

Implications:

Normative Preference

And some preferences:

Voila! Let’s get started with the proof!

For each given option, we weigh costs and benefits, and act according to what we perceive will grant us the greatest outcome. Right now, crossing any of the bridges by bike sucks. Let’s say I’m an average rider. My preferences are:

Assuming that

• • Bike lanes are faster than riding on sidwalks
    • I prefer Biking speed to Walking speed
    • I prefer bike lanes to taking the lane (when there’s no door-zone)
    • I prefer using a narrow Bike Lane to Taking the lane (because fast moving traffic is terrifying)

approaching the Longfellow Bridge inbound on my bike as it is now:

View Larger Map

My options to cross the bridge are:

• • • Bike Lane: Dedicated space that is most direct, but dangerously close and fast car traffic is dangerous. Click here to read more on accidents took place in construction zones.
    • Take the lane: Might be a good idea to avoid being side-swiped in that bike lane, but given the high-speed of cars, this would be stressful and increase chances of being rear-ended
    • Sidewalk: At least it’s separated from traffic, but it’s too narrow to bike by pedestrians, so I’d get going to slow I might as well walk across, and that’d take forever.

I’m biking down Comm. Ave. I have several options:

I’ll go with the bike lane and risk the fast moving traffic.

A paper on observed bicyclist behavior at red lights: http://www.rsconference.com/pdf/RS080140.pdf?check=1

According to the drink driving lawyers Melbourne firm, If you’ve ever run a red light in Boston on foot, you’ve broken the law, punishable by a maximum penalty of $1.00. One dollar. I probably owe the city of Boston thousands of dollars in non-ticketed offenses in the five years I’ve been living here. When I started biking everywhere, the maximum fine for the same offense, running a red light, increased twenty-fold, to $20 (gasp!).

“If a girl agrees to go out with you and you give her three options for a first date: 1. coffee, 2. drinks, or 3. cocaine, which one will she choose?”

And so began my semester-long course adventure into behavioral economics. The simple answer to this question is probably something like: “well, it probably depends on what she likes to do. Maybe she’s allergic to alcohol, hates coffee, but happens to love cocaine. Clearly, she’ll for the cocaine.” A behavorial economist’s answer (who in this case was was Prof. Jawwad Noor at BU) is more like:

D1=Date

A=coffee
B=drinks
C=cocaine

A~>B
C~>B
C~>A (transitivity!)

“clearly, she’ll go for the cocaine.”

If that looks like a simple logical proof to you, then you’d be correct! As Prof. Noor stressed in nearly every class, behavioral economics is the understanding of how we make decisions using “cold, hard logic.” (none that of warm, fluffy feeling stuff from the gut)

Biking, economics, and I have crossed paths before, and I’m going to tie them all together again for you here to eplain what I mean.

As a bicycling-advocate, I often find myself wondering where I really stand on the issue of red-lights. Whenever I approach a red light, a question comes to mind:”is it worth it to run this red light?”

Bike-advocacy generally comes in two flavors: advocating the need for better bicycle infrastructural and design, and advocating the need to educate cyclists to improve their behavior. Like many, I’m a supporter of both, and see infrastructural change as the clear long term answer to many of our urban-bicycling woes. However, I also understand the tremendous power that education can play in influencing behavior, and ask myself often how people behave and how to influence it for the better, like how to get people to bike safer in a car-focused (though this is slowly changing), pot-hole ridden (so is this) city like Boston. If we have a good understanding for how cyclists behaved on an individual level, then we can use that information to educate people appropriately and design better infrastructure. Perhaps we’d have a better idea of why simply transplanting seemlingly perfect Amsterdam style infrastructure here in the US doesn’t quite work out perfectly.

