Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections
Abstract
:1. Introduction
2. Methodology
- regular pavement, without distresses, ensuring high structural and functional performances (e.g., load bearing, adherence, regularity…);
- no adverse weather condition—the pavement is not contaminated, and the visibility is not impaired;
- efficient vehicles, both passenger cars and bicycles, with regular braking performances [37]; and
- an optimum and unobstructed view, to avoid impact.
2.1. Summary Approach
2.2. Elementary Approach
- the events that generate an opportunity for crash are all allowed maneuvers (i.e., crossing, left-turn, and right-turn);
- the mean hourly number of arrivals is equal from each approach, but the hourly vehicle flow QV does not necessarily coincide with the hourly bikes flow QB;
- bicycles and vehicles maneuvers per unit of time occur by a Poisson process, as shown by other transport risk analysis [45], according to Equation (6):
- the elementary unit of exposure is defined by Elvik et al. [32] (i.e., 1 s); therefore, according to Equation (6), the probability of at least one arrival (vehicles or bikes) during 1 s, is given by Equation (7):λ is calculated according to Equations (8) and (9), respectively, for the vehicles (λV) and bikes (λB):
- each maneuver from different approaches is independent of each other [13]; therefore, the probability that a vehicle p(V) impacts a bicycle p(B), within the same 1 s, is calculated according to Equation (10):
- the binomial distribution describes the real probability P that at least one crash might occur at the intersection where N conflict points have been detected according to Equation (11):
2.3. Overall Risk of Collision
- Scheme 1 (S1) is a symmetrical four-arm intersection without a bike path. The cyclists use the carriageway to cross the intersection (Figure 5a);
- Scheme 2 (S2) is a symmetrical four-arm intersection without a bike path. The cyclists use the pedestrian crossings to cross the intersection, using the shortest paths (Figure 5b);
- Scheme 3 (S3) is a four-arm intersection with a bike path (Figure 5c).
3. Results
3.1. Summary Approach
- Identification of the conflict areas: The envelope of different vehicle and bikes paths, from and to the same approaches, formed a whole conflict area. In this paper, all vehicles paths are green and all bike paths are orange.
- Calculation of the whole extension of conflict areas (ECA): ECA was the sum of the envelopes of conflict areas detected at the intersection.
- Identification of the most interfering maneuvers detected, according to the calculated conflict areas.
- Identification of the most dangerous maneuvers detected at the intersection, according to the minimum available ART.
- To calculate the cyclists’ exposure time to vehicles (ET).
3.2. Elementary Approach and Overall Risk Calculation
- S1 had the lowest number of functional CPs (i.e., 56), but most of them were red, none was green. The D values did not achieve the maximum value.
- S2 had 64 functional CPs and most of them were red; right-turn was the most dangerous maneuverer because its ART was 0 s, therefore, D had the highest value (i.e., 1.5). On the other hand, when compared to the other two schemes, S2 had the lowest values of D (i.e., slight interaction) in 19 yellow CPs.
- S3 had 64 functional CPs and more than half of them were red.
4. Discussion
- to locate the whole extension of the conflict areas identified by the envelope of interfering trajectories;
- to identify the most dangerous maneuvers, in terms of the time available to the vehicle users to avoid a collision, and the exposure time of cyclists; and
- to assess the current crash-risk between vehicles and bicycles.
