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Connected vehicle technology can help the driver make decisions, improve awareness of the road environment, and thereby possibly enhance traffic safety. This study explored the impact of a motorcycle vehicle‐to‐infrastructure (V2I) warning system on road safety through a field trial of a Motorcycle Safety Warning System (MSWS). This study used principal component analysis, K‐means, and ordinal logistic regression to explore the effects of the MSWS. After system activation, the road safety level (RSL) improved at 50% of the field trial sites. This study provides a reference for evaluating RSLs through the composite index of this study and verifies that the V2I warning signs of the MSWS provide a certain degree of improvement of motorcycle traffic safety. A V2I system like the MSWS can be used to collect data on driving behaviours in a short period for safety effect analysis, as compared to crash data, which require an extended period. In addition, the traffic behaviour data collected by a V2I system can also be used to identify potential high crash risk locations. The warning signs developed in this study can prevent accidents by alerting drivers who are speeding and at risk of crashes.

The mixed traffic environment often has high accident rates. Therefore, many motorcycle-related traffic improvements or control methods are employed in countries with mixed traffic, including slow-traffic lanes, motorcycle two-stage left turn areas, and motorcycle waiting zones. In Taiwan, motorcycles can ride in only the two outermost lanes, including the curb lane and a mixed traffic lane. This study analyzed the new motorcycle-riding space control policy on 27 major arterial roads containing 248 road segments in Taipei by analyzing before-and-after accident data from the years 2012–2018. In this study, the equivalent-property-damage-only (EPDO) method was used to evaluate the severity of crashes before and after the cancelation of the third lane prohibition of motorcycles (TLPM) policy. After EPDO analysis, the random forest analysis method was used to screen the crucial factors in accidents for specific road segments. Finally, a classification and regression tree (CART) was created to predict the accident improvement effects of the road segments with discontinued TLPM in different situations. Furthermore, to provide practical applications, this study integrated the CART results and the needs of traffic authorities to determine four rules for canceling TLPM. In the future, on the accident-prone road segment with TLPM, the inspection of the four rules can provide the authority to decide whether to cancel TLPM to improve the accident or not.

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Taiwan has the highest motorcycle ownership of 608 motorcycles per 1000 people in the world. The motorcycle safety is always the hottest issue. This paper aimed at analysing the most frequently occurred collision types of motorcycle involved accidents according to the accident data collected at 80 selected highest accident prone intersections and then to create the new countermeasures accordingly. The most frequently occurred collision types are 1. Sideswiped collision due to change lane, 2. Right Angel collision during change interval, 3.Left turning other Angle collision by left turning movement raised by turning movement against straight movement, 4. Right turning other Angle collision by right turning movement raised by turning movement against through movement, and Rear-end collision related to change interval and width of intersection. The effective countermeasures proven include the right turn lane layout modification, the inter-green time recalculated according to the motorcycle speed, separate direction of movement between car and motorcycle, and to provide the segregate waiting zone the turning movement.