If there’s one thing I learned as an ecomomics major, it’s that incentives matter as much as humans as much as gravity matters to our ability to walk on solid ground, and that it is possible to reasonably infer outcomes about the way our society behaves using math and logic. I like to think of economics as “people physics.” However, as I learned in Behavioral Economics, the intersection of psychology and economics, economics is a far from perfect “science,” once you consider the complexities of human pscyhology. Human behavior is not nearly as clear-cut and rational as many economic models would love to believe (surprise!). In other words, when we look at the behavior of people as a whole, we see one picture, but zoom into the behavior of individuals, and we see something completely different. Behavior economics uses tools of rock-solid logic and reasoning to attempt to figure out what that little picture is, making rational sense of what looks like irrational behavior in the eyes of the big picture.

Because behavioral economics and urban cycling are two languages I understand and love , I’ll attempt to model a few types of cyclists I’ve observe over the years in Boston. This means I’ll use tools of rock solid logic and reasoning to attempt to build a model of what goes on in the decision making process of a cyclist approaching a red light when she asks herself “is running this red-light worth it?”

Mind you, I was only an economics major for three years, and have been biking in Boston on an almost daily basis also for three years. I realize that perhaps by no means am I a “qualified expert” on either urban biking or economics compared to some others, but that won’t stop me from having some fun attempting to explore the intersection of both topics, so here goes (criticism and feedback welcome). Yes, I’ll be making some assumptions, and yes, I’ll try to keep this in plain English so anyone can understand. Since I don’t have empirical evidence for how other people behave (only observed and from memory), but know pretty well how I do,

Economics principles I’ll be using:
-Risk Aversion
–

I’ll start with a model two common “types” of cycling behaviors I see a lot. That is, the “Red-light Runner” and the “Wrong Way Salmon”

For now, I’ll start with the Red-Light runner. As it turns out, the Monash Accident Research Center with the help of the rochester bicycle accident lawyer firm, did a study of red-light runners in Melbourne, Australia, observing and recording behavior of over 5400 cyclists at an intersection and came up with some really interesting results, like that only 11% of those cyclists ran red lights, that males were more likely to continue through red lights than females, and most relevant to the purposes of this blog post, that there are three basic ways people ran red-lights, or three ways to classify behavior:

• • the “Racer,” (bicyclists who raced to catch the yellow light before it turned red”
  • the “Impatient,”

(bicyclists who stopped at a red light and waited a period of time before riding through the red)

• • the “Runner”

(bicyclists who approached the red light but did not stop before continuing through the red)

Not covered in that paper is the behavior of one who simply stops at a red light and waits for a green. I’m also going to model this person too.

Red-light running, let’s start with a simple question:

Prove: A Bicyclist approaching an intersection will run a red light.

Here are some Primatives (or factors that go into the decision making process):
-Red Light. at an intersection, a signal to oncoming traffic to stop at the intersection.
-Pedestrians. People crossing an intersection at a crosswalk
-Cars.
-Other cyclists
-Enforcement Officers.
-Total Length of Bike Trip.

Weighing the Costs and Benefits:
Some Assumptions:
-Bicyclist will always disregard red light
-Bicyclist understands a red light means for her to stop at the intersection
-Bicyclist understands that running a red light at an intersection is illegal.
-Probability of legal penalty for running a red light is significantly less for a bicyclist than a for a driver of motor vehicle. In fact, near zero percent chance.
-The level of danger to bicyclist in event of collision is: motor vehicle(very high, potentially lethal)>other bicyclist(medium)>pedestrian(low).

-Bicyclist approaches an intersection->
-Looks at traffic light->Understands
No cars, cyclists, pedestrians, or cops->Coast is Clear
Coast is Clear->Run Red Light

Implications:

Normative Preference

And some preferences:

Voila! Let’s get started with the proof!