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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ART (s) | Level of Damage | D | Chromatic Categorization |
---|---|---|---|
0 < ART ≤ 1.5 | Very dangerous interaction | 1 ≤ D ≤ 1.5 | ● |
1.5 < ART ≤ 3 | Dangerous interaction | 0.5 < D ≤ 1 | ● |
3 < ART ≤ 4.5 | Slight interaction | 0 < D ≤ 0.5 | ● |
ART > 4.5 | No interaction | - | ● |
Scheme | ECA (m2) | Analysis of Conflict Areas | Analysis of Maneuvers | Maximum ART (s) | Minimum ET (s) | Maximum ET (s) | ||
---|---|---|---|---|---|---|---|---|
Most Interfering Maneuvers (-) | Largest ECA (m2) | Most Dangerous Maneuvers (-) | Minimum ART (s) | |||||
S1 | 96.08 | (I-III)V-(I-IV)B (II-IV)V-(II-I)B (III-I)V-(III-II)B (IV-II)V-(IV-III)B | 8.75 | (right-turn)V-(crossing)B (right-turn)V-(left-turn)B | 0.49 | 3.38 | 6.42 | 15.76 |
S2 | 118.36 | (I-II)V-(I-II, I-IV, II-IV, IV-II)B (II-III)V-(II-III, II-I, III-I, I-III)B (III-IV)V-(III-IV, III-II, IV-II, II-IV)B (IV-I)V-(IV-I, IV-III, I-III, III-I)B | 8.41 | (right-turn)V-(left-turn)B (left-turn)V-(left-turn)B (crossing)V-(left-turn)B | 0.00 | 5.13 | 6.30 | 12.06 |
S3 | 22.41 | (II-I)V-(I-II, I-III, I-IV, II-I, II-IV, III-I, III-IV, IV-I,I V-II, IV-III)B | 1.89 | (II-III)V-(I-II)B (II-III)V-(I-III)B (II-III)V-(I-IV)B | 0.68 | 4.11 | 3.48 | 20.75 |
Scheme | Total Number of CPs | Number of Red CPs | Number of Orange CPs | Number of Yellow CPs | Number of Green CPs |
---|---|---|---|---|---|
S1 | 56 | 32 | 12 | 12 | 0 |
S2 | 24 | 12 | 4 | 8 | 0 |
S3 | 24 | 16 | 0 | 8 | 0 |
Scheme | p | P | R | Minimum Rij | Maximum Rij |
---|---|---|---|---|---|
S1 | 7.45 × 10−4 | 4.09 × 10−2 | 3.71 × 10−2 | 2.79 × 10−4 | 5.46 × 10−2 |
S2 | 7.45 × 10−4 | 1.77 × 10−2 | 1.67 × 10−2 | 5.23 × 10−4 | 2.66 × 10−2 |
S3 | 7.45 × 10−4 | 1.92 × 10−2 | 1.67 × 10−2 | 3.01 × 10−3 | 2.45 × 10−2 |
Class of Risk | Maximum Rij | Minimum Rij |
---|---|---|
α | 1.00 × 10−1 | <1.00 × 10−2 |
β | 1.00 × 10−2 | <1.00 × 10−3 |
γ | 1.00 × 10−3 | <1.00 × 10−4 |
Vehicle Maneuver | Percentage of CPs (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|
Right-turn | Crossing | Left-turn | |||||||
Class of Risk Scheme | γ | β | α | γ | β | α | γ | β | α |
S1 | 0 | 0 | 27 | 20 | 0 | 20 | 6 | 0 | 27 |
S2 | 0 | 0 | 30 | 17 | 2 | 19 | 0 | 13 | 19 |
S3 | 0 | 2 | 34 | 0 | 16 | 16 | 0 | 16 | 16 |
Traffic ID | Traffic Volume | R | |||
---|---|---|---|---|---|
QV (veh./h) | QB (veh./h) | S1 | S2 | S3 | |
T1 | 700 | 40 | 9.40 × 10−2 | 4.30 × 10−2 | 4.31 × 10−2 |
T2 | 500 | 70 | 1.18 × 10−1 | 5.47 × 10−2 | 5.47 × 10−2 |
T3 | 400 | 120 | 1.59 × 10−1 | 7.47 × 10−2 | 7.47 × 10−2 |
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Cantisani, G.; Moretti, L.; De Andrade Barbosa, Y. Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections. Safety 2019, 5, 6. https://doi.org/10.3390/safety5010006
Cantisani G, Moretti L, De Andrade Barbosa Y. Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections. Safety. 2019; 5(1):6. https://doi.org/10.3390/safety5010006
Chicago/Turabian StyleCantisani, Giuseppe, Laura Moretti, and Yessica De Andrade Barbosa. 2019. "Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections" Safety 5, no. 1: 6. https://doi.org/10.3390/safety5010006
APA StyleCantisani, G., Moretti, L., & De Andrade Barbosa, Y. (2019). Safety Problems in Urban Cycling Mobility: A Quantitative Risk Analysis at Urban Intersections. Safety, 5(1), 6. https://doi.org/10.3390/safety5010006