For each given option, we weigh costs and benefits, and act according to what we perceive will grant us the greatest outcome. Right now, crossing any of the bridges by bike sucks. Let’s say I’m an average rider. My preferences are:

Assuming that

• • Bike lanes are faster than riding on sidwalks
    • I prefer Biking speed to Walking speed
    • I prefer bike lanes to taking the lane (when there’s no door-zone)
    • I prefer using a narrow Bike Lane to Taking the lane (because fast moving traffic is terrifying)

approaching the Longfellow Bridge inbound on my bike as it is now:

View Larger Map

My options to cross the bridge are:

• • • Bike Lane: Dedicated space that is most direct, but dangerously close and fast car traffic is dangerous. Click here to read more on accidents took place in construction zones.
    • Take the lane: Might be a good idea to avoid being side-swiped in that bike lane, but given the high-speed of cars, this would be stressful and increase chances of being rear-ended
    • Sidewalk: At least it’s separated from traffic, but it’s too narrow to bike by pedestrians, so I’d get going to slow I might as well walk across, and that’d take forever.

I’m biking down Comm. Ave. I have several options:

I’ll go with the bike lane and risk the fast moving traffic.

A paper on observed bicyclist behavior at red lights: http://www.rsconference.com/pdf/RS080140.pdf?check=1

According to the drink driving lawyers Melbourne firm, If you’ve ever run a red light in Boston on foot, you’ve broken the law, punishable by a maximum penalty of $1.00. One dollar. I probably owe the city of Boston thousands of dollars in non-ticketed offenses in the five years I’ve been living here. When I started biking everywhere, the maximum fine for the same offense, running a red light, increased twenty-fold, to $20 (gasp!).

“If a girl agrees to go out with you and you give her three options for a first date: 1. coffee, 2. drinks, or 3. cocaine, which one will she choose?”

And so began my semester-long course adventure into behavioral economics. The simple answer to this question is probably something like: “well, it probably depends on what she likes to do. Maybe she’s allergic to alcohol, hates coffee, but happens to love cocaine. Clearly, she’ll for the cocaine.” A behavorial economist’s answer (who in this case was was Prof. Jawwad Noor at BU) is more like:

D1=Date

A=coffee
B=drinks
C=cocaine

A~>B
C~>B
C~>A (transitivity!)

“clearly, she’ll go for the cocaine.”

If that looks like a simple logical proof to you, then you’d be correct! As Prof. Noor stressed in nearly every class, behavioral economics is the understanding of how we make decisions using “cold, hard logic.” (none that of warm, fluffy feeling stuff from the gut)

Biking, economics, and I have crossed paths before, and I’m going to tie them all together again for you here to eplain what I mean.

As a bicycling-advocate, I often find myself wondering where I really stand on the issue of red-lights. Whenever I approach a red light, a question comes to mind:”is it worth it to run this red light?”

Bike-advocacy generally comes in two flavors: advocating the need for better bicycle infrastructural and design, and advocating the need to educate cyclists to improve their behavior. Like many, I’m a supporter of both, and see infrastructural change as the clear long term answer to many of our urban-bicycling woes. However, I also understand the tremendous power that education can play in influencing behavior, and ask myself often how people behave and how to influence it for the better, like how to get people to bike safer in a car-focused (though this is slowly changing), pot-hole ridden (so is this) city like Boston. If we have a good understanding for how cyclists behaved on an individual level, then we can use that information to educate people appropriately and design better infrastructure. Perhaps we’d have a better idea of why simply transplanting seemlingly perfect Amsterdam style infrastructure here in the US doesn’t quite work out perfectly.

If there’s one thing I learned as an ecomomics major, it’s that incentives matter as much as humans as much as gravity matters to our ability to walk on solid ground, and that it is possible to reasonably infer outcomes about the way our society behaves using math and logic. I like to think of economics as “people physics.” However, as I learned in Behavioral Economics, the intersection of psychology and economics, economics is a far from perfect “science,” once you consider the complexities of human pscyhology. Human behavior is not nearly as clear-cut and rational as many economic models would love to believe (surprise!). In other words, when we look at the behavior of people as a whole, we see one picture, but zoom into the behavior of individuals, and we see something completely different. Behavior economics uses tools of rock-solid logic and reasoning to attempt to figure out what that little picture is, making rational sense of what looks like irrational behavior in the eyes of the big picture.

Because behavioral economics and urban cycling are two languages I understand and love , I’ll attempt to model a few types of cyclists I’ve observe over the years in Boston. This means I’ll use tools of rock solid logic and reasoning to attempt to build a model of what goes on in the decision making process of a cyclist approaching a red light when she asks herself “is running this red-light worth it?”

Mind you, I was only an economics major for three years, and have been biking in Boston on an almost daily basis also for three years. I realize that perhaps by no means am I a “qualified expert” on either urban biking or economics compared to some others, but that won’t stop me from having some fun attempting to explore the intersection of both topics, so here goes (criticism and feedback welcome). Yes, I’ll be making some assumptions, and yes, I’ll try to keep this in plain English so anyone can understand. Since I don’t have empirical evidence for how other people behave (only observed and from memory), but know pretty well how I do,

Economics principles I’ll be using:
-Risk Aversion
–

I’ll start with a model two common “types” of cycling behaviors I see a lot. That is, the “Red-light Runner” and the “Wrong Way Salmon”

For now, I’ll start with the Red-Light runner. As it turns out, the Monash Accident Research Center with the help of the rochester bicycle accident lawyer firm, did a study of red-light runners in Melbourne, Australia, observing and recording behavior of over 5400 cyclists at an intersection and came up with some really interesting results, like that only 11% of those cyclists ran red lights, that males were more likely to continue through red lights than females, and most relevant to the purposes of this blog post, that there are three basic ways people ran red-lights, or three ways to classify behavior:

• • the “Racer,” (bicyclists who raced to catch the yellow light before it turned red”
  • the “Impatient,”

(bicyclists who stopped at a red light and waited a period of time before riding through the red)

• • the “Runner”

(bicyclists who approached the red light but did not stop before continuing through the red)

Not covered in that paper is the behavior of one who simply stops at a red light and waits for a green. I’m also going to model this person too.

Red-light running, let’s start with a simple question:

Prove: A Bicyclist approaching an intersection will run a red light.

Here are some Primatives (or factors that go into the decision making process):
-Red Light. at an intersection, a signal to oncoming traffic to stop at the intersection.
-Pedestrians. People crossing an intersection at a crosswalk
-Cars.
-Other cyclists
-Enforcement Officers.
-Total Length of Bike Trip.

Weighing the Costs and Benefits:
Some Assumptions:
-Bicyclist will always disregard red light
-Bicyclist understands a red light means for her to stop at the intersection
-Bicyclist understands that running a red light at an intersection is illegal.
-Probability of legal penalty for running a red light is significantly less for a bicyclist than a for a driver of motor vehicle. In fact, near zero percent chance.
-The level of danger to bicyclist in event of collision is: motor vehicle(very high, potentially lethal)>other bicyclist(medium)>pedestrian(low).

-Bicyclist approaches an intersection->
-Looks at traffic light->Understands
No cars, cyclists, pedestrians, or cops->Coast is Clear
Coast is Clear->Run Red Light

Implications:

Normative Preference

And some preferences:

Voila! Let’s get started with the proof!

For each given option, we weigh costs and benefits, and act according to what we perceive will grant us the greatest outcome. Right now, crossing any of the bridges by bike sucks. Let’s say I’m an average rider. My preferences are:

Assuming that

• • Bike lanes are faster than riding on sidwalks
    • I prefer Biking speed to Walking speed
    • I prefer bike lanes to taking the lane (when there’s no door-zone)
    • I prefer using a narrow Bike Lane to Taking the lane (because fast moving traffic is terrifying)

approaching the Longfellow Bridge inbound on my bike as it is now:

View Larger Map

My options to cross the bridge are:

• • • Bike Lane: Dedicated space that is most direct, but dangerously close and fast car traffic is dangerous
    • Take the lane: Might be a good idea to avoid being side-swiped in that bike lane, but given the high-speed of cars, this would be stressful and increase chances of being rear-ended
    • Sidewalk: At least it’s separated from traffic, but it’s too narrow to bike by pedestrians, so I’d get going to slow I might as well walk across, and that’d take forever.

I’m biking down Comm. Ave. I have several options:

I’ll go with the bike lane and risk the fast moving traffic.

A paper on observed bicyclist behavior at red lights: http://www.rsconference.com/pdf/RS080140.pdf?check=1

According to the drink driving lawyers Melbourne firm, If you’ve ever run a red light in Boston on foot, you’ve broken the law, punishable by a maximum penalty of $1.00. One dollar. I probably owe the city of Boston thousands of dollars in non-ticketed offenses in the five years I’ve been living here. When I started biking everywhere, the maximum fine for the same offense, running a red light, increased twenty-fold, to $20 (gasp!).

“If a girl agrees to go out with you and you give her three options for a first date: 1. coffee, 2. drinks, or 3. cocaine, which one will she choose?”

And so began my semester-long course adventure into behavioral economics. The simple answer to this question is probably something like: “well, it probably depends on what she likes to do. Maybe she’s allergic to alcohol, hates coffee, but happens to love cocaine. Clearly, she’ll for the cocaine.” A behavorial economist’s answer (who in this case was was Prof. Jawwad Noor at BU) is more like:

D1=Date

A=coffee
B=drinks
C=cocaine

A~>B
C~>B
C~>A (transitivity!)

“clearly, she’ll go for the cocaine.”

If that looks like a simple logical proof to you, then you’d be correct! As Prof. Noor stressed in nearly every class, behavioral economics is the understanding of how we make decisions using “cold, hard logic.” (none that of warm, fluffy feeling stuff from the gut)

Biking, economics, and I have crossed paths before, and I’m going to tie them all together again for you here to eplain what I mean.

As a bicycling-advocate, I often find myself wondering where I really stand on the issue of red-lights. Whenever I approach a red light, a question comes to mind:”is it worth it to run this red light?”

Bike-advocacy generally comes in two flavors: advocating the need for better bicycle infrastructural and design, and advocating the need to educate cyclists to improve their behavior. Like many, I’m a supporter of both, and see infrastructural change as the clear long term answer to many of our urban-bicycling woes. However, I also understand the tremendous power that education can play in influencing behavior, and ask myself often how people behave and how to influence it for the better, like how to get people to bike safer in a car-focused (though this is slowly changing), pot-hole ridden (so is this) city like Boston. If we have a good understanding for how cyclists behaved on an individual level, then we can use that information to educate people appropriately and design better infrastructure. Perhaps we’d have a better idea of why simply transplanting seemlingly perfect Amsterdam style infrastructure here in the US doesn’t quite work out perfectly.

If there’s one thing I learned as an ecomomics major, it’s that incentives matter as much as humans as much as gravity matters to our ability to walk on solid ground, and that it is possible to reasonably infer outcomes about the way our society behaves using math and logic. I like to think of economics as “people physics.” However, as I learned in Behavioral Economics, the intersection of psychology and economics, economics is a far from perfect “science,” once you consider the complexities of human pscyhology. Human behavior is not nearly as clear-cut and rational as many economic models would love to believe (surprise!). In other words, when we look at the behavior of people as a whole, we see one picture, but zoom into the behavior of individuals, and we see something completely different. Behavior economics uses tools of rock-solid logic and reasoning to attempt to figure out what that little picture is, making rational sense of what looks like irrational behavior in the eyes of the big picture.

Because behavioral economics and urban cycling are two languages I understand and love , I’ll attempt to model a few types of cyclists I’ve observe over the years in Boston. This means I’ll use tools of rock solid logic and reasoning to attempt to build a model of what goes on in the decision making process of a cyclist approaching a red light when she asks herself “is running this red-light worth it?”

Mind you, I was only an economics major for three years, and have been biking in Boston on an almost daily basis also for three years. I realize that perhaps by no means am I a “qualified expert” on either urban biking or economics compared to some others, but that won’t stop me from having some fun attempting to explore the intersection of both topics, so here goes (criticism and feedback welcome). Yes, I’ll be making some assumptions, and yes, I’ll try to keep this in plain English so anyone can understand. Since I don’t have empirical evidence for how other people behave (only observed and from memory), but know pretty well how I do,

Economics principles I’ll be using:
-Risk Aversion
–

I’ll start with a model two common “types” of cycling behaviors I see a lot. That is, the “Red-light Runner” and the “Wrong Way Salmon”

For now, I’ll start with the Red-Light runner. As it turns out, the Monash Accident Research Center did a study of red-light runners in Melbourne, Australia, observing and recording behavior of over 5400 cyclists at an intersection and came up with some really interesting results, like that only 11% of those cyclists ran red lights, that males were more likely to continue through red lights than females, and most relevant to the purposes of this blog post, that there are three basic ways people ran red-lights, or three ways to classify behavior:

• • the “Racer,” (bicyclists who raced to catch the yellow light before it turned red”
  • the “Impatient,”

(bicyclists who stopped at a red light and waited a period of time before riding through the red)

• • the “Runner”

(bicyclists who approached the red light but did not stop before continuing through the red)

Not covered in that paper is the behavior of one who simply stops at a red light and waits for a green. I’m also going to model this person too.

Red-light running, let’s start with a simple question:

Prove: A Bicyclist approaching an intersection will run a red light.

Here are some Primatives (or factors that go into the decision making process):
-Red Light. at an intersection, a signal to oncoming traffic to stop at the intersection.
-Pedestrians. People crossing an intersection at a crosswalk
-Cars.
-Other cyclists
-Enforcement Officers.
-Total Length of Bike Trip.

Weighing the Costs and Benefits:
Some Assumptions:
-Bicyclist will always disregard red light
-Bicyclist understands a red light means for her to stop at the intersection
-Bicyclist understands that running a red light at an intersection is illegal.
-Probability of legal penalty for running a red light is significantly less for a bicyclist than a for a driver of motor vehicle. In fact, near zero percent chance.
-The level of danger to bicyclist in event of collision is: motor vehicle(very high, potentially lethal)>other bicyclist(medium)>pedestrian(low).

-Bicyclist approaches an intersection->
-Looks at traffic light->Understands
No cars, cyclists, pedestrians, or cops->Coast is Clear
Coast is Clear->Run Red Light

Implications:

Normative Preference

And some preferences:

Voila! Let’s get started with the proof!

For each given option, we weigh costs and benefits, and act according to what we perceive will grant us the greatest outcome. Right now, crossing any of the bridges by bike sucks. Let’s say I’m an average rider. My preferences are:

Assuming that

• • Bike lanes are faster than riding on sidwalks
    • I prefer Biking speed to Walking speed
    • I prefer bike lanes to taking the lane (when there’s no door-zone)
    • I prefer using a narrow Bike Lane to Taking the lane (because fast moving traffic is terrifying)

approaching the Longfellow Bridge inbound on my bike as it is now:

View Larger Map

My options to cross the bridge are:

• • • Bike Lane: Dedicated space that is most direct, but dangerously close and fast car traffic is dangerous
    • Take the lane: Might be a good idea to avoid being side-swiped in that bike lane, but given the high-speed of cars, this would be stressful and increase chances of being rear-ended
    • Sidewalk: At least it’s separated from traffic, but it’s too narrow to bike by pedestrians, so I’d get going to slow I might as well walk across, and that’d take forever.

I’m biking down Comm. Ave. I have several options:

I’ll go with the bike lane and risk the fast moving traffic.

A paper on observed bicyclist behavior at red lights: http://www.rsconference.com/pdf/RS080140.pdf?check